| Date | Title | Provider |
| 2010 |
Orthophotos of Allegheny County, Pennsylvania - An orthoimage is remotely sensed image data that has been positionally corrected for camera lens distortion, vertical displacement and variations in aircraft altitude and orientation. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map. Aerial survey of Allegheny County,Pennsylvania. Orthophotos serve a variety of purposes, from interim maps to field references for earth science investigations and analysis. The digital orthophoto is useful as a layer of a geographic information system and as a tool for revision of digital line graphs and topographic maps.
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| Allegheny County |
| 2010 |
Tile Index - Orthophotos of Allegheny County, Pennsylvania - An orthoimage is remotely sensed image data that has been positionally corrected for camera lens distortion, vertical displacement and variations in aircraft altitude and orientation. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map. Aerial survey of Allegheny County,Pennsylvania. Orthophotos serve a variety of purposes, from interim maps to field references for earth science investigations and analysis. The digital orthophoto is useful as a layer of a geographic information system and as a tool for revision of digital line graphs and topographic maps.
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| Allegheny County |
| 2013 |
Orthophotos of Allegheny County, Pennsylvania - An orthoimage is remotely sensed image data that has been positionally corrected for camera lens distortion, vertical displacement and variations in aircraft altitude and orientation. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map. Aerial survey of Allegheny County,Pennsylvania. Orthophotos serve a variety of purposes, from interim maps to field references for earth science investigations and analysis. The digital orthophoto is useful as a layer of a geographic information system and as a tool for revision of digital line graphs and topographic maps.
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| Allegheny County |
| 2013 |
Orthophotos of Allegheny County, Pennsylvania - An orthoimage is remotely sensed image data that has been positionally corrected for camera lens distortion, vertical displacement and variations in aircraft altitude and orientation. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map. Aerial survey of Allegheny County,Pennsylvania. Orthophotos serve a variety of purposes, from interim maps to field references for earth science investigations and analysis. The digital orthophoto is useful as a layer of a geographic information system and as a tool for revision of digital line graphs and topographic maps.
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| Allegheny County |
| 2015 |
Orthophotos of Allegheny County, Pennsylvania - An orthoimage is remotely sensed image data that has been positionally corrected for camera lens distortion, vertical displacement and variations in aircraft altitude and orientation. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map. Aerial survey of Allegheny County,Pennsylvania. Orthophotos serve a variety of purposes, from interim maps to field references for earth science investigations and analysis. The digital orthophoto is useful as a layer of a geographic information system and as a tool for revision of digital line graphs and topographic maps.
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| Allegheny County |
| 2015 |
Tile Index - Orthophotos of Allegheny County, Pennsylvania - An orthoimage is remotely sensed image data that has been positionally corrected for camera lens distortion, vertical displacement and variations in aircraft altitude and orientation. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map. Aerial survey of Allegheny County,Pennsylvania. Orthophotos serve a variety of purposes, from interim maps to field references for earth science investigations and analysis. The digital orthophoto is useful as a layer of a geographic information system and as a tool for revision of digital line graphs and topographic maps.
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| Allegheny County |
| 2017 |
Orthophotos of Allegheny County, Pennsylvania - An orthoimage is remotely sensed image data that has been positionally corrected for camera lens distortion, vertical displacement and variations in aircraft altitude and orientation. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map. Aerial survey of Allegheny County,Pennsylvania. Orthophotos serve a variety of purposes, from interim maps to field references for earth science investigations and analysis. The digital orthophoto is useful as a layer of a geographic information system and as a tool for revision of digital line graphs and topographic maps.
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| Allegheny County |
| 2017 |
Orthophotos of Allegheny County, Pennsylvania - An orthoimage is remotely sensed image data that has been positionally corrected for camera lens distortion, vertical displacement and variations in aircraft altitude and orientation. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map. Aerial survey of Allegheny County,Pennsylvania. Orthophotos serve a variety of purposes, from interim maps to field references for earth science investigations and analysis. The digital orthophoto is useful as a layer of a geographic information system and as a tool for revision of digital line graphs and topographic maps.
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| Allegheny County |
| 2017 |
Tile Index - Orthophotos of Allegheny County, Pennsylvania - An orthoimage is remotely sensed image data that has been positionally corrected for camera lens distortion, vertical displacement and variations in aircraft altitude and orientation. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map. Aerial survey of Allegheny County,Pennsylvania. Orthophotos serve a variety of purposes, from interim maps to field references for earth science investigations and analysis. The digital orthophoto is useful as a layer of a geographic information system and as a tool for revision of digital line graphs and topographic maps.
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| Allegheny County |
| 2017 |
Tile Index - Orthophotos of Allegheny County, Pennsylvania - An orthoimage is remotely sensed image data that has been positionally corrected for camera lens distortion, vertical displacement and variations in aircraft altitude and orientation. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map. Aerial survey of Allegheny County,Pennsylvania. Orthophotos serve a variety of purposes, from interim maps to field references for earth science investigations and analysis. The digital orthophoto is useful as a layer of a geographic information system and as a tool for revision of digital line graphs and topographic maps.
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| Allegheny County |
| 2010 |
(2010) Pennsylvania area natural color seamless orthoimagery acquired by Aerials Express at a 45cm pixel-resolution. Flight operations began on 12/11/09 and ended on 04/10/10 using an (DMC) camera with an approximate forward overlap of 60% and side overlap of 30% with an approximate Ground Sample Distance of (44 cm). The dataset is projected as Universal Transverse Mercator (UTM) 17 on the North American Datum of 1983. The PAMAP Program LiDAR Data of Pennsylvania; West Virginia Statewide Digital Elevation Models; USGS National Elevation Dataset (NED) - (Used in the respective sequential order) were utilized as the Digital Elevation Model in ortho-processing.
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| DCNR PAMAP Program |
| 2010 |
TILE INDEX North - (2010) Pennsylvania area natural color seamless orthoimagery acquired by Aerials Express at a 45cm pixel-resolution. Flight operations began on 12/11/09 and ended on 04/10/10 using an (DMC) camera with an approximate forward overlap of 60% and side overlap of 30% with an approximate Ground Sample Distance of (44 cm). The dataset is projected as Universal Transverse Mercator (UTM) 17 on the North American Datum of 1983. The PAMAP Program LiDAR Data of Pennsylvania; West Virginia Statewide Digital Elevation Models; USGS National Elevation Dataset (NED) - (Used in the respective sequential order) were utilized as the Digital Elevation Model in ortho-processing.
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| DCNR PAMAP Program |
| 2010 |
TILE INDEX South - (2010) Pennsylvania area natural color seamless orthoimagery acquired by Aerials Express at a 45cm pixel-resolution. Flight operations began on 12/11/09 and ended on 04/10/10 using an (DMC) camera with an approximate forward overlap of 60% and side overlap of 30% with an approximate Ground Sample Distance of (44 cm). The dataset is projected as Universal Transverse Mercator (UTM) 17 on the North American Datum of 1983. The PAMAP Program LiDAR Data of Pennsylvania; West Virginia Statewide Digital Elevation Models; USGS National Elevation Dataset (NED) - (Used in the respective sequential order) were utilized as the Digital Elevation Model in ortho-processing.
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| DCNR PAMAP Program |
| 2003 - 2006 |
Orthoimagery for south-central Pennsylvania captured in April of 2003. An orthoimage is remotely sensed image data in which displacement of features in the image caused by terrain relief and sensor orientation have been mathematically removed. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map. For this dataset, the natural color orthoimages were produced at 2-feet pixel resolution. The design accuracy is estimated not to exceed 4.8 feet at the 95% confidence level. Each orthoimage provides imagery for a 10,000 by 10,000 feet block on the ground. The projected coordinate system is Pennsylvania State Plane with a NAD83 datum. There is no image overlap been adjacent files. The ortho image filenames were derived from the northwest corner of each ortho tile using the first four digits of the northing and easting coordinates referenced to the Pennsylvania State Plane coordinate system, followed by the State designator "PA", and the State Plane zone designator "S".
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| DCNR PAMAP Program |
| 2007 - 2008 |
This dataset, produced by the PAMAP Program, consists of an orthorectified digital raster image (i.e. orthoimage) with a horizontal ground resolution of 1 foot. An orthoimage is a remotely sensed image that has been positionally corrected for camera lens distortion, vertical displacement, and variations in aircraft altitude and orientation. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map. Source images were captured in natural color at a negative scale of 1:19200. PAMAP data are organized into blocks, which do not have gaps or overlaps, that represent 10,000 feet by 10,000 feet on the ground. The coordinate system for blocks in the northern half of the state is Pennsylvania State Plane North (datum:NAD83, units: feet); blocks in the southern half of the state are in Pennsylvania State Plane South. A block name is formed by concatenating the first four digits of the State Plane northing and easting defining the block's northwest corner, the State identifier "PA", and the State Plane zone designator "N" or "S" (e.g. 45001210PAS).
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| DCNR PAMAP Program |
| 2003 - 2006 |
County Mosaics MR.SID format - An orthoimage is remotely sensed image data that has been positionally corrected for camera lens distortion, vertical displacement and variations in aircraft altitude and orientation. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map. The PAMAP 2005 natural color orthoimages were produced at 1-foot pixel resolution. Each orthoimage provides imagery for a 10,000 x 10,000 ft. block on the ground. The projected coordinate system is Pennsylvania State Plane South with a NAD83 datum. There is no image overlap been adjacent files. The orthoimage filenames were derived from the northwest corner of each ortho tile using the first four digits of the northing and easting coordinates referenced to the Pennsylvania State Plane coordinate system, followed by the State designator "PA," and the State Plane zone designator "S." This dataset consists of 10000 x 10000 ft. uncompressed natural color (24-bit) GeoTIFF files at a pixel resolution of 1 foot. The imagery was captured at a negative scale of 1:19200 for the purpose of producing orthophotos.
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| DCNR PAMAP Program |
| 2007 - 2008 |
County Mosaics JPEG 2000 format - This dataset, produced by the PAMAP Program, consists of an orthorectified digital raster image (i.e. orthoimage) with a horizontal ground resolution of 1 foot. An orthoimage is a remotely sensed image that has been positionally corrected for camera lens distortion, vertical displacement, and variations in aircraft altitude and orientation. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map. Source images were captured in natural color at a negative scale of 1:19200. PAMAP data are organized into blocks, which do not have gaps or overlaps, that represent 10,000 feet by 10,000 feet on the ground. The coordinate system for blocks in the northern half of the state is Pennsylvania State Plane North (datum:NAD83, units: feet); blocks in the southern half of the state are in Pennsylvania State Plane South. A block name is formed by concatenating the first four digits of the State Plane northing and easting defining the block's northwest corner, the State identifier "PA", and the State Plane zone designator "N" or "S" (e.g. 45001210PAS).
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| DCNR PAMAP Program |
| 2000 |
An orthoimage is remotely sensed image data in which displacement of features in the image caused by terrain relief and sensor orientation have been mathematically removed. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map.
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| Delaware Valley Regional Planning Commission |
| 2000 |
Tile Index - An orthoimage is remotely sensed image data in which displacement of features in the image caused by terrain relief and sensor orientation have been mathematically removed. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map.
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| Delaware Valley Regional Planning Commission |
| 2005 |
Mosaic - An orthoimage is remotely sensed image data in which displacement of features in the image caused by terrain relief and sensor orientation have been mathematically removed. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map. This project consists of the creation of 3-band, 24 bit color digital orthophoto tiles for the 5-county, Pennsylvania portion DVRPC?s region utilizing a Leica ADS40 digital imaging system. The tiles were delivered in both GeoTIFF and MrSID MG3 formats. A GeoTIFF is a TIFF file which has geographic (or cartographic) data embedded as tags within the TIFF file. The geographic data can then be used to position the image in the correct location and geometry within a geographic information system (GIS) display. MrSID (Multi-resolution Seamless Image Database) is a proprietary, wavelet-based, image compression file format (*.sid) developed and patented by LizardTech, Inc. A 20:1 compression ratio was used for the MrSIDs. The complete data set contains 1,540 full ortho tiles in Pennsylvania State Plane South coordinate system, NAD83. The individual tiles measure 5,055' x 8,745' at a 1.0' pixel size. There is no image overlap between adjacent tiles. Counties include: Bucks, Chester, Delaware, Montgomery, and Philadelphia.
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| Delaware Valley Regional Planning Commission |
| 2005 |
An orthoimage is remotely sensed image data in which displacement of features in the image caused by terrain relief and sensor orientation have been mathematically removed. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map. This project consists of the creation of 3-band, 24 bit color digital orthophoto tiles for the 5-county, Pennsylvania portion DVRPC?s region utilizing a Leica ADS40 digital imaging system. The tiles were delivered in both GeoTIFF and MrSID MG3 formats. A GeoTIFF is a TIFF file which has geographic (or cartographic) data embedded as tags within the TIFF file. The geographic data can then be used to position the image in the correct location and geometry within a geographic information system (GIS) display. MrSID (Multi-resolution Seamless Image Database) is a proprietary, wavelet-based, image compression file format (*.sid) developed and patented by LizardTech, Inc. A 20:1 compression ratio was used for the MrSIDs. The complete data set contains 1,540 full ortho tiles in Pennsylvania State Plane South coordinate system, NAD83. The individual tiles measure 5,055' x 8,745' at a 1.0' pixel size. There is no image overlap between adjacent tiles.
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| Delaware Valley Regional Planning Commission |
| 2005 |
TILE INDEX - An orthoimage is remotely sensed image data in which displacement of features in the image caused by terrain relief and sensor orientation have been mathematically removed. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map. This project consists of the creation of 3-band, 24 bit color digital orthophoto tiles for the 5-county, Pennsylvania portion DVRPC?s region utilizing a Leica ADS40 digital imaging system. The tiles were delivered in both GeoTIFF and MrSID MG3 formats. A GeoTIFF is a TIFF file which has geographic (or cartographic) data embedded as tags within the TIFF file. The geographic data can then be used to position the image in the correct location and geometry within a geographic information system (GIS) display. MrSID (Multi-resolution Seamless Image Database) is a proprietary, wavelet-based, image compression file format (*.sid) developed and patented by LizardTech, Inc. A 20:1 compression ratio was used for the MrSIDs. The complete data set contains 1,540 full ortho tiles in Pennsylvania State Plane South coordinate system, NAD83. The individual tiles measure 5,055' x 8,745' at a 1.0' pixel size. There is no image overlap between adjacent tiles.
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| Delaware Valley Regional Planning Commission |
| 2010 |
Mosaic - An orthoimage is remotely sensed image data in which displacement of features in the image caused by terrain relief and sensor orientation have been mathematically removed. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map. This project consists of the creation of 3-band, 24 bit color digital orthophoto tiles for the 5-county, Pennsylvania portion DVRPC?s region utilizing a Leica ADS40 digital imaging system. The tiles were delivered in both GeoTIFF and MrSID MG3 formats. A GeoTIFF is a TIFF file which has geographic (or cartographic) data embedded as tags within the TIFF file. The geographic data can then be used to position the image in the correct location and geometry within a geographic information system (GIS) display. MrSID (Multi-resolution Seamless Image Database) is a proprietary, wavelet-based, image compression file format (*.sid) developed and patented by LizardTech, Inc. A 20:1 compression ratio was used for the MrSIDs. The complete data set contains 1,540 full ortho tiles in Pennsylvania State Plane South coordinate system, NAD83. The individual tiles measure 5,055' x 8,745' at a 1.0' pixel size. There is no image overlap between adjacent tiles. Counties include: Bucks, Chester, Delaware, Montgomery, and Philadelphia.
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| Delaware Valley Regional Planning Commission |
| 2010 |
An orthoimage is remotely sensed image data in which displacement of features in the image caused by terrain relief and sensor orientation have been mathematically removed. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map. This project consists of the creation of 3-band, 24 bit color digital orthophoto tiles for the 5-county, Pennsylvania portion DVRPC?s region utilizing a Leica ADS40 digital imaging system. The tiles were delivered in both GeoTIFF and MrSID MG3 formats. A GeoTIFF is a TIFF file which has geographic (or cartographic) data embedded as tags within the TIFF file. The geographic data can then be used to position the image in the correct location and geometry within a geographic information system (GIS) display. MrSID (Multi-resolution Seamless Image Database) is a proprietary, wavelet-based, image compression file format (*.sid) developed and patented by LizardTech, Inc. A 20:1 compression ratio was used for the MrSIDs. The complete data set contains 1,540 full ortho tiles in Pennsylvania State Plane South coordinate system, NAD83. The individual tiles measure 5,055' x 8,745' at a 1.0' pixel size. There is no image overlap between adjacent tiles.
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| Delaware Valley Regional Planning Commission |
| 2010 |
TILE INDEX - An orthoimage is remotely sensed image data in which displacement of features in the image caused by terrain relief and sensor orientation have been mathematically removed. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map. This project consists of the creation of 3-band, 24 bit color digital orthophoto tiles for the 5-county, Pennsylvania portion DVRPC?s region utilizing a Leica ADS40 digital imaging system. The tiles were delivered in both GeoTIFF and MrSID MG3 formats. A GeoTIFF is a TIFF file which has geographic (or cartographic) data embedded as tags within the TIFF file. The geographic data can then be used to position the image in the correct location and geometry within a geographic information system (GIS) display. MrSID (Multi-resolution Seamless Image Database) is a proprietary, wavelet-based, image compression file format (*.sid) developed and patented by LizardTech, Inc. A 20:1 compression ratio was used for the MrSIDs. The complete data set contains 1,540 full ortho tiles in Pennsylvania State Plane South coordinate system, NAD83. The individual tiles measure 5,055' x 8,745' at a 1.0' pixel size. There is no image overlap between adjacent tiles.
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| Delaware Valley Regional Planning Commission |
| 2016 |
Multi-spectral digital orthophotography was produced at a scale of 1:2400 (1 in = 200 ft) with a 12 inch pixel resolution for the DVRPC - PA project area. Digital orthophotography combines the image characteristics of a photograph with the geometric qualities of a map. Orthophoto data is produced through the use of digitized perspective aerial photographs or other remotely sensed image data. This data is processed into a digital product that has been rectified for camera lens distortion, vertical displacement caused by terrain relief, and variations in aircraft altitude and orientation.
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| Delaware Valley Regional Planning Commission |
| 2016 |
Multi-spectral digital orthophotography was produced at a scale of 1:2400 (1 in = 200 ft) with a 12 inch pixel resolution for the DVRPC - PA project area. Digital orthophotography combines the image characteristics of a photograph with the geometric qualities of a map. Orthophoto data is produced through the use of digitized perspective aerial photographs or other remotely sensed image data. This data is processed into a digital product that has been rectified for camera lens distortion, vertical displacement caused by terrain relief, and variations in aircraft altitude and orientation.
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| Delaware Valley Regional Planning Commission |
| 2016 |
Multi-spectral digital orthophotography was produced at a scale of 1:2400 (1 in = 200 ft) with a 12 inch pixel resolution for the DVRPC - PA project area. Digital orthophotography combines the image characteristics of a photograph with the geometric qualities of a map. Orthophoto data is produced through the use of digitized perspective aerial photographs or other remotely sensed image data. This data is processed into a digital product that has been rectified for camera lens distortion, vertical displacement caused by terrain relief, and variations in aircraft altitude and orientation.
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| Delaware Valley Regional Planning Commission |
| 2020 |
This orthoimagery consists of 1-foot pixel resolution, 3-band, natural color county mosaics in JPEG 2000 format covering the Delaware Valley Regional Planning Commission’s (DVRPC) 9-county region (Bucks, Chester, Delaware, Montgomery, and Philadelphia counties in Pennsylvania; and Burlington, Camden, Gloucester, and Mercer counties in New Jersey). This orthoimagery was acquired in the late winter/early spring of 2020. An orthoimage is remotely sensed image data in which displacement of features in the image caused by terrain relief and sensor orientation have been mathematically removed. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map.
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| Delaware Valley Regional Planning Commission |
| 1959 - 1995 |
Prior to the year 2000, DVRPC’s aerial imagery consisted of mylar aerial photo
enlargements or “atlas sheets”. These atlas sheets were produced from 9x9" aerial
photos. The imagery dates from the years 1959, 1965, 1970, 1975, 1980, 1985, 1990,
& 1995. The 1959s and 1965s primarily cover the urbanized portion of
the DVRPC region (the DVRPC region is made up of nine counties: Bucks, Chester,
Delaware, Montgomery, and Philadelphia in Pennsylvania; Burlington, Camden,
Gloucester, and Mercer in New Jersey). Subsequent years provide full coverage of the
region, minus the occasional missing scan.
In order to increase the efficiency of using the historical aerial imagery, the sheets were
scanned into TIFF (Tagged Image File Format) files. Each TIFF file ranges between 35-
40MB in size. Unlike DVRPC’s more recent aerial imagery (2000 and later), the
historical aerials are not “orthorectified” or “orthocorrected”. In other words, they are
simply aerial images with no spatial reference or uniform scale. Through the process of
georeferencing, the scanned images can be assigned a spatial reference which will
enable them to be used more readily in a GIS environment. That said, georeferencing is
not orthorectifying or orthocorrecting. What it does allow is for the scan to be displayed
relative to other spatially referenced GIS layers. A georeferenced scan does not have
the properties of an actual orthoimage. Whereas an orthoimage can be used for making
accurate measurements, a georeferenced image cannot, as it does not have the spatial
accuracy and uniform scale of an orthoimage.
ftp://ftp.pasda.psu.edu/pub/pasda/dvrpc/DVRPC_Historical_Aerials/Indexes/DVRPC_Historical_Aerial_Index_Maps.pdf
https://www.dvrpc.org/webmaps/TileIndex/
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| Delaware Valley Regional Planning Commission |
| 2010 |
Digital orthophoto covering Lehigh and Northampton County, Pennsylvania that was flow in spring 2010. An orthoimage is remotely sensed image data that has been positionally corrected for camera lens distortion, vertical displacement and variations in aircraft altitude and orientation. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map.
Flown during leaf off conditions between March 27, 2010 and April 22, 2010.
Digital imagery at 1''=200 design scale natural color aerial photography at 1' pixel resolution.
Image tile dimensions are 5000' by 5000' and 1000tiles cover the entirety of Lehigh and Northampton Counties.
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| Lehigh Valley Planning Commission |
| 2010 |
TILE INDEX - Digital orthophoto covering Lehigh and Northampton County, Pennsylvania that was flow in spring 2010. An orthoimage is remotely sensed image data that has been positionally corrected for camera lens distortion, vertical displacement and variations in aircraft altitude and orientation. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map.
Flown during leaf off conditions between March 27, 2010 and April 22, 2010.
Digital imagery at 1''=200 design scale natural color aerial photography at 1' pixel resolution.
Image tile dimensions are 5000' by 5000' and 1000tiles cover the entirety of Lehigh and Northampton Counties.
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| Lehigh Valley Planning Commission |
| 2016 |
Multi-spectral digital orthophotography was produced at a scale of 1:2400 (1 in = 200 ft) with a 12 inch pixel resolution for the LVPC project area. Digital orthophotography combines the image characteristics of a photograph with the geometric qualities of a map. Orthophoto data is produced through the use of digitized perspective aerial photographs or other remotely sensed image data. This data is processed into a digital product that has been rectified for camera lens distortion, vertical displacement caused by terrain relief, and variations in aircraft altitude and orientation.
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| Lehigh Valley Planning Commission |
| 2016 |
Multi-spectral digital orthophotography was produced at a scale of 1:2400 (1 in = 200 ft) with a 12 inch pixel resolution for the LVPC project area. Digital orthophotography combines the image characteristics of a photograph with the geometric qualities of a map. Orthophoto data is produced through the use of digitized perspective aerial photographs or other remotely sensed image data. This data is processed into a digital product that has been rectified for camera lens distortion, vertical displacement caused by terrain relief, and variations in aircraft altitude and orientation.
