Allegheny County Imagery data from 2017, hosted by PASDA.

Allegheny County Imagery data from 2017, hosted by PASDA.

This imagery dataset consists of 3-meter resolution, lidar-derived imagery of the Honesdale 30 x 60 minute quadrangle in Pennsylvania and part of New York. It also covers part of the Delaware River Basin. The source data used to construct this imagery consists of 1-meter resolution lidar-derived digital elevation models (DEMs). The lidar source data were compiled from different acquisitions published between 2017 and 2019 from the Pennsylvania Spatial Data Access (PASDA). The data were processed using geographic information systems (GIS) software. The data is projected in North America Datum (NAD) UTM Zone 18 North. This representation illustrates the terrain as a hillshade with contrast adjusted to highlight local relief according to a topographic position index (TPI) calculation.

This imagery dataset consists of 3-meter resolution, lidar-derived imagery of the Allentown 30 x 60 minute quadrangle in Pennsylvania and part of New Jersey. It also covers part of the Delaware River Basin. The source data used to construct this imagery consists of 1-meter and 2-meter resolution Lidar-derived digital elevation models (DEMs). The lidar source data were compiled from different acquisitions published between 2010 and 2019 from the U.S. Department of Agriculture (USDA) and the Pennsylvania Spatial Data Access (PASDA). The data were processed using geographic information systems (GIS) software. The data is projected in North America Datum (NAD) UTM Zone 18 North. This representation illustrates the terrain as a hillshade with contrast adjusted to highlight local relief according to a topographic position index (TPI) calculation.

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

This data is hosted at, and may be downloaded or accessed from PASDA, the Pennsylvania Spatial Data Access Geospatial Data Clearinghouse http://www.pasda.psu.edu/uci/DataSummary.aspx?dataset=3193

Allegheny County Imagery data from 2017, hosted by PASDA.

This imagery dataset consists of 3-meter resolution, lidar-derived imagery of the Scranton 30 x 60 minute quadrangle in Pennsylvania. It also covers part of the Delaware River Basin. The source data used to construct this imagery consists of 1-meter resolution lidar-derived digital elevation models (DEMs). The lidar source data were compiled from different acquisitions published between 2017 and 2019 from the Pennsylvania Spatial Data Access (PASDA). The data were processed using geographic information systems (GIS) software. The data is projected in North America Datum (NAD) UTM Zone 18 North. This representation illustrates the terrain as a hillshade with contrast adjusted to highlight local relief according to a topographic position index (TPI) calculation.

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.

This data is hosted at, and may be downloaded or accessed from PASDA, the Pennsylvania Spatial Data Access Geospatial Data Clearinghouse http://www.pasda.psu.edu/uci/DataSummary.aspx?dataset=3208

Clipped to Counties - Mapping Area polygon - High resolution land cover dataset for the Delaware River Basin, an area comprised of parts of six counties in the state of New York and four counties in Pennsylvania. Seven land cover classes were mapped: (1) tree canopy, (2) grass/shrub, (3) bare earth, (4) water, (5) buildings, (6) roads, and (7) other paved surfaces. The minimum mapping unit for the delineation of features was set at six square meters. The primary sources used to derive this land cover layer were 2008 LiDAR data and 2010 - 2011 NAIP imagery. LiDAR coverage was complete for the Pennsylvaia portion of the AOI, however, LiDAR was unavailable for large portions of the New York portion. Where LiDAR was not available, imagery was the primary data source. Ancillary data sources included GIS data (eg. such as hydrology, breakline and buildings) provided by the counties of Lackawana, Monroe, Pike and Wayne, PA, as well as the New York State GIS Clearinghouse. Some of these vector datasets were edited by the UVM Spatial Analysis lab through manual interpretation. Other datasets, such as bare soil, were created by the UVM Spatial Anyslsis Lab in order to assist in landcover creation. This land cover dataset is considered current for Pennsylvania portion of the study area as of summer 2010. The dataset is current as of summer 2011 for the New York counties of Chenango, Delaware, Orange and Sullivan. Broome County, NY, is considered current as of summer 2010. Ulster County, NY, employed data from both summer 2010 and summer 2011, therefore currentness varies throughout the county. Object-based image analysis techniques (OBIA) were employed to extract land cover information using the best available remotely sensed and vector GIS datasets. OBIA systems 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. No accuracy assessment was conducted, but the dataset was subject to a thorough manual quality control.

This data is hosted at, and may be downloaded or accessed from PASDA, the Pennsylvania Spatial Data Access Geospatial Data Clearinghouse http://www.pasda.psu.edu/uci/DataSummary.aspx?dataset=3167

High resolution land cover dataset for Philadelphia. Seven land cover classes were mapped: (1) tree canopy, (2) grass/shrub, (3) bare earth, (4) water, (5) buildings, (6) roads, and (7) other paved surfaces. The minimum mapping unit for the delineation of features was set at ten square feet. The primary sources used to derive this land cover layer were 2008 Orthophotography and 2008 LiDAR LAS data. Ancillary data sources included GIS data (building footprints, road polygons, and hydrography) provided by City of Philadelphia. This land cover dataset is considered current as of 2008. Object-based image analysis techniques (OBIA) were employed to extract land cover information using the best available remotely sensed and vector GIS datasets. OBIA systems 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. No accuracy assessment was conducted, but the dataset was subject to a thorough manual quality control. More than 30700 corrections were made to the classification.

This data is hosted at, and may be downloaded or accessed from PASDA, the Pennsylvania Spatial Data Access Geospatial Data Clearinghouse http://www.pasda.psu.edu/uci/DataSummary.aspx?dataset=138

This data set represents the extent, approximate location and type of wetlands and deepwater habitats in the conterminous United States. These data delineate the areal extent of wetlands and surface waters as defined by Cowardin et al. (1979).

Certain wetland habitats are excluded from the National mapping program because of the limitations of aerial imagery as the primary data source used to detect wetlands. These habitats include seagrasses or submerged aquatic vegetation that are found in the intertidal and subtidal zones of estuaries and near shore coastal waters. Some deepwater reef communities (coral or tuberficid worm reefs) have also been excluded from the inventory. These habitats, because of their depth, go undetected by aerial imagery.

By policy, the Service also excludes certain types of "farmed wetlands" as may be defined by the Food Security Act or that do not coincide with the Cowardin et al. definition. Contact the Service's Regional Wetland Coordinator for additional information on what types of farmed wetlands are included on wetland maps.

This data is hosted at, and may be downloaded or accessed from PASDA, the Pennsylvania Spatial Data Access Geospatial Data Clearinghouse http://www.pasda.psu.edu/uci/DataSummary.aspx?dataset=1457

High resolution land cover dataset for the Delaware River Basin, an area comprised of parts of six counties in the state of New York and four counties in Pennsylvania. Seven land cover classes were mapped: (1) tree canopy, (2) grass/shrub, (3) bare earth, (4) water, (5) buildings, (6) roads, and (7) other paved surfaces. The minimum mapping unit for the delineation of features was set at six square meters. The primary sources used to derive this land cover layer were 2008 LiDAR data and 2010 - 2011 NAIP imagery. LiDAR coverage was complete for the Pennsylvaia portion of the AOI, however, LiDAR was unavailable for large portions of the New York portion. Where LiDAR was not available, imagery was the primary data source. Ancillary data sources included GIS data (eg. such as hydrology, breakline and buildings) provided by the counties of Lackawana, Monroe, Pike and Wayne, PA, as well as the New York State GIS Clearinghouse. Some of these vector datasets were edited by the UVM Spatial Analysis lab through manual interpretation. Other datasets, such as bare soil, were created by the UVM Spatial Anyslsis Lab in order to assist in landcover creation. This land cover dataset is considered current for Pennsylvania portion of the study area as of summer 2010. The dataset is current as of summer 2011 for the New York counties of Chenango, Delaware, Orange and Sullivan. Broome County, NY, is considered current as of summer 2010. Ulster County, NY, employed data from both summer 2010 and summer 2011, therefore currentness varies throughout the county. Object-based image analysis techniques (OBIA) were employed to extract land cover information using the best available remotely sensed and vector GIS datasets. OBIA systems 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. No accuracy assessment was conducted, but the dataset was subject to a thorough manual quality control.

This data is hosted at, and may be downloaded or accessed from PASDA, the Pennsylvania Spatial Data Access Geospatial Data Clearinghouse http://www.pasda.psu.edu/uci/DataSummary.aspx?dataset=3166

The aerial imagery used to create this tile layer is available for download in TIFF format on PASDA.The 2020 Aerial Photography Tile Index is also available for download on PASDA.View metadata for key information about this dataset.For questions about this dataset or technical assistance, email maps@phila.gov.

This data set represents the extent, approximate location and type of wetlands and deepwater habitats in the conterminous United States. These data delineate the areal extent of wetlands and surface waters as defined by Cowardin et al. (1979).

Certain wetland habitats are excluded from the National mapping program because of the limitations of aerial imagery as the primary data source used to detect wetlands. These habitats include seagrasses or submerged aquatic vegetation that are found in the intertidal and subtidal zones of estuaries and near shore coastal waters. Some deepwater reef communities (coral or tuberficid worm reefs) have also been excluded from the inventory. These habitats, because of their depth, go undetected by aerial imagery.

By policy, the Service also excludes certain types of "farmed wetlands" as may be defined by the Food Security Act or that do not coincide with the Cowardin et al. definition. Contact the Service's Regional Wetland Coordinator for additional information on what types of farmed wetlands are included on wetland maps.

This data is hosted at, and may be downloaded or accessed from PASDA, the Pennsylvania Spatial Data Access Geospatial Data Clearinghouse http://www.pasda.psu.edu/uci/DataSummary.aspx?dataset=1456

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.

This data is hosted at, and may be downloaded or accessed from PASDA, the Pennsylvania Spatial Data Access Geospatial Data Clearinghouse http://www.pasda.psu.edu/uci/DataSummary.aspx?dataset=3147

This is a connection to the Dauphin County GIS Data Portal. The following categories are available: Boundaries Election Hydrology Tax Assessment Transportation Elevation

The following Applications are available: Mobile Parcel Viewer - provides the general public and other interested parties access to searchable and interactive information such as property tax and assessment information or the locations of water access points.

MDJ (Magisterial District Judges) Locator - Identifies Magisterial District Judge and Municipality

Dauphin County Homicides - Application showing Dauphin County homicides in 2015 and 2016

Parcel Viewer - Search for a Parcel, Property Information, Tax Assessment, Municipality, Assessed Land or Building Value, Acres, etc.

Digital Data is distributed as a countywide dataset in ESRI shapefile format. Aerial imagery is available as a countywide dataset either through Dauphin County GIS or downloaded from PA Spatial Data Access (PASDA also available on the Commonwealth Open Data portal)

The aerial imagery used to create this tile layer is available for download in TIFF format on PASDA.The 2024 Aerial Photography Tile Index is also available for download on PASDA.For questions about this dataset or technical assistance, email maps@phila.gov.

Questions Email: pasda@psu.edu

DOQQ imagery from PASDA (Pennsylvania Spatial Data Access)

USGS Digital Orthophoto Quarter Quadrangle images for Pennsylvania 1993

This data set represents the extent, approximate location and type of wetlands and deepwater habitats in the conterminous United States. These data delineate the areal extent of wetlands and surface waters as defined by Cowardin et al. (1979).

Certain wetland habitats are excluded from the National mapping program because of the limitations of aerial imagery as the primary data source used to detect wetlands. These habitats include seagrasses or submerged aquatic vegetation that are found in the intertidal and subtidal zones of estuaries and near shore coastal waters. Some deepwater reef communities (coral or tuberficid worm reefs) have also been excluded from the inventory. These habitats, because of their depth, go undetected by aerial imagery.

By policy, the Service also excludes certain types of "farmed wetlands" as may be defined by the Food Security Act or that do not coincide with the Cowardin et al. definition. Contact the Service's Regional Wetland Coordinator for additional information on what types of farmed wetlands are included on wetland maps.

This data is hosted at, and may be downloaded or accessed from PASDA, the Pennsylvania Spatial Data Access Geospatial Data Clearinghouse http://www.pasda.psu.edu/uci/DataSummary.aspx?dataset=1453