This layer is a subset of the Maine Conserved Lands layer. The full dataset is here. The conserved lands layer is an inventory of Maine’s terrestrial protected areas that are dedicated to the preservation of biological diversity and to other natural, recreation and cultural uses, and which are managed for these purposes through legal or other effective means. Conserved Lands contains conservation lands ownership boundaries at 1:24,000 scale for Maine land in federal, state, municipal and non-profit ownership with easements. State, county, town, and coast boundary data were obtained from MEGIS town boundary dataset METWP24. 1:24,000 US Geological Survey (USGS) digital line graph data was used for hydrography and transportation features. Where state, county, and town boundaries were coincident with property boundaries, the coincident features were taken from METWP24. Where hydrography, roads, railroads and power-lines were coincident with property boundaries, the coincident features were taken from 1:24,000 digital line graph data. The ownership lines do not represent legal boundaries nor are the ownership lines a survey. Conserved Lands is an inventory of approximate property boundaries.Conserved Lands was created to provide GIS coverage for the conservation lands database. The ownership lines do not represent legal boundaries nor are the ownership lines a survey. The data contained in Conserved Lands is an inventory only. Users must assume responsibility in determining the usability of this data for their purposes. Data at this scale is suitable for local and regional planning. Original mapping was produced in 1989, updated in 1993 by R.D. Kelly Jr. of the State Planning Office. Data is continually updated.

The conserved lands layer is an inventory of Maine’s terrestrial protected areas that are dedicated to the preservation of biological diversity and to other natural, recreation and cultural uses, and which are managed for these purposes through legal or other effective means. Conserved Lands contains conservation lands ownership boundaries at 1:24,000 scale for Maine land in federal, state, municipal and non-profit ownership with easements. State, county, town, and coast boundary data were obtained from MEGIS town boundary dataset METWP24. 1:24,000 US Geological Survey (USGS) digital line graph data was used for hydrography and transportation features. Where state, county, and town boundaries were coincident with property boundaries, the coincident features were taken from METWP24. Where hydrography, roads, railroads and power-lines were coincident with property boundaries, the coincident features were taken from 1:24,000 digital line graph data. The ownership lines do not represent legal boundaries nor are the ownership lines a survey. Conserved Lands is an inventory of approximate property boundaries.Users must assume responsibility in determining the usability of this data for their purposes. Data at this scale is suitable for local and regional planning. Original mapping was produced in 1989, updated in 1993 by R.D. Kelly Jr. of the State Planning Office. Conserved Lands data submittalConservation organizations, land trusts, and municipalities can submit new or updated fee ownership or easement parcels to the statewide Conserved Lands layer using one of two online interfaces developed by Maine Coast Heritage Trust and the Beginning with Habitat program (Department of Inland Fisheries and Wildlife):Individual parcel tool - a simplified process designed for easy submission, without the need for GISShapefile upload - a web form ideal for uploading multiple features at a time (add your data as a zip file)For batch submissions, please ensure that the shapefiles adhere to the conserved lands template schema. If you have questions about using the template or the submittal process, contact Amy.Dowley@maine.gov.Updates are processed annually.

Geospatial data about Meigs County, Ohio Addresses. Export to CAD, GIS, PDF, CSV and access via API.

Image Service | OGC WCS | OGC WMS | KMZORTHO_1F are high resolution digital orthophotographs produced from aerial photos collected over southwestern, central and northeastern Maine in the Spring of 2003, 2004 and 2005. Each pixel represents a planimetric square 1 foot on a side on the ground. Aerial photography for ORTHO_1F was flown at 6,000 feet above mean ground level. Source elevation data were 10 meter Digital Elevation Models produced for this project by USGS from 1:24,000 scale elevation and hydrography data supplied by MEGIS. The digital orthorectified images (image chips) are referenced to North American Datum 1983, UTM Zone 19, expressed in units of meters. Cartographic Services for orthorectification and the creation of digital elevation models were provided by USGS Mid-Continent Mapping Center (USGSMCMC). ORTHO_1F provides a digital photographic map suitable for applications requiring a 1:2400 map scale, a National Map Accuracy Standard (NMAS) of +/- 6.67 feet. The multi-agreement program was developed and funded in coordination with the Maine GeoLibrary Board. The U.S. Department of Agriculture, Natural Resource Conservation Service (NRCS) contributed toward this project via a separate funding agreement with USGS. The completed orthorectified files represent quarter-quarter-quadrangle (QQQ) sized tiles with a 300m over-edge. All overedges for ORTHO_1F also overlap adjacent ORTHO_HF and ORTHO_2F orthophotography by this distance. ORTHO_1F tiles provide complete coverage of the TIER A boundaries as defined by the Towns designated TIER A will have complete coverage by 1 foot GSD imagery.