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| Lehigh Valley Planning Commission |
| 2016 |
Multi-spectral digital orthophotography was produced at a scale of 1:2400 (1 in = 200 ft) with a 12 inch pixel resolution for the LVPC project area. Digital orthophotography combines the image characteristics of a photograph with the geometric qualities of a map. Orthophoto data is produced through the use of digitized perspective aerial photographs or other remotely sensed image data. This data is processed into a digital product that has been rectified for camera lens distortion, vertical displacement caused by terrain relief, and variations in aircraft altitude and orientation.
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| Lehigh Valley Planning Commission |
| 2024 |
Road segments representing centerlines of all roadways or carriageways in a local government. Typically, this information is compiled from orthoimagery or other aerial photography sources. This representation of the road centerlines support address geocoding and mapping. It also serves as a source for public works and other agencies that are responsible for the active management of the road network.
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| Mercer County |
| 2018 - 2020 |
This orthoimagery data set includes 0.5-foot (15-centimeter) 8-bit 4-band (RGBN) digital orthoimage tiles in GeoTIFF, Mr. SID, and JPEG 2000(JP2) format. The PEMA 2018 0.5-foot Orthoimagery called for the planning, acquisition, processing, and derivative products of imagery data to be collected at a ground sample distance (GSD) of 0.5-foot (15 centimeters). Project specifications are based on the U.S. Geological Survey National Geospatial Program Base Ortho Specification, Version 1.0. The data were developed based on a horizontal projection/datum of NAD83 (2011) State Plane Pennsylvania, US Survey Feet. Orthoimagery data was delivered as 298 individual 0.5-foot (15-centimeter) 1" = 100' GeoTIFF (uncompressed) 10,000-foot x 10,000-foot (3,048-meter x 3,048-meter) tiles. Aerial photography was captured during the spring of 2018, while no snow was on the ground and rivers were at or below normal levels. In order to post process the imagery data to meet task order specifications and meet horizontal accuracy guidelines, Quantum Spatial, Inc. utilized a total of 496 QC points throughout the Commonwealth of Pennsylvania to assess the horizontal accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| Pennsylvania Emergency Management Agency |
| 2018 - 2020 |
This orthoimagery data set includes 0.5-foot (15-centimeter) 8-bit 4-band (RGBN) digital orthoimage tiles in GeoTIFF, Mr. SID, and JPEG 2000(JP2) format. The PEMA 2018 0.5-foot Orthoimagery called for the planning, acquisition, processing, and derivative products of imagery data to be collected at a ground sample distance (GSD) of 0.5-foot (15 centimeters). Project specifications are based on the U.S. Geological Survey National Geospatial Program Base Ortho Specification, Version 1.0. The data were developed based on a horizontal projection/datum of NAD83 (2011) State Plane Pennsylvania, US Survey Feet. Orthoimagery data was delivered as 298 individual 0.5-foot (15-centimeter) 1" = 100' GeoTIFF (uncompressed) 10,000-foot x 10,000-foot (3,048-meter x 3,048-meter) tiles. Aerial photography was captured during the spring of 2018, while no snow was on the ground and rivers were at or below normal levels. In order to post process the imagery data to meet task order specifications and meet horizontal accuracy guidelines, Quantum Spatial, Inc. utilized a total of 496 QC points throughout the Commonwealth of Pennsylvania to assess the horizontal accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| Pennsylvania Emergency Management Agency |
| 2018 - 2020 |
This orthoimagery data set includes 0.5-foot (15-centimeter) 8-bit 4-band (RGBN) digital orthoimage tiles in GeoTIFF, Mr. SID, and JPEG 2000(JP2) format. The PEMA 2018 0.5-foot Orthoimagery called for the planning, acquisition, processing, and derivative products of imagery data to be collected at a ground sample distance (GSD) of 0.5-foot (15 centimeters). Project specifications are based on the U.S. Geological Survey National Geospatial Program Base Ortho Specification, Version 1.0. The data were developed based on a horizontal projection/datum of NAD83 (2011) State Plane Pennsylvania, US Survey Feet. Orthoimagery data was delivered as 298 individual 0.5-foot (15-centimeter) 1" = 100' GeoTIFF (uncompressed) 10,000-foot x 10,000-foot (3,048-meter x 3,048-meter) tiles. Aerial photography was captured during the spring of 2018, while no snow was on the ground and rivers were at or below normal levels. In order to post process the imagery data to meet task order specifications and meet horizontal accuracy guidelines, Quantum Spatial, Inc. utilized a total of 496 QC points throughout the Commonwealth of Pennsylvania to assess the horizontal accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| Pennsylvania Emergency Management Agency |
| 2018 - 2020 |
This orthoimagery data set includes 0.5-foot (15-centimeter) 8-bit 4-band (RGBN) digital orthoimage tiles in GeoTIFF, Mr. SID, and JPEG 2000(JP2) format. The PEMA 2018 0.5-foot Orthoimagery called for the planning, acquisition, processing, and derivative products of imagery data to be collected at a ground sample distance (GSD) of 0.5-foot (15 centimeters). Project specifications are based on the U.S. Geological Survey National Geospatial Program Base Ortho Specification, Version 1.0. The data were developed based on a horizontal projection/datum of NAD83 (2011) State Plane Pennsylvania, US Survey Feet. Orthoimagery data was delivered as 298 individual 0.5-foot (15-centimeter) 1" = 100' GeoTIFF (uncompressed) 10,000-foot x 10,000-foot (3,048-meter x 3,048-meter) tiles. Aerial photography was captured during the spring of 2018, while no snow was on the ground and rivers were at or below normal levels. In order to post process the imagery data to meet task order specifications and meet horizontal accuracy guidelines, Quantum Spatial, Inc. utilized a total of 496 QC points throughout the Commonwealth of Pennsylvania to assess the horizontal accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| Pennsylvania Emergency Management Agency |
| 2022 |
Counties include: Allegheny, Greene, Washington. This orthoimagery data set includes 0.5 foot 8-bit 4-band (RGBN) digital orthoimage tiles in GeoTIFF, Mr. SID, and JPEG 2000 (JP2) format.
Dataset Description: The PEMA 0.5-Foot Orthoimagery Delivery (US Survey Feet) project called for the planning, acquisition, processing, and derivative products of imagery data to be collected at a ground sample distance (GSD) of 0.5 foot. Project specifications are based on the American Society of Photogrammetry and Remote Sensing (ASPRS) standards. The data were developed based on a horizontal projection/datum of NAD 1983 HARN StatePlane Pennsylvania North FIPS 3701 Feet, Foot US.
Ground Conditions: Imagery was collected in spring 2022, while no snow was on the ground and rivers were at or below normal levels. In order to post process the imagery data to meet task order specifications and meet ASPRS horizontal accuracy guidelines, NV5 Geospatial utilized a total of 119 ground control points to assess the horizontal accuracy of the data.
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| Pennsylvania Emergency Management Agency |
| 2018 - 2020 |
This orthoimagery data set includes 0.5-foot (15-centimeter) 8-bit 4-band (RGBN) digital orthoimage tiles in GeoTIFF, Mr. SID, and JPEG 2000(JP2) format. The PEMA 2018 0.5-foot Orthoimagery called for the planning, acquisition, processing, and derivative products of imagery data to be collected at a ground sample distance (GSD) of 0.5-foot (15 centimeters). Project specifications are based on the U.S. Geological Survey National Geospatial Program Base Ortho Specification, Version 1.0. The data were developed based on a horizontal projection/datum of NAD83 (2011) State Plane Pennsylvania, US Survey Feet. Orthoimagery data was delivered as 298 individual 0.5-foot (15-centimeter) 1" = 100' GeoTIFF (uncompressed) 10,000-foot x 10,000-foot (3,048-meter x 3,048-meter) tiles. Aerial photography was captured during the spring of 2018, while no snow was on the ground and rivers were at or below normal levels. In order to post process the imagery data to meet task order specifications and meet horizontal accuracy guidelines, Quantum Spatial, Inc. utilized a total of 496 QC points throughout the Commonwealth of Pennsylvania to assess the horizontal accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| Pennsylvania Emergency Management Agency |
| 2018 - 2020 |
This orthoimagery data set includes 0.5-foot (15-centimeter) 8-bit 4-band (RGBN) digital orthoimage tiles in GeoTIFF, Mr. SID, and JPEG 2000(JP2) format. The PEMA 2018 0.5-foot Orthoimagery called for the planning, acquisition, processing, and derivative products of imagery data to be collected at a ground sample distance (GSD) of 0.5-foot (15 centimeters). Project specifications are based on the U.S. Geological Survey National Geospatial Program Base Ortho Specification, Version 1.0. The data were developed based on a horizontal projection/datum of NAD83 (2011) State Plane Pennsylvania, US Survey Feet. Orthoimagery data was delivered as 298 individual 0.5-foot (15-centimeter) 1" = 100' GeoTIFF (uncompressed) 10,000-foot x 10,000-foot (3,048-meter x 3,048-meter) tiles. Aerial photography was captured during the spring of 2018, while no snow was on the ground and rivers were at or below normal levels. In order to post process the imagery data to meet task order specifications and meet horizontal accuracy guidelines, Quantum Spatial, Inc. utilized a total of 496 QC points throughout the Commonwealth of Pennsylvania to assess the horizontal accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| Pennsylvania Emergency Management Agency |
| 2018 - 2020 |
This orthoimagery data set includes 0.5-foot (15-centimeter) 8-bit 4-band (RGBN) digital orthoimage tiles in GeoTIFF, Mr. SID, and JPEG 2000(JP2) format. The PEMA 2018 0.5-foot Orthoimagery called for the planning, acquisition, processing, and derivative products of imagery data to be collected at a ground sample distance (GSD) of 0.5-foot (15 centimeters). Project specifications are based on the U.S. Geological Survey National Geospatial Program Base Ortho Specification, Version 1.0. The data were developed based on a horizontal projection/datum of NAD83 (2011) State Plane Pennsylvania, US Survey Feet. Orthoimagery data was delivered as 298 individual 0.5-foot (15-centimeter) 1" = 100' GeoTIFF (uncompressed) 10,000-foot x 10,000-foot (3,048-meter x 3,048-meter) tiles. Aerial photography was captured during the spring of 2018, while no snow was on the ground and rivers were at or below normal levels. In order to post process the imagery data to meet task order specifications and meet horizontal accuracy guidelines, Quantum Spatial, Inc. utilized a total of 496 QC points throughout the Commonwealth of Pennsylvania to assess the horizontal accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| Pennsylvania Emergency Management Agency |
| 2021 - 2023 |
This orthoimagery data set includes 0.5 foot 8-bit 4-band (RGBN) digital orthoimage tiles in GeoTIFF, Mr. SID, and JPEG 2000 (JP2) format.
Dataset Description: The PEMA 0.5-Foot Orthoimagery Delivery (US Survey Feet) project called for the planning, acquisition, processing, and derivative products of imagery data to be collected at a ground sample distance (GSD) of 0.5 foot. Project specifications are based on the American Society of Photogrammetry and Remote Sensing (ASPRS) standards. The data were developed based on a horizontal projection/datum of NAD 1983 HARN StatePlane Pennsylvania North FIPS 3701 Feet, Foot US.
Ground Conditions: Imagery was collected in spring 2022, while no snow was on the ground and rivers were at or below normal levels. In order to post process the imagery data to meet task order specifications and meet ASPRS horizontal accuracy guidelines, NV5 Geospatial utilized a total of 119 ground control points to assess the horizontal accuracy of the data.
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| Pennsylvania Emergency Management Agency |
| 2021 - 2023 |
This orthoimagery data set includes 0.5 foot 8-bit 4-band (RGBN) digital orthoimage mosaics in GeoTIFF, Mr. SID, and JPEG 2000 (JP2) format. Dataset Description: The PEMA 2020-2021 0.5-Foot Orthoimagery project called for the planning, acquisition, processing, and derivative products of imagery data to be collected at a ground sample distance (GSD) of 0.5 foot. Project specifications are based on the American Society of Photogrammetry and Remote Sensing (ASPRS) standards. The data were developed based on a horizontal projection/datum of NAD 1983 HARN StatePlane Pennsylvania Feet, Foot US.. Ground Conditions: Imagery was collected in winter 2020 and 2021, while no snow was on the ground and rivers were at or below normal levels. In order to post process the imagery data to meet task order specifications and meet ASPRS horizontal accuracy guidelines, NV5 Geospatial utilized a total of 496 ground control points to assess the horizontal accuracy of the data.
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| Pennsylvania Emergency Management Agency |
| 2021 |
Counties include: Adams, Berks, Bucks, Carbon, Chester, Columbia, Cumberland, Dauphin, Delaware, Franklin, Lackawanna, Lancaster, Lebanon, Lehigh, Monroe, Montgomery, Northampton, Northumberland, Perry, Philadelphia, Pike, Schuylkill, Susquehanna, Wayne, Wyoming, York. Product: This orthoimagery data set includes 0.5 foot 8-bit 4-band (RGBN) digital orthoimage mosaics in GeoTIFF, Mr. SID, and JPEG 2000 (JP2) format. Dataset Description: The PEMA 2020-2021 0.5-Foot Orthoimagery project called for the planning, acquisition, processing, and derivative products of imagery data to be collected at a ground sample distance (GSD) of 0.5 foot. Project specifications are based on the American Society of Photogrammetry and Remote Sensing (ASPRS) standards. The data were developed based on a horizontal projection/datum of NAD 1983 HARN StatePlane Pennsylvania Feet, Foot US.. Ground Conditions: Imagery was collected in winter 2020 and 2021, while no snow was on the ground and rivers were at or below normal levels. In order to post process the imagery data to meet task order specifications and meet ASPRS horizontal accuracy guidelines, NV5 Geospatial utilized a total of 496 ground control points to assess the horizontal accuracy of the data.
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| Pennsylvania Emergency Management Agency |
| 2021 |
Counties include: Adams, Berks, Bucks, Carbon, Chester, Columbia, Cumberland, Dauphin, Delaware, Franklin, Lackawanna, Lancaster, Lebanon, Lehigh, Monroe, Montgomery, Northampton, Northumberland, Perry, Philadelphia, Pike, Schuylkill, Susquehanna, Wayne, Wyoming, York. Product: This orthoimagery data set includes 0.5 foot 8-bit 4-band (RGBN) digital orthoimage mosaics in GeoTIFF, Mr. SID, and JPEG 2000 (JP2) format. Dataset Description: The PEMA 2020-2021 0.5-Foot Orthoimagery project called for the planning, acquisition, processing, and derivative products of imagery data to be collected at a ground sample distance (GSD) of 0.5 foot. Project specifications are based on the American Society of Photogrammetry and Remote Sensing (ASPRS) standards. The data were developed based on a horizontal projection/datum of NAD 1983 HARN StatePlane Pennsylvania Feet, Foot US.. Ground Conditions: Imagery was collected in winter 2020 and 2021, while no snow was on the ground and rivers were at or below normal levels. In order to post process the imagery data to meet task order specifications and meet ASPRS horizontal accuracy guidelines, NV5 Geospatial utilized a total of 496 ground control points to assess the horizontal accuracy of the data.
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| Pennsylvania Emergency Management Agency |
| 2021 |
Counties include: Adams, Berks, Bucks, Carbon, Chester, Columbia, Cumberland, Dauphin, Delaware, Franklin, Lackawanna, Lancaster, Lebanon, Lehigh, Monroe, Montgomery, Northampton, Northumberland, Perry, Philadelphia, Pike, Schuylkill, Susquehanna, Wayne, Wyoming, York. Product: This orthoimagery data set includes 0.5 foot 8-bit 4-band (RGBN) digital orthoimage mosaics in GeoTIFF, Mr. SID, and JPEG 2000 (JP2) format. Dataset Description: The PEMA 2020-2021 0.5-Foot Orthoimagery project called for the planning, acquisition, processing, and derivative products of imagery data to be collected at a ground sample distance (GSD) of 0.5 foot. Project specifications are based on the American Society of Photogrammetry and Remote Sensing (ASPRS) standards. The data were developed based on a horizontal projection/datum of NAD 1983 HARN StatePlane Pennsylvania Feet, Foot US.. Ground Conditions: Imagery was collected in winter 2020 and 2021, while no snow was on the ground and rivers were at or below normal levels. In order to post process the imagery data to meet task order specifications and meet ASPRS horizontal accuracy guidelines, NV5 Geospatial utilized a total of 496 ground control points to assess the horizontal accuracy of the data.
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| Pennsylvania Emergency Management Agency |
| 2021 |
Counties include: Adams, Berks, Bucks, Carbon, Chester, Columbia, Cumberland, Dauphin, Delaware, Franklin, Lackawanna, Lancaster, Lebanon, Lehigh, Monroe, Montgomery, Northampton, Northumberland, Perry, Philadelphia, Pike, Schuylkill, Susquehanna, Wayne, Wyoming, York. Product: This orthoimagery data set includes 0.5 foot 8-bit 4-band (RGBN) digital orthoimage mosaics in GeoTIFF, Mr. SID, and JPEG 2000 (JP2) format. Dataset Description: The PEMA 2020-2021 0.5-Foot Orthoimagery project called for the planning, acquisition, processing, and derivative products of imagery data to be collected at a ground sample distance (GSD) of 0.5 foot. Project specifications are based on the American Society of Photogrammetry and Remote Sensing (ASPRS) standards. The data were developed based on a horizontal projection/datum of NAD 1983 HARN StatePlane Pennsylvania Feet, Foot US.. Ground Conditions: Imagery was collected in winter 2020 and 2021, while no snow was on the ground and rivers were at or below normal levels. In order to post process the imagery data to meet task order specifications and meet ASPRS horizontal accuracy guidelines, NV5 Geospatial utilized a total of 496 ground control points to assess the horizontal accuracy of the data.
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| Pennsylvania Emergency Management Agency |
| 2021 |
Counties include: Adams, Berks, Bucks, Carbon, Chester, Columbia, Cumberland, Dauphin, Delaware, Franklin, Lackawanna, Lancaster, Lebanon, Lehigh, Monroe, Montgomery, Northampton, Northumberland, Perry, Philadelphia, Pike, Schuylkill, Susquehanna, Wayne, Wyoming, York. Product: This orthoimagery data set includes 0.5 foot 8-bit 4-band (RGBN) digital orthoimage mosaics in GeoTIFF, Mr. SID, and JPEG 2000 (JP2) format. Dataset Description: The PEMA 2020-2021 0.5-Foot Orthoimagery project called for the planning, acquisition, processing, and derivative products of imagery data to be collected at a ground sample distance (GSD) of 0.5 foot. Project specifications are based on the American Society of Photogrammetry and Remote Sensing (ASPRS) standards. The data were developed based on a horizontal projection/datum of NAD 1983 HARN StatePlane Pennsylvania Feet, Foot US.. Ground Conditions: Imagery was collected in winter 2020 and 2021, while no snow was on the ground and rivers were at or below normal levels. In order to post process the imagery data to meet task order specifications and meet ASPRS horizontal accuracy guidelines, NV5 Geospatial utilized a total of 496 ground control points to assess the horizontal accuracy of the data.
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| Pennsylvania Emergency Management Agency |
| 2022 |
This orthoimagery data set includes 0.5 foot 8-bit 4-band (RGBN) digital orthoimage tiles in GeoTIFF, Mr. SID, and JPEG 2000 (JP2) format.
Dataset Description: The PEMA 0.5-Foot Orthoimagery Delivery (US Survey Feet) project called for the planning, acquisition, processing, and derivative products of imagery data to be collected at a ground sample distance (GSD) of 0.5 foot. Project specifications are based on the American Society of Photogrammetry and Remote Sensing (ASPRS) standards. The data were developed based on a horizontal projection/datum of NAD 1983 HARN StatePlane Pennsylvania North FIPS 3701 Feet, Foot US.
Ground Conditions: Imagery was collected in spring 2022, while no snow was on the ground and rivers were at or below normal levels. In order to post process the imagery data to meet task order specifications and meet ASPRS horizontal accuracy guidelines, NV5 Geospatial utilized a total of 119 ground control points to assess the horizontal accuracy of the data.
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| Pennsylvania Emergency Management Agency |
| 2010 |
PAMAP Program Cycle 1/DVRPC 2005 Digital Orthoimagery High Resolution Orthoimage (2003 - 2006) - cached mapservice
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| The Pennsylvania State University |
| 2012 |
2012 Lake Erie Drainage Area (Erie, PA) Digital Orthoimagery/LiDAR Project - In the fall of 2012, Woolpert obtained new aerial LiDAR covering the entire project area (512 square miles). The aerial LiDAR was acquired at a point density average of 1-meter with final products comprised of LAS (ground and above ground points). The aerial LiDAR was collected during leaf-off conditions during the fall 2012 flying season (November). The LiDAR is being delivered as a project area wide dataset, consisting of 2,500' x 2,500' tiles (which matches the ortho tiling system). Adjacent flight lines overlap by an average of 30 percent. LiDAR was collected with Leica ALS LiDAR Systems. The file naming convention is as follows: xxxyyy (Pennsylvania North Zone); Please note that xxx and yyy represent the easting and northing coordinates (respectively) in state plane feet. Each LiDAR file is approximately 40 megabytes in size. Ownership of the data products resides with Penn State and the Pennsylvania Department of Environmental Protection. The LiDAR data will be utilized for the rectification of aerial imagery to produce 1”=100’ scale ortho-imagery with a 6-inch pixel resolution. The LiDAR data will also be used as a component during the future delineation of project area wide impervious surfaces (using remote sensing techniques).
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| The Pennsylvania State University |
| 2012 |
2012 Lake Erie Drainage Area (Erie, PA) Digital Orthoimagery/LiDAR Project - In the fall of 2012, Woolpert obtained new aerial LiDAR covering the entire project area (512 square miles). The aerial LiDAR was acquired at a point density average of 1-meter with final products comprised of LAS (ground and above ground points). The aerial LiDAR was collected during leaf-off conditions during the fall 2012 flying season (November). The LiDAR is being delivered as a project area wide dataset, consisting of 2,500' x 2,500' tiles (which matches the ortho tiling system). Adjacent flight lines overlap by an average of 30 percent. LiDAR was collected with Leica ALS LiDAR Systems. The file naming convention is as follows: xxxyyy (Pennsylvania North Zone); Please note that xxx and yyy represent the easting and northing coordinates (respectively) in state plane feet. Each LiDAR file is approximately 40 megabytes in size. Ownership of the data products resides with Penn State and the Pennsylvania Department of Environmental Protection. The LiDAR data will be utilized for the rectification of aerial imagery to produce 1”=100’ scale ortho-imagery with a 6-inch pixel resolution. The LiDAR data will also be used as a component during the future delineation of project area wide impervious surfaces (using remote sensing techniques).
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| The Pennsylvania State University |
| 2012 |
2012 Lake Erie Drainage Area (Erie, PA) Digital Orthoimagery Project - In the fall of 2012, Woolpert obtained new aerial Orthoimagery covering the entire project area (512 square miles). The aerial Orthoimagery was collected during leaf-off conditions during the fall 2012 flying season (November) at 1"=100' scale with a 6-inch pixel resolution. The Orthoimagery is being delivered as a project area wide dataset, consisting of 2,500' x 2,500' tiles. The file naming convention is as follows: xxxyyy (Pennsylvania North Zone); Please note that xxx and yyy represent the easting and northing coordinates (respectively) in state plane feet. Ownership of the data products resides with Penn State and the Pennsylvania Department of Environmental Protection.
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| The Pennsylvania State University |
| 2012 |
2012 Lake Erie Drainage Area (Erie, PA) Digital Orthoimagery Project - In the fall of 2012, Woolpert obtained new aerial Orthoimagery covering the entire project area (512 square miles). The aerial Orthoimagery was collected during leaf-off conditions during the fall 2012 flying season (November) at 1"=100' scale with a 6-inch pixel resolution. The Orthoimagery is being delivered as a project area wide dataset, consisting of 2,500' x 2,500' tiles. The file naming convention is as follows: xxxyyy (Pennsylvania North Zone); Please note that xxx and yyy represent the easting and northing coordinates (respectively) in state plane feet. Ownership of the data products resides with Penn State and the Pennsylvania Department of Environmental Protection.
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| The Pennsylvania State University |
| 2017 |
Lake Erie Watershed 2015 Ortho/LiDAR/Hydro Project will consist the following: • New project – wide 1”=100’ scale color digital orthoimagery (with a 6-inch pixel resolution) • New project wide 0.7-meter LiDAR (average point density) • New project wide hydrology • Crest Delineation This task is for a high resolution data set of lidar covering approximately 512 square miles of the Lake Erie Shoreline, PA. The lidar data was acquired and processed under the requirements identified in this task order. Lidar data is a remotely sensed high resolution elevation data collected by an airborne platform. The lidar sensor uses a combination of laser range finding, GPS positioning, and inertial measurement technologies. The lidar systems collect data point clouds that are used to produce highly detailed Digital Elevation Models (DEMs) of the earth's terrain, man-made structures, and vegetation. The task required the LiDAR data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. The final products include classified LAS, 2.5' pixel raster DEMs of the bare-earth surface in ERDAS IMG Format. Each LAS file contains lidar point information, which has been calibrated, controlled, and classified. Additional deliverables include hydrologic breakline data, 8-bit intensity images, control data, tile index, lidar processing and survey reports in PDF format, FGDC metadata files for each data deliverable in .xml format. Ground conditions: Water at normal levels; no unusual inundation; no snow; leaf off. To better understand one of the state’s most vital natural resources and accurately plan for the future, the Pennsylvania Department of Environmental Protection (PADEP), through grant funding provided to the Pennsylvania Sea Grant (PASG) College Program, partnered with Woolpert to acquire imagery and lidar data for the entire Pennsylvania Lake Erie Watershed and all 77 miles of shoreline. - See more at: http://www.xyht.com/aerialuas/heights-april-2017-mapping-the-pennsylvania-lake-erie-watershed/#sthash.n3pVphR6.dpuf
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| The Pennsylvania State University |
| 2017 |
Lake Erie Watershed 2015 Ortho/LiDAR/Hydro Project will consist the following: • New project – wide 1”=100’ scale color digital orthoimagery (with a 6-inch pixel resolution) • New project wide 0.7-meter LiDAR (average point density) • New project wide hydrology • Crest Delineation This task is for a high resolution data set of lidar covering approximately 512 square miles of the Lake Erie Shoreline, PA. The lidar data was acquired and processed under the requirements identified in this task order. Lidar data is a remotely sensed high resolution elevation data collected by an airborne platform. The lidar sensor uses a combination of laser range finding, GPS positioning, and inertial measurement technologies. The lidar systems collect data point clouds that are used to produce highly detailed Digital Elevation Models (DEMs) of the earth's terrain, man-made structures, and vegetation. The task required the LiDAR data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. The final products include classified LAS, 2.5' pixel raster DEMs of the bare-earth surface in ERDAS IMG Format. Each LAS file contains lidar point information, which has been calibrated, controlled, and classified. Additional deliverables include hydrologic breakline data, 8-bit intensity images, control data, tile index, lidar processing and survey reports in PDF format, FGDC metadata files for each data deliverable in .xml format. Ground conditions: Water at normal levels; no unusual inundation; no snow; leaf off. To better understand one of the state’s most vital natural resources and accurately plan for the future, the Pennsylvania Department of Environmental Protection (PADEP), through grant funding provided to the Pennsylvania Sea Grant (PASG) College Program, partnered with Woolpert to acquire imagery and lidar data for the entire Pennsylvania Lake Erie Watershed and all 77 miles of shoreline. - See more at: http://www.xyht.com/aerialuas/heights-april-2017-mapping-the-pennsylvania-lake-erie-watershed/#sthash.n3pVphR6.dpuf
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| The Pennsylvania State University |
| 2012 |
TILE INDEX - 2012 Lake Erie Drainage Area (Erie, PA) Digital Orthoimagery Project - In the fall of 2012, Woolpert obtained new aerial Orthoimagery covering the entire project area (512 square miles). The aerial Orthoimagery was collected during leaf-off conditions during the fall 2012 flying season (November) at 1"=100' scale with a 6-inch pixel resolution. The Orthoimagery is being delivered as a project area wide dataset, consisting of 2,500' x 2,500' tiles. The file naming convention is as follows: xxxyyy (Pennsylvania North Zone); Please note that xxx and yyy represent the easting and northing coordinates (respectively) in state plane feet. Ownership of the data products resides with Penn State and the Pennsylvania Department of Environmental Protection.
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| The Pennsylvania State University |
| 2017 |
Lake Erie Watershed 2015 Ortho/LiDAR/Hydro Project will consist the following: • New project – wide 1”=100’ scale color digital orthoimagery (with a 6-inch pixel resolution) • New project wide 0.7-meter LiDAR (average point density) • New project wide hydrology • Crest Delineation This task is for a high resolution data set of lidar covering approximately 512 square miles of the Lake Erie Shoreline, PA. The lidar data was acquired and processed under the requirements identified in this task order. Lidar data is a remotely sensed high resolution elevation data collected by an airborne platform. The lidar sensor uses a combination of laser range finding, GPS positioning, and inertial measurement technologies. The lidar systems collect data point clouds that are used to produce highly detailed Digital Elevation Models (DEMs) of the earth's terrain, man-made structures, and vegetation. The task required the LiDAR data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. The final products include classified LAS, 2.5' pixel raster DEMs of the bare-earth surface in ERDAS IMG Format. Each LAS file contains lidar point information, which has been calibrated, controlled, and classified. Additional deliverables include hydrologic breakline data, 8-bit intensity images, control data, tile index, lidar processing and survey reports in PDF format, FGDC metadata files for each data deliverable in .xml format. Ground conditions: Water at normal levels; no unusual inundation; no snow; leaf off. To better understand one of the state’s most vital natural resources and accurately plan for the future, the Pennsylvania Department of Environmental Protection (PADEP), through grant funding provided to the Pennsylvania Sea Grant (PASG) College Program, partnered with Woolpert to acquire imagery and lidar data for the entire Pennsylvania Lake Erie Watershed and all 77 miles of shoreline. - See more at: http://www.xyht.com/aerialuas/heights-april-2017-mapping-the-pennsylvania-lake-erie-watershed/#sthash.n3pVphR6.dpuf
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| The Pennsylvania State University |
| 2017 |
Lake Erie Watershed 2015 Ortho/LiDAR/Hydro Project will consist the following: • New project – wide 1”=100’ scale color digital orthoimagery (with a 6-inch pixel resolution) • New project wide 0.7-meter LiDAR (average point density) • New project wide hydrology • Crest Delineation This task is for a high resolution data set of lidar covering approximately 512 square miles of the Lake Erie Shoreline, PA. The lidar data was acquired and processed under the requirements identified in this task order. Lidar data is a remotely sensed high resolution elevation data collected by an airborne platform. The lidar sensor uses a combination of laser range finding, GPS positioning, and inertial measurement technologies. The lidar systems collect data point clouds that are used to produce highly detailed Digital Elevation Models (DEMs) of the earth's terrain, man-made structures, and vegetation. The task required the LiDAR data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. The final products include classified LAS, 2.5' pixel raster DEMs of the bare-earth surface in ERDAS IMG Format. Each LAS file contains lidar point information, which has been calibrated, controlled, and classified. Additional deliverables include hydrologic breakline data, 8-bit intensity images, control data, tile index, lidar processing and survey reports in PDF format, FGDC metadata files for each data deliverable in .xml format. Ground conditions: Water at normal levels; no unusual inundation; no snow; leaf off. To better understand one of the state’s most vital natural resources and accurately plan for the future, the Pennsylvania Department of Environmental Protection (PADEP), through grant funding provided to the Pennsylvania Sea Grant (PASG) College Program, partnered with Woolpert to acquire imagery and lidar data for the entire Pennsylvania Lake Erie Watershed and all 77 miles of shoreline. - See more at: http://www.xyht.com/aerialuas/heights-april-2017-mapping-the-pennsylvania-lake-erie-watershed/#sthash.n3pVphR6.dpuf
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| The Pennsylvania State University |
| 2017 |
Lake Erie Watershed 2015 Ortho/LiDAR/Hydro Project will consist the following: • New project – wide 1”=100’ scale color digital orthoimagery (with a 6-inch pixel resolution) • New project wide 0.7-meter LiDAR (average point density) • New project wide hydrology • Crest Delineation This task is for a high resolution data set of lidar covering approximately 512 square miles of the Lake Erie Shoreline, PA. The lidar data was acquired and processed under the requirements identified in this task order. Lidar data is a remotely sensed high resolution elevation data collected by an airborne platform. The lidar sensor uses a combination of laser range finding, GPS positioning, and inertial measurement technologies. The lidar systems collect data point clouds that are used to produce highly detailed Digital Elevation Models (DEMs) of the earth's terrain, man-made structures, and vegetation. The task required the LiDAR data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. The final products include classified LAS, 2.5' pixel raster DEMs of the bare-earth surface in ERDAS IMG Format. Each LAS file contains lidar point information, which has been calibrated, controlled, and classified. Additional deliverables include hydrologic breakline data, 8-bit intensity images, control data, tile index, lidar processing and survey reports in PDF format, FGDC metadata files for each data deliverable in .xml format. Ground conditions: Water at normal levels; no unusual inundation; no snow; leaf off. To better understand one of the state’s most vital natural resources and accurately plan for the future, the Pennsylvania Department of Environmental Protection (PADEP), through grant funding provided to the Pennsylvania Sea Grant (PASG) College Program, partnered with Woolpert to acquire imagery and lidar data for the entire Pennsylvania Lake Erie Watershed and all 77 miles of shoreline. - See more at: http://www.xyht.com/aerialuas/heights-april-2017-mapping-the-pennsylvania-lake-erie-watershed/#sthash.n3pVphR6.dpuf
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| The Pennsylvania State University |
| 2017 |
Lake Erie Watershed 2015 Ortho/LiDAR/Hydro Project will consist the following: • New project – wide 1”=100’ scale color digital orthoimagery (with a 6-inch pixel resolution) • New project wide 0.7-meter LiDAR (average point density) • New project wide hydrology • Crest Delineation This task is for a high resolution data set of lidar covering approximately 512 square miles of the Lake Erie Shoreline, PA. The lidar data was acquired and processed under the requirements identified in this task order. Lidar data is a remotely sensed high resolution elevation data collected by an airborne platform. The lidar sensor uses a combination of laser range finding, GPS positioning, and inertial measurement technologies. The lidar systems collect data point clouds that are used to produce highly detailed Digital Elevation Models (DEMs) of the earth's terrain, man-made structures, and vegetation. The task required the LiDAR data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. The final products include classified LAS, 2.5' pixel raster DEMs of the bare-earth surface in ERDAS IMG Format. Each LAS file contains lidar point information, which has been calibrated, controlled, and classified. Additional deliverables include hydrologic breakline data, 8-bit intensity images, control data, tile index, lidar processing and survey reports in PDF format, FGDC metadata files for each data deliverable in .xml format. Ground conditions: Water at normal levels; no unusual inundation; no snow; leaf off. To better understand one of the state’s most vital natural resources and accurately plan for the future, the Pennsylvania Department of Environmental Protection (PADEP), through grant funding provided to the Pennsylvania Sea Grant (PASG) College Program, partnered with Woolpert to acquire imagery and lidar data for the entire Pennsylvania Lake Erie Watershed and all 77 miles of shoreline. - See more at: http://www.xyht.com/aerialuas/heights-april-2017-mapping-the-pennsylvania-lake-erie-watershed/#sthash.n3pVphR6.dpuf
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| The Pennsylvania State University |
| 2017 |
Lake Erie Watershed 2015 Ortho/LiDAR/Hydro Project will consist the following: • New project – wide 1”=100’ scale color digital orthoimagery (with a 6-inch pixel resolution) • New project wide 0.7-meter LiDAR (average point density) • New project wide hydrology • Crest Delineation This task is for a high resolution data set of lidar covering approximately 512 square miles of the Lake Erie Shoreline, PA. The lidar data was acquired and processed under the requirements identified in this task order. Lidar data is a remotely sensed high resolution elevation data collected by an airborne platform. The lidar sensor uses a combination of laser range finding, GPS positioning, and inertial measurement technologies. The lidar systems collect data point clouds that are used to produce highly detailed Digital Elevation Models (DEMs) of the earth's terrain, man-made structures, and vegetation. The task required the LiDAR data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. The final products include classified LAS, 2.5' pixel raster DEMs of the bare-earth surface in ERDAS IMG Format. Each LAS file contains lidar point information, which has been calibrated, controlled, and classified. Additional deliverables include hydrologic breakline data, 8-bit intensity images, control data, tile index, lidar processing and survey reports in PDF format, FGDC metadata files for each data deliverable in .xml format. Ground conditions: Water at normal levels; no unusual inundation; no snow; leaf off. To better understand one of the state’s most vital natural resources and accurately plan for the future, the Pennsylvania Department of Environmental Protection (PADEP), through grant funding provided to the Pennsylvania Sea Grant (PASG) College Program, partnered with Woolpert to acquire imagery and lidar data for the entire Pennsylvania Lake Erie Watershed and all 77 miles of shoreline. - See more at: http://www.xyht.com/aerialuas/heights-april-2017-mapping-the-pennsylvania-lake-erie-watershed/#sthash.n3pVphR6.dpuf
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| The Pennsylvania State University |
| 2012 |
TILE INDEX - 2012 Lake Erie Drainage Area (Erie, PA) Digital Orthoimagery Project - In the fall of 2012, Woolpert obtained new aerial Orthoimagery covering the entire project area (512 square miles). The aerial Orthoimagery was collected during leaf-off conditions during the fall 2012 flying season (November) at 1"=100' scale with a 6-inch pixel resolution. The Orthoimagery is being delivered as a project area wide dataset, consisting of 2,500' x 2,500' tiles. The file naming convention is as follows: xxxyyy (Pennsylvania North Zone); Please note that xxx and yyy represent the easting and northing coordinates (respectively) in state plane feet. Ownership of the data products resides with Penn State and the Pennsylvania Department of Environmental Protection.
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| The Pennsylvania State University |
| 2020 |
Lidar, Hyperspectral Imagery, Orthoimagery for The Pennsylvania State University Stone Valley Experimental Forest.
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| The Pennsylvania State University |
| 2009 |
One foot GSD, natural color (RGB), 8-bit digital orthophotography for the City of Erie, Pennsylvania. The imagery was collected using the Leica Geosystems ADS40 sensor between April 27th and June 6th, 2009 at an average altitude of 9,600 feet above ground level. The National Elevation Dataset (NED) was used as vertical control. Airborne GPS/IMU data was used as horizontal control. The orthophotography is georeferenced to UTM Zone 17 North, meter units, NAD83, NAVD88. The imagery was produced by Pixxures, Inc. under contract for DigitalGlobe, Inc." Data received at EROS were reprojected from 1-foot Pennsylvania 3-band, State Plane to 3-band, 0.30 meter UTM Zone 17 and resampled to align to the USNG using the USGS Seamless system. The naming convention is based on the U.S. National Grid (USNG), taking the coordinates of the SW corner of the orthoimage. The metadata were imported and updated for display through The National Map Seamless Server at Chip-level metadata are provided in XML format.
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| U S Geological Survey |
| 2009 |
TILE INDEX - One foot GSD, natural color (RGB), 8-bit digital orthophotography for the City of Erie, Pennsylvania. The imagery was collected using the Leica Geosystems ADS40 sensor between April 27th and June 6th, 2009 at an average altitude of 9,600 feet above ground level. The National Elevation Dataset (NED) was used as vertical control. Airborne GPS/IMU data was used as horizontal control. The orthophotography is georeferenced to UTM Zone 17 North, meter units, NAD83, NAVD88. The imagery was produced by Pixxures, Inc. under contract for DigitalGlobe, Inc." Data received at EROS were reprojected from 1-foot Pennsylvania 3-band, State Plane to 3-band, 0.30 meter UTM Zone 17 and resampled to align to the USNG using the USGS Seamless system. The naming convention is based on the U.S. National Grid (USNG), taking the coordinates of the SW corner of the orthoimage. The metadata were imported and updated for display through The National Map Seamless Server at Chip-level metadata are provided in XML format.
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| U S Geological Survey |
| 2009 |
One foot GSD, natural color (RGB), 8-bit digital orthophotography for the City of PIttsburgh, Pennsylvania. The imagery was collected using the Leica Geosystems ADS40 sensor between April 26th and July 8th, 2009 at an average altitude of 9,600 feet above ground level. The National Elevation Dataset (NED) was used as vertical control. Airborne GPS/IMU data was used as horizontal control. The orthophotography is georeferenced to UTM Zone 17 North, meter units, NAD83, NAVD88. The imagery was produced by Pixxures, Inc. under contract for DigitalGlobe, Inc." Data received at EROS were reprojected from 1-foot Pennsylvania 3-band, State Plane to 3-band, 0.30 meter UTM Zone 17 and resampled to align to the USNG using the USGS Seamless system. The naming convention is based on the U.S. National Grid (USNG), taking the coordinates of the SW corner of the orthoimage. The metadata were imported and updated for display through The National Map Seamless Server at Chip-level metadata are provided in XML format.
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| U S Geological Survey |
| 2012 |
"This task order consists of digital orthophoto production covering the Pittsburgh Area, Pennsylvania." An orthoimage is remotely sensed image data in which displacement of features in the image caused by terrain relief and sensor orientation have been mathematically removed. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map. There is no image overlap between adjacent files.
Data received at Earth Resources Observation and Science Center (EROS) were verified as:
Projection: NAD_1983_UTM_Zone_17N
Resolution: 0.3000 m
Type: Natural Color
and resampled to align to the U.S. National Grid (USNG) using The National Map. The naming convention is based on the U.S. National Grid (USNG), taking the coordinates of the SW corner of the orthoimage. The metadata were imported and updated for display through The National Map at http://nationalmap.gov/viewer.html Chip-level metadata are provided in HTML and XML format. Data were compressed utilizing IAS software. The compression was JPEG2000 Lossy Compressed. The file format created was .jp2.
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| U S Geological Survey |
| 2009 |
TILE INDEX - One foot GSD, natural color (RGB), 8-bit digital orthophotography for the City of PIttsburgh, Pennsylvania. The imagery was collected using the Leica Geosystems ADS40 sensor between April 26th and July 8th, 2009 at an average altitude of 9,600 feet above ground level. The National Elevation Dataset (NED) was used as vertical control. Airborne GPS/IMU data was used as horizontal control. The orthophotography is georeferenced to UTM Zone 17 North, meter units, NAD83, NAVD88. The imagery was produced by Pixxures, Inc. under contract for DigitalGlobe, Inc." Data received at EROS were reprojected from 1-foot Pennsylvania 3-band, State Plane to 3-band, 0.30 meter UTM Zone 17 and resampled to align to the USNG using the USGS Seamless system. The naming convention is based on the U.S. National Grid (USNG), taking the coordinates of the SW corner of the orthoimage. The metadata were imported and updated for display through The National Map Seamless Server at Chip-level metadata are provided in XML format.
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| U S Geological Survey |
| 2012 |
TILE INDEX -"This task order consists of digital orthophoto production covering the Pittsburgh Area, Pennsylvania." An orthoimage is remotely sensed image data in which displacement of features in the image caused by terrain relief and sensor orientation have been mathematically removed. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map. There is no image overlap between adjacent files.
Data received at Earth Resources Observation and Science Center (EROS) were verified as:
Projection: NAD_1983_UTM_Zone_17N
Resolution: 0.3000 m
Type: Natural Color
and resampled to align to the U.S. National Grid (USNG) using The National Map. The naming convention is based on the U.S. National Grid (USNG), taking the coordinates of the SW corner of the orthoimage. The metadata were imported and updated for display through The National Map at http://nationalmap.gov/viewer.html Chip-level metadata are provided in HTML and XML format. Data were compressed utilizing IAS software. The compression was JPEG2000 Lossy Compressed. The file format created was .jp2.
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| U S Geological Survey |
| 2005 |
This data set consists of 0.3-meter pixel resolution (approximately 1-foot), natural color orthoimages covering Mercer County, Pennsylvania. An orthoimage is remotely sensed image data in which displacement of features in the image caused by terrain relief and sensor orientation have been mathematically removed. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map. The design accuracy is estimated not to exceed 3-meter diagonal RMSE (2.12m RMSE in X or Y).
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| U S Geological Survey |
| 2005 |
This data set consists of 0.3-meter pixel resolution (approximately 1-foot), natural color orthoimages covering Mercer County, Pennsylvania. An orthoimage is remotely sensed image data in which displacement of features in the image caused by terrain relief and sensor orientation have been mathematically removed. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map. The design accuracy is estimated not to exceed 3-meter diagonal RMSE (2.12m RMSE in X or Y).
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| U S Geological Survey |
| 2005 |
This data set consists of 0.3-meter pixel resolution (approximately 1-foot), natural color orthoimages covering the Pittsburgh, PA Urban Area (Allegheny and Beaver Counties. An orthoimage is remotely sensed image data in which displacement of features in the image caused by terrain relief and sensor orientation have been mathematically removed. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map. The design accuracy is estimated not to exceed 3-meter diagonal RMSE (2.12m RMSE in X or Y).
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| U S Geological Survey |
| 2005 |
Tile Index - This data set consists of 0.3-meter pixel resolution (approximately 1-foot), natural color orthoimages covering the Pittsburgh, PA Urban Area (Allegheny and Beaver Counties. An orthoimage is remotely sensed image data in which displacement of features in the image caused by terrain relief and sensor orientation have been mathematically removed. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map. The design accuracy is estimated not to exceed 3-meter diagonal RMSE (2.12m RMSE in X or Y).
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| U S Geological Survey |
| 2011 |
"This task order consists of digital orthophoto production covering the Pittsburgh Area, Pennsylvania." An orthoimage is remotely sensed image data in which displacement of features in the image caused by terrain relief and sensor orientation have been mathematically removed. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map. There is no image overlap between adjacent files.
Data received at Earth Resources Observation and Science Center (EROS) were verified as:
Projection: NAD_1983_UTM_Zone_17N
Resolution: 0.3000 m
Type: Natural Color
and resampled to align to the U.S. National Grid (USNG) using The National Map. The naming convention is based on the U.S. National Grid (USNG), taking the coordinates of the SW corner of the orthoimage. The metadata were imported and updated for display through The National Map at http://nationalmap.gov/viewer.html Chip-level metadata are provided in HTML and XML format. Data were compressed utilizing IAS software. The compression was JPEG2000 Lossy Compressed. The file format created was .jp2.
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| U S Geological Survey |
| 2011 |
TILE INDEX -"This task order consists of digital orthophoto production covering the Pittsburgh Area, Pennsylvania." An orthoimage is remotely sensed image data in which displacement of features in the image caused by terrain relief and sensor orientation have been mathematically removed. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map. There is no image overlap between adjacent files.
Data received at Earth Resources Observation and Science Center (EROS) were verified as:
Projection: NAD_1983_UTM_Zone_17N
Resolution: 0.3000 m
Type: Natural Color
and resampled to align to the U.S. National Grid (USNG) using The National Map. The naming convention is based on the U.S. National Grid (USNG), taking the coordinates of the SW corner of the orthoimage. The metadata were imported and updated for display through The National Map at http://nationalmap.gov/viewer.html Chip-level metadata are provided in HTML and XML format. Data were compressed utilizing IAS software. The compression was JPEG2000 Lossy Compressed. The file format created was .jp2.
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| U S Geological Survey |
| 2012 |
"This task order consists of digital orthophoto production covering the Pittsburgh Area, Pennsylvania." An orthoimage is remotely sensed image data in which displacement of features in the image caused by terrain relief and sensor orientation have been mathematically removed. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map. There is no image overlap between adjacent files.
Data received at Earth Resources Observation and Science Center (EROS) were verified as:
Projection: NAD_1983_UTM_Zone_17N
Resolution: 0.3000 m
Type: Natural Color
and resampled to align to the U.S. National Grid (USNG) using The National Map. The naming convention is based on the U.S. National Grid (USNG), taking the coordinates of the SW corner of the orthoimage. The metadata were imported and updated for display through The National Map at http://nationalmap.gov/viewer.html Chip-level metadata are provided in HTML and XML format. Data were compressed utilizing IAS software. The compression was JPEG2000 Lossy Compressed. The file format created was .jp2.
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| U S Geological Survey |
| 2012 |
TILE INDEX -"This task order consists of digital orthophoto production covering the Pittsburgh Area, Pennsylvania." An orthoimage is remotely sensed image data in which displacement of features in the image caused by terrain relief and sensor orientation have been mathematically removed. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map. There is no image overlap between adjacent files.
Data received at Earth Resources Observation and Science Center (EROS) were verified as:
Projection: NAD_1983_UTM_Zone_17N
Resolution: 0.3000 m
Type: Natural Color
and resampled to align to the U.S. National Grid (USNG) using The National Map. The naming convention is based on the U.S. National Grid (USNG), taking the coordinates of the SW corner of the orthoimage. The metadata were imported and updated for display through The National Map at http://nationalmap.gov/viewer.html Chip-level metadata are provided in HTML and XML format. Data were compressed utilizing IAS software. The compression was JPEG2000 Lossy Compressed. The file format created was .jp2.
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| U S Geological Survey |
| 2009 |
One foot GSD, natural color (RGB), 8-bit digital orthophotography for the City of New Castle, Pennsylvania. The imagery was collected using the Leica Geosystems ADS40 sensor between October 19th and November 2nd, 2009 at an average altitude of 9,600 feet above ground level. The National Elevation Dataset (NED) was used as vertical control. Airborne GPS/IMU data was used as horizontal control. The orthophotography is georeferenced to UTM Zone 17 North, meter units, NAD83, NAVD88. The imagery was produced by Pixxures, Inc. under contract for DigitalGlobe, Inc." An orthoimage is remotely sensed image data in which displacement of features in the image caused by terrain relief and sensor orientation have been mathematically removed. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map. There is no image overlap between adjacent files. Data received at EROS as: Projection: NAD_1983_UTM_Zone_17N Resolution: 0.3 meter Type: Natural Color and chipped to the Standard Product as: Standard Product Projection: NAD_1983_UTM_Zone_17N Standard Product Resolution: 0.3000 m Rows: 5,000 Columns: 5,000.
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| U S Geological Survey |
| 2009 |
TILE INDEX - One foot GSD, natural color (RGB), 8-bit digital orthophotography for the City of New Castle, Pennsylvania. The imagery was collected using the Leica Geosystems ADS40 sensor between October 19th and November 2nd, 2009 at an average altitude of 9,600 feet above ground level. The National Elevation Dataset (NED) was used as vertical control. Airborne GPS/IMU data was used as horizontal control. The orthophotography is georeferenced to UTM Zone 17 North, meter units, NAD83, NAVD88. The imagery was produced by Pixxures, Inc. under contract for DigitalGlobe, Inc." An orthoimage is remotely sensed image data in which displacement of features in the image caused by terrain relief and sensor orientation have been mathematically removed. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map. There is no image overlap between adjacent files. Data received at EROS as: Projection: NAD_1983_UTM_Zone_17N Resolution: 0.3 meter Type: Natural Color and chipped to the Standard Product as: Standard Product Projection: NAD_1983_UTM_Zone_17N Standard Product Resolution: 0.3000 m Rows: 5,000 Columns: 5,000.
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| U S Geological Survey |
| 2016 |
High-resolution land cover dataset for the Commonwealth of Pennsylvania. Twelve land cover classes were mapped:0 - Background1 - Water2 - Emergent Wetlands3 - Tree Canopy4 - Scrub/Shrub5 - Low Vegetation6 - Barren7 - Structures8 - Other Impervious Surfaces9 - Roads10 - Tree Canopy over Structures11 - Tree Canopy over Other Impervious Surfaces12 - Tree Canopy over RoadsThe complete class definitions and standards can be viewed at the link below.http://goo.gl/THacggThe primary sources used to derive this land-cover layer were 2006-2008 leaf-off LiDAR data, 2005-2008 leaf-off orthoimagery, and 2013 leaf-on orthoimagery. Ancillary data sources such as LiDAR-derived breaklines for roads and hydrology were used to augment the land-cover mapping. This land-cover dataset is considered current based on data of acquisition for the leaf-on orthoimagery. Land-cover class assignment was accomplished using a rule-based expert system embedded within an object-based framework. Object-based image analysis techniques (OBIA) work by grouping pixels into meaningful objects based on their spectral and spatial properties, while taking into account boundaries imposed by existing vector datasets. Within the OBIA environment a rule-based expert system was designed to effectively mimic the process of manual image analysis by incorporating the elements of image interpretation (color/tone, texture, pattern, location, size, and shape) into the classification process. A series of morphological procedures were employed to insure that the end product is both accurate and cartographically pleasing. Following the automated OBIA mapping a detailed manual review of the dataset was carried out at a scale of 1:3000 and all observable errors were corrected.This dataset was developed to support land-cover mapping and modeling initiatives in the Chesapeake Bay Watershed and Delaware River Basin. At the time of its publication, it represented the most accurate and detailed land cover map for the Pennsylvania portion of the Chesapeake Bay Watershed
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| University of Vermont Spatial Analysis Laboratory |
| 2016 |
High-resolution land cover dataset for the Chesapeke Bay Watershed. Twelve land cover classes were mapped:0 - Background1 - Water2 - Emergent Wetlands3 - Tree Canopy4 - Scrub/Shrub5 - Low Vegetation6 - Barren7 - Structures8 - Other Impervious Surfaces9 - Roads10 - Tree Canopy over Structures11 - Tree Canopy over Other Impervious Surfaces12 - Tree Canopy over Roads. The complete class definitions and standards can be viewed at the link below.http://goo.gl/THacgg. The primary sources used to derive this land-cover layer were 2006-2008 leaf-off LiDAR data, 2005-2008 leaf-off orthoimagery, and 2013 leaf-on orthoimagery. Ancillary data sources such as LiDAR-derived breaklines for roads and hydrology were used to augment the land-cover mapping. This land-cover dataset is considered current based on data of acquisition for the leaf-on orthoimagery. Land-cover class assignment was accomplished using a rule-based expert system embedded within an object-based framework. Object-based image analysis techniques (OBIA) work by grouping pixels into meaningful objects based on their spectral and spatial properties, while taking into account boundaries imposed by existing vector datasets. Within the OBIA environment a rule-based expert system was designed to effectively mimic the process of manual image analysis by incorporating the elements of image interpretation (color/tone, texture, pattern, location, size, and shape) into the classification process. A series of morphological procedures were employed to insure that the end product is both accurate and cartographically pleasing. Following the automated OBIA mapping a detailed manual review of the dataset was carried out at a scale of 1:3000 and all observable errors were corrected.
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| University of Vermont Spatial Analysis Laboratory |
| 2016 |
High-resolution land cover dataset for the Chesapeke Bay Watershed. Twelve land cover classes were mapped:0 - Background1 - Water2 - Emergent Wetlands3 - Tree Canopy4 - Scrub/Shrub5 - Low Vegetation6 - Barren7 - Structures8 - Other Impervious Surfaces9 - Roads10 - Tree Canopy over Structures11 - Tree Canopy over Other Impervious Surfaces12 - Tree Canopy over Roads. The complete class definitions and standards can be viewed at the link below.http://goo.gl/THacgg. The primary sources used to derive this land-cover layer were 2006-2008 leaf-off LiDAR data, 2005-2008 leaf-off orthoimagery, and 2013 leaf-on orthoimagery. Ancillary data sources such as LiDAR-derived breaklines for roads and hydrology were used to augment the land-cover mapping. This land-cover dataset is considered current based on data of acquisition for the leaf-on orthoimagery. Land-cover class assignment was accomplished using a rule-based expert system embedded within an object-based framework. Object-based image analysis techniques (OBIA) work by grouping pixels into meaningful objects based on their spectral and spatial properties, while taking into account boundaries imposed by existing vector datasets. Within the OBIA environment a rule-based expert system was designed to effectively mimic the process of manual image analysis by incorporating the elements of image interpretation (color/tone, texture, pattern, location, size, and shape) into the classification process. A series of morphological procedures were employed to insure that the end product is both accurate and cartographically pleasing. Following the automated OBIA mapping a detailed manual review of the dataset was carried out at a scale of 1:3000 and all observable errors were corrected.
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| University of Vermont Spatial Analysis Laboratory |
| 2016 |
High-resolution land cover dataset for the Chesapeke Bay Watershed. Twelve land cover classes were mapped:0 - Background1 - Water2 - Emergent Wetlands3 - Tree Canopy4 - Scrub/Shrub5 - Low Vegetation6 - Barren7 - Structures8 - Other Impervious Surfaces9 - Roads10 - Tree Canopy over Structures11 - Tree Canopy over Other Impervious Surfaces12 - Tree Canopy over Roads. The complete class definitions and standards can be viewed at the link below.http://goo.gl/THacgg. The primary sources used to derive this land-cover layer were 2006-2008 leaf-off LiDAR data, 2005-2008 leaf-off orthoimagery, and 2013 leaf-on orthoimagery. Ancillary data sources such as LiDAR-derived breaklines for roads and hydrology were used to augment the land-cover mapping. This land-cover dataset is considered current based on data of acquisition for the leaf-on orthoimagery. Land-cover class assignment was accomplished using a rule-based expert system embedded within an object-based framework. Object-based image analysis techniques (OBIA) work by grouping pixels into meaningful objects based on their spectral and spatial properties, while taking into account boundaries imposed by existing vector datasets. Within the OBIA environment a rule-based expert system was designed to effectively mimic the process of manual image analysis by incorporating the elements of image interpretation (color/tone, texture, pattern, location, size, and shape) into the classification process. A series of morphological procedures were employed to insure that the end product is both accurate and cartographically pleasing. Following the automated OBIA mapping a detailed manual review of the dataset was carried out at a scale of 1:3000 and all observable errors were corrected.
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| University of Vermont Spatial Analysis Laboratory |
| 2016 |
High-resolution land cover dataset for the Chesapeke Bay Watershed. Twelve land cover classes were mapped:0 - Background1 - Water2 - Emergent Wetlands3 - Tree Canopy4 - Scrub/Shrub5 - Low Vegetation6 - Barren7 - Structures8 - Other Impervious Surfaces9 - Roads10 - Tree Canopy over Structures11 - Tree Canopy over Other Impervious Surfaces12 - Tree Canopy over Roads. The complete class definitions and standards can be viewed at the link below.http://goo.gl/THacgg. The primary sources used to derive this land-cover layer were 2006-2008 leaf-off LiDAR data, 2005-2008 leaf-off orthoimagery, and 2013 leaf-on orthoimagery. Ancillary data sources such as LiDAR-derived breaklines for roads and hydrology were used to augment the land-cover mapping. This land-cover dataset is considered current based on data of acquisition for the leaf-on orthoimagery. Land-cover class assignment was accomplished using a rule-based expert system embedded within an object-based framework. Object-based image analysis techniques (OBIA) work by grouping pixels into meaningful objects based on their spectral and spatial properties, while taking into account boundaries imposed by existing vector datasets. Within the OBIA environment a rule-based expert system was designed to effectively mimic the process of manual image analysis by incorporating the elements of image interpretation (color/tone, texture, pattern, location, size, and shape) into the classification process. A series of morphological procedures were employed to insure that the end product is both accurate and cartographically pleasing. Following the automated OBIA mapping a detailed manual review of the dataset was carried out at a scale of 1:3000 and all observable errors were corrected.
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| University of Vermont Spatial Analysis Laboratory |
| 2016 |
High-resolution land cover dataset for the Chesapeke Bay Watershed. Twelve land cover classes were mapped:0 - Background1 - Water2 - Emergent Wetlands3 - Tree Canopy4 - Scrub/Shrub5 - Low Vegetation6 - Barren7 - Structures8 - Other Impervious Surfaces9 - Roads10 - Tree Canopy over Structures11 - Tree Canopy over Other Impervious Surfaces12 - Tree Canopy over Roads. The complete class definitions and standards can be viewed at the link below.http://goo.gl/THacgg. The primary sources used to derive this land-cover layer were 2006-2008 leaf-off LiDAR data, 2005-2008 leaf-off orthoimagery, and 2013 leaf-on orthoimagery. Ancillary data sources such as LiDAR-derived breaklines for roads and hydrology were used to augment the land-cover mapping. This land-cover dataset is considered current based on data of acquisition for the leaf-on orthoimagery. Land-cover class assignment was accomplished using a rule-based expert system embedded within an object-based framework. Object-based image analysis techniques (OBIA) work by grouping pixels into meaningful objects based on their spectral and spatial properties, while taking into account boundaries imposed by existing vector datasets. Within the OBIA environment a rule-based expert system was designed to effectively mimic the process of manual image analysis by incorporating the elements of image interpretation (color/tone, texture, pattern, location, size, and shape) into the classification process. A series of morphological procedures were employed to insure that the end product is both accurate and cartographically pleasing. Following the automated OBIA mapping a detailed manual review of the dataset was carried out at a scale of 1:3000 and all observable errors were corrected.
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| University of Vermont Spatial Analysis Laboratory |
| 2016 |
High-resolution land cover dataset for the Delaware River Basin. Twelve land cover classes were mapped:0 - Background1 - Water2 - Emergent Wetlands3 - Tree Canopy4 - Scrub/Shrub5 - Low Vegetation6 - Barren7 - Structures8 - Other Impervious Surfaces9 - Roads10 - Tree Canopy over Structures11 - Tree Canopy over Other Impervious Surfaces12 - Tree Canopy over Roads. The complete class definitions and standards can be viewed at the link below.http://goo.gl/THacgg. The primary sources used to derive this land-cover layer were 2006-2008 leaf-off LiDAR data, 2005-2008 leaf-off orthoimagery, and 2013 leaf-on orthoimagery. Ancillary data sources such as LiDAR-derived breaklines for roads and hydrology were used to augment the land-cover mapping. This land-cover dataset is considered current based on data of acquisition for the leaf-on orthoimagery. Land-cover class assignment was accomplished using a rule-based expert system embedded within an object-based framework. Object-based image analysis techniques (OBIA) work by grouping pixels into meaningful objects based on their spectral and spatial properties, while taking into account boundaries imposed by existing vector datasets. Within the OBIA environment a rule-based expert system was designed to effectively mimic the process of manual image analysis by incorporating the elements of image interpretation (color/tone, texture, pattern, location, size, and shape) into the classification process. A series of morphological procedures were employed to insure that the end product is both accurate and cartographically pleasing. Following the automated OBIA mapping a detailed manual review of the dataset was carried out at a scale of 1:3000 and all observable errors were corrected.
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| University of Vermont Spatial Analysis Laboratory |
| 2016 |
High-resolution land cover dataset for the Commonwealth of Pennsylvania. Twelve land cover classes were mapped:0 - Background1 - Water2 - Emergent Wetlands3 - Tree Canopy4 - Scrub/Shrub5 - Low Vegetation6 - Barren7 - Structures8 - Other Impervious Surfaces9 - Roads10 - Tree Canopy over Structures11 - Tree Canopy over Other Impervious Surfaces12 - Tree Canopy over RoadsThe complete class definitions and standards can be viewed at the link below.http://goo.gl/THacggThe primary sources used to derive this land-cover layer were 2006-2008 leaf-off LiDAR data, 2005-2008 leaf-off orthoimagery, and 2013 leaf-on orthoimagery. Ancillary data sources such as LiDAR-derived breaklines for roads and hydrology were used to augment the land-cover mapping. This land-cover dataset is considered current based on data of acquisition for the leaf-on orthoimagery. Land-cover class assignment was accomplished using a rule-based expert system embedded within an object-based framework. Object-based image analysis techniques (OBIA) work by grouping pixels into meaningful objects based on their spectral and spatial properties, while taking into account boundaries imposed by existing vector datasets. Within the OBIA environment a rule-based expert system was designed to effectively mimic the process of manual image analysis by incorporating the elements of image interpretation (color/tone, texture, pattern, location, size, and shape) into the classification process. A series of morphological procedures were employed to insure that the end product is both accurate and cartographically pleasing. Following the automated OBIA mapping a detailed manual review of the dataset was carried out at a scale of 1:3000 and all observable errors were corrected.This dataset was developed to support land-cover mapping and modeling initiatives in the Chesapeake Bay Watershed and Delaware River Basin. At the time of its publication, it represented the most accurate and detailed land cover map for the Pennsylvania portion of the Chesapeake Bay Watershed
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| University of Vermont Spatial Analysis Laboratory |
| 2018 |
High-resolution land cover dataset for the Commonwealth of Pennsylvania. Twelve land cover classes were mapped:0 - Background1 - Water2 - Emergent Wetlands3 - Tree Canopy4 - Scrub/Shrub5 - Low Vegetation6 - Barren7 - Structures8 - Other Impervious Surfaces9 - Roads10 - Tree Canopy over Structures11 - Tree Canopy over Other Impervious Surfaces12 - Tree Canopy over RoadsThe complete class definitions and standards can be viewed at the link below.http://goo.gl/THacggThe primary sources used to derive this land-cover layer were 2006-2008 leaf-off LiDAR data, 2005-2008 leaf-off orthoimagery, and 2013 leaf-on orthoimagery. Ancillary data sources such as LiDAR-derived breaklines for roads and hydrology were used to augment the land-cover mapping. This land-cover dataset is considered current based on data of acquisition for the leaf-on orthoimagery. Land-cover class assignment was accomplished using a rule-based expert system embedded within an object-based framework. Object-based image analysis techniques (OBIA) work by grouping pixels into meaningful objects based on their spectral and spatial properties, while taking into account boundaries imposed by existing vector datasets. Within the OBIA environment a rule-based expert system was designed to effectively mimic the process of manual image analysis by incorporating the elements of image interpretation (color/tone, texture, pattern, location, size, and shape) into the classification process. A series of morphological procedures were employed to insure that the end product is both accurate and cartographically pleasing. Following the automated OBIA mapping a detailed manual review of the dataset was carried out at a scale of 1:3000 and all observable errors were corrected.This dataset was developed to support land-cover mapping and modeling initiatives in Commonwealth of Pennsylvannia. At the time of its publication, it represented the most accurate and detailed land cover map for the state.
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| University of Vermont Spatial Analysis Laboratory |
| 2017 |
High-resolution land cover dataset for the State of New Jersey, Delaware River Basin. Twelve land cover classes were mapped:0 - Background1 - Water2 - Emergent Wetlands3 - Tree Canopy4 - Scrub/Shrub5 - Low Vegetation6 - Barren7 - Structures8 - Other Impervious Surfaces9 - Roads10 - Tree Canopy over Structures11 - Tree Canopy over Other Impervious Surfaces12 - Tree Canopy over RoadsThe complete class definitions and standards can be viewed at the link below.http://goo.gl/THacggThe primary sources used to derive this land-cover layer were 2013 leaf-on orthoimagery, 2015 leaf-off orthoimagery, and leaf-off LiDAR acquired across a series of dates during the period 2006-2015. Ancillary data sources such as road centerlines and hydrology were used to augment the land-cover mapping. This land-cover dataset is considered current based on data of acquisition for the leaf-on orthoimagery. Land-cover class assignment was accomplished using a rule-based expert system embedded within an object-based framework. Object-based image analysis techniques (OBIA) work by grouping pixels into meaningful objects based on their spectral and spatial properties, while taking into account boundaries imposed by existing vector datasets. Within the OBIA environment a rule-based expert system was designed to effectively mimic the process of manual image analysis by incorporating the elements of image interpretation (color/tone, texture, pattern, location, size, and shape) into the classification process. A series of morphological procedures were employed to insure that the end product is both accurate and cartographically pleasing. Following the automated OBIA mapping a detailed manual review of the dataset was carried out at a scale of 1:3000 and all observable errors were corrected.This dataset was developed to support land-cover mapping and modeling initiatives in the Delaware River Basin. At the time of its publication, it represented the most accurate and detailed land cover map for the New Jersey portion of the Delaware River Basin.
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| University of Vermont Spatial Analysis Laboratory |
| 2013 |
This dataset was developed to support land-cover mapping and modeling initiatives in the Commonwealth of Pennsylvania.
High-resolution wetlands dataset for Pennsylvlania. Primary wetlands classes were mapped, plus water:EmergentScrub\ShrubForestedWaterThe primary sources used to derive this modeled wetlands layer were 2006-2008 leaf-off LiDAR data, 2005-2008 leaf-off orthoimagery, 2013 high-resolution land-cover data, and moderate-resolution predictive wetlands maps incorporating topography, hydrological flow potential, and climate data. This dataset is considered current based on the 2013 land-cover map.Wetlands classes were mapped using a rule-based expert system embedded within an object-based framework. Object-based image analysis techniques (OBIA) work by grouping pixels into meaningful objects based on their spectral and spatial properties. Using this technique, a rule-based expert system was designed to effectively mimic the process of manual image analysis by incorporating the elements of image interpretation (color/tone, texture, pattern, location, size, and shape) into the classification process. A series of morphological procedures were used to ensure that the end product was both accurate and cartographically coherent.This dataset was developed to support land-cover mapping and modeling initiatives in Pennsylvania.
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| University of Vermont Spatial Analysis Laboratory |
| 2013 |
This dataset was developed to support land-cover mapping and modeling initiatives in the Commonwealth of Pennsylvania.
High-resolution dataset depicting restorable wetlands in Pennsylvania. It includes agricultural fields that have topographic, hydrological flow, and climate characteristics indicative of wetlands. Theoretically, these features could be restored as wetlands if different land uses were practiced at each site.The primary sources used to derive this restorable wetlands layer were 2006-2008 leaf-off LiDAR data, 2005-2008 leaf-off orthoimagery, 2013 high-resolution land-cover data, and moderate-resolution predictive wetlands maps incorporating topography, hydrological flow potential, and climate data. This dataset is considered current based on the 2013 land-cover map.Restorable wetlands were mapped using a rule-based expert system embedded within an object-based framework. Object-based image analysis techniques (OBIA) work by grouping pixels into meaningful objects based on their spectral and spatial properties, while taking into account land-cover boundaries imposed by the 2013 land-cover map. Using this technique, a rule-based expert system was designed to effectively mimic the process of manual image analysis by incorporating the elements of image interpretation (color/tone, texture, pattern, location, size, and shape) into the classification process. A series of morphological procedures were employed to ensure that the end product was both accurate and cartographically coherent.This dataset was developed to support land-cover mapping and modeling initiatives in Pennsylvania.This vector version was derived from the original 1-meter raster layer.
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| University of Vermont Spatial Analysis Laboratory |
| 2016 |
Multi-spectral digital orthophotography was produced at a scale of 1:2400 (1 in = 200 ft) with a 12 inch pixel resolution for the YCPC project area. Digital orthophotography combines the image characteristics of a photograph with the geometric qualities of a map. Orthophoto data is produced through the use of digitized perspective aerial photographs or other remotely sensed image data. This data is processed into a digital product that has been rectified for camera lens distortion, vertical displacement caused by terrain relief, and variations in aircraft altitude and orientation.
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| York County Planning Commission |
| 2016 |
Multi-spectral digital orthophotography was produced at a scale of 1:2400 (1 in = 200 ft) with a 12 inch pixel resolution for the YCPC project area. Digital orthophotography combines the image characteristics of a photograph with the geometric qualities of a map. Orthophoto data is produced through the use of digitized perspective aerial photographs or other remotely sensed image data. This data is processed into a digital product that has been rectified for camera lens distortion, vertical displacement caused by terrain relief, and variations in aircraft altitude and orientation.
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| York County Planning Commission |
| 2016 |
Multi-spectral digital orthophotography was produced at a scale of 1:2400 (1 in = 200 ft) with a 12 inch pixel resolution for the YCPC project area. Digital orthophotography combines the image characteristics of a photograph with the geometric qualities of a map. Orthophoto data is produced through the use of digitized perspective aerial photographs or other remotely sensed image data. This data is processed into a digital product that has been rectified for camera lens distortion, vertical displacement caused by terrain relief, and variations in aircraft altitude and orientation.
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| York County Planning Commission |