Image Service | OGC WCS | OGC WMS | KMZORTHO_2F was collected at a 2 foot ground sample distance (GSD) , high resolution digital orthophotographs produced from aerial photos collected over southwestern, central and northeastern Maine in the Spring of 2003, 2004 and 2005. Each pixel represents a planimetric square 2 feet on a side on the ground. Aerial photography for ORTHO_2F was flown at 12,000 feet above mean ground level. Source elevation data were 10 meter Digital Elevation Models produced for this project by USGS from 1:24,000 scale elevation and hydrography data supplied by MEGIS. The digital orthorectified images (image chips) are referenced to North American Datum 1983, UTM Zone 19, expressed in units of meters. Cartographic Services for orthorectification and the creation of digital elevation models were provided by USGS Mid-Continent Mapping Center (USGSMCMC). ORTHO_2F provides a digital photographic map suitable for applications requiring a 1:4800 map scale, a National Map Accuracy Standard (NMAS) of +/- 13.33 feet. The multi-agreement program was developed and funded in coordination with the Maine GeoLibrary Board. The U.S. Department of Agriculture, Natural Resource Conservation Service (NRCS) contributed toward this project via a separate funding agreement with USGS. The completed orthorectified GeoTIFF files represent quarter-quadrangle (QQ) sized tiles with a 300m over-edge. All overedges for ORTHO_2f overlap adjacent ORTHO_1F orthophotography by this distance. ORTHO_2F tiles provide complete coverage of the TIER B boundaries as defined by the project. Tiles split by tier and project boundaries were completed to their full tile extent. Towns designated TIER B will have complete coverage by 2 foot GSD imagery.

Feature class that compare the elevations between seawall crests (extracted from available LiDAR datasets from 2010 and 2013) with published FEMA Base Flood Elevations (BFEs) from preliminary FEMA DFIRMS (Panels issued in 2018 and 2019) in coastal York and Cumberland counties (up through Willard Beach in South Portland). The dataset included the development of an inventory of coastal armor structures from a range of different datasets. Feature classes include the following:Steps to create the dataset included:Shoreline structures from the most recent NOAA EVI LANDWARD_SHORETYPE feature class were extracted using the boundaries of York and Cumberland counties. This included 1B: Exposed, Solid Man-Made structures, 8B: Sheltered, Solid Man-Made Structures; 6B: Riprap, and 8C: Sheltered Riprap. This resulted in the creation of Cumberland_ESIL_Structures and York_ESIL_Structures. Note that ESIL uses the MHW line as the feature base.Shoreline structures from the work by Rice (2015) were extracted using the York and Cumberland county boundaries. This resulted in the creation of Cumberland_Rice_Structures and York_Rice_Structures.Additional feature classes for structures were created for York and Cumberland county structures that were missed. This was Slovinsky_York_Structures and Slovinsky_Cumberland_Structures. GoogleEarth imagery was inspected while additional structures were being added to the GIS. 2012 York and Cumberland County imagery was used as the basemap, and structures were classified as bulkheads, rip rap, or dunes (if known). Also, whether or not the structure was in contact with the 2015 HAT was noted.MEDEP was consulted to determine which permit data (both PBR and Individual Permit, IP, data) could be used to help determine where shoreline stabilization projects may have been conducted adjacent to or on coastal bluffs. A file was received for IP data and brought into GIS (DEP_Licensing_Points). This is a point file for shoreline stabilization permits under NRPA.Clip GISVIEW.MEDEP.Permit_By_Rule_Locations to the boundaries of the study area and output DEP_PBR_Points.Join GISVIEW.sde>GISVIEW.MEDEP.PBR_ACTIVITY to the DEP_PBR_Points using the PBR_ID Field. Then, export this file as DEP_PBR_Points2. Using the new ACTIVITY_DESC field, select only those activities that relate to shoreline stabilization projects:PBR_ACTIVITY ACTIVITY_DESC02 Act. Adjacent to a Protected Natural Resource04 Maint Repair & Replacement of Structure08 Shoreline StabilizationSelect by Attributes > PBR_ACTIVITY IN (‘02’, ‘04’, ‘08’) select only those activities likely to be related to shoreline stabilization, and export the selected data as a DEP_PBR_Points3. Then delete 1 and 2, and rename this final product as DEP_PBR_Points.Next, visually inspect the Licensing and PBR files using ArcMap 2012, 2013 imagery, along with Google Earth imagery to determine the extents of armoring along the shoreline.Using EVI and Rice data as indicators, manually inspect and digitize sections of the coastline that are armored. Classify the seaward shoreline type (beach, mudflat, channel, dune, etc.) and the armor type (wall or bulkhead). Bring in the HAT line and, using that and visual indicators, identify whether or not the armored sections are in contact with HAT. Use Google Earth at the same time as digitizing in order to help constrain areas. Merge digitized armoring into Cumberland_York_Merged.Bring the preliminary FEMA DFIRM data in and use “intersect” to assign the different flood zones and elevations to the digitized armored sections. This was done first for Cumberland, then for York Counties. Delete ancillary attributes, as needed. Resulting layer is Cumberland_Structure_FloodZones and York_Structure_FloodZones.Go to NOAA Digital Coast Data Layers and download newest LiDAR data for York and Cumberland county beach, dune, and just inland areas. This includes 2006 and newer topobathy data available from 2010 (entire coast), and selected areas from 2013 and 2014 (Wells, Scarborough, Kennebunk).Mosaic the 2006, 2010, 2013 and 2014 data (with 2013 and 2014 being the first dataset laying on top of the 2010 data) Mosaic this dataset into the sacobaydem_ftNAVD raster (this is from the MEGIS bare-earth model). This will cover almost all of the study area except for armor along several areas in York. Resulting in LidAR206_2010_2013_Mosaic.tif.Using the LiDAR data as a proxy, create a “seaward crest” line feature class which follows along the coast and extracts the approximate highest point (cliff, bank, dune) along the shoreline. This will be used to extract LiDAR data and compare with preliminary flood zone information. The line is called Dune_Crest.Using an added tool Points Along Line, create points at 5 m spacing along each of the armored shoreline feature lines and the dune crest lines. Call the outputs PointsonLines and PointsonDunes.Using Spatial Analyst, Extract LIDAR elevations to the points using the 2006_2010_2013 Mosaic first. Call this LidarPointsonLines1. Select those points which have NULL values, export as this LiDARPointsonLines2. Then rerun Extract Values to Points using just the selected data and the state MEGIS DEM. Convert RASTERVALU to feet by multiplying by 3.2808 (and rename as Elev_ft). Select by Attributes, find all NULL values, and in an edit session, delete them from LiDARPointsonLines. Then, merge the 2 datasets and call it LidarPointsonLines. Do the same above with dune lines and create LidarPointsonDunes.Next, use the Cumberland and York flood zone layers to intersect the points with the appropriate flood zone data. Create ….CumbFIRM and …YorkFIRM files for the dunes and lines.Select those points from the Dunes feature class that are within the X zone – these will NOT have an associated BFE for comparison with the Lidar data. Export the Dune Points as Cumberland_York_Dunes_XZone. Run NEAR and use the merged flood zone feature class (with only V, AE, and AO zones selected). Then, join the flood zone data to the feature class using FID (from the feature class) and OBJECTID (from the flood zone feature class). Export as Cumberland_York_Dunes_XZone_Flood. Delete ancillary columns of data, leaving the original FLD_ZONE (X), Elev_ft, NEAR_DIST (distance, in m, to the nearest flood zone), FLD_ZONE_1 (the near flood zone), and the STATIC_BFE_1 (the nearest static BFE).Do the same as above, except with the Structures file (Cumberland_York_Structures_Lidar_DFIRM_Merged), but also select those features that are within the X zone and the OPEN WATER. Export the points as Cumberland_York_Structures_XZone. Again, run the NEAR using the merged flood zone and only AE, VE, and AO zones selected. Export the file as Cumberland_York_Structures_XZone_Flood.Merge the above feature classes with the original feature classes. Add a field BFE_ELEV_COMPARE. Select all those features whose attributes have a VE or AE flood zone and use field calculator to calculate the difference between the Elev_ft and the BFE (subtracting the STATIC_BFE from Elev_ft). Positive values mean the maximum wall value is higher than the BFE, while negative values mean the max is below the BFE. Then, select the remaining values with switch selection. Calculate the same value but use the NEAR_STATIC_BFE value instead. Select by Attributes>FLD_ZONE=AO, and use the DEPTH value to enter into the above created fields as negative values. Delete ancilary attribute fields, leaving those listed in the _FINAL feature classes described above the process steps section.

Feature class that compares the elevations between sand dune crests (extracted from available LiDAR datasets from 2010 and 2013) with published FEMA Base Flood Elevations (BFEs) from preliminary FEMA DFIRMS (Panels issued in 2018 and 2019) in coastal York and Cumberland counties (up through Willard Beach in South Portland). Steps to create the dataset included:Shoreline structures from the most recent NOAA EVI LANDWARD_SHORETYPE feature class were extracted using the boundaries of York and Cumberland counties. This included 1B: Exposed, Solid Man-Made structures, 8B: Sheltered, Solid Man-Made Structures; 6B: Riprap, and 8C: Sheltered Riprap. This resulted in the creation of Cumberland_ESIL_Structures and York_ESIL_Structures. Note that ESIL uses the MHW line as the feature base.Shoreline structures from the work by Rice (2015) were extracted using the York and Cumberland county boundaries. This resulted in the creation of Cumberland_Rice_Structures and York_Rice_Structures.Additional feature classes for structures were created for York and Cumberland county structures that were missed. This was Slovinsky_York_Structures and Slovinsky_Cumberland_Structures. GoogleEarth imagery was inspected while additional structures were being added to the GIS. 2012 York and Cumberland County imagery was used as the basemap, and structures were classified as bulkheads, rip rap, or dunes (if known). Also, whether or not the structure was in contact with the 2015 HAT was noted.MEDEP was consulted to determine which permit data (both PBR and Individual Permit, IP, data) could be used to help determine where shoreline stabilization projects may have been conducted adjacent to or on coastal bluffs. A file was received for IP data and brought into GIS (DEP_Licensing_Points). This is a point file for shoreline stabilization permits under NRPA.Clip GISVIEW.MEDEP.Permit_By_Rule_Locations to the boundaries of the study area and output DEP_PBR_Points.Join GISVIEW.sde>GISVIEW.MEDEP.PBR_ACTIVITY to the DEP_PBR_Points using the PBR_ID Field. Then, export this file as DEP_PBR_Points2. Using the new ACTIVITY_DESC field, select only those activities that relate to shoreline stabilization projects:PBR_ACTIVITY ACTIVITY_DESC02 Act. Adjacent to a Protected Natural Resource04 Maint Repair & Replacement of Structure08 Shoreline StabilizationSelect by Attributes > PBR_ACTIVITY IN (‘02’, ‘04’, ‘08’) select only those activities likely to be related to shoreline stabilization, and export the selected data as a DEP_PBR_Points3. Then delete 1 and 2, and rename this final product as DEP_PBR_Points.Next, visually inspect the Licensing and PBR files using ArcMap 2012, 2013 imagery, along with Google Earth imagery to determine the extents of armoring along the shoreline.Using EVI and Rice data as indicators, manually inspect and digitize sections of the coastline that are armored. Classify the seaward shoreline type (beach, mudflat, channel, dune, etc.) and the armor type (wall or bulkhead). Bring in the HAT line and, using that and visual indicators, identify whether or not the armored sections are in contact with HAT. Use Google Earth at the same time as digitizing in order to help constrain areas. Merge digitized armoring into Cumberland_York_Merged.Bring the preliminary FEMA DFIRM data in and use “intersect” to assign the different flood zones and elevations to the digitized armored sections. This was done first for Cumberland, then for York Counties. Delete ancillary attributes, as needed. Resulting layer is Cumberland_Structure_FloodZones and York_Structure_FloodZones.Go to NOAA Digital Coast Data Layers and download newest LiDAR data for York and Cumberland county beach, dune, and just inland areas. This includes 2006 and newer topobathy data available from 2010 (entire coast), and selected areas from 2013 and 2014 (Wells, Scarborough, Kennebunk).Mosaic the 2006, 2010, 2013 and 2014 data (with 2013 and 2014 being the first dataset laying on top of the 2010 data) Mosaic this dataset into the sacobaydem_ftNAVD raster (this is from the MEGIS bare-earth model). This will cover almost all of the study area except for armor along several areas in York. Resulting in LidAR206_2010_2013_Mosaic.tif.Using the LiDAR data as a proxy, create a “seaward crest” line feature class which follows along the coast and extracts the approximate highest point (cliff, bank, dune) along the shoreline. This will be used to extract LiDAR data and compare with preliminary flood zone information. The line is called Dune_Crest.Using an added tool Points Along Line, create points at 5 m spacing along each of the armored shoreline feature lines and the dune crest lines. Call the outputs PointsonLines and PointsonDunes.Using Spatial Analyst, Extract LIDAR elevations to the points using the 2006_2010_2013 Mosaic first. Call this LidarPointsonLines1. Select those points which have NULL values, export as this LiDARPointsonLines2. Then rerun Extract Values to Points using just the selected data and the state MEGIS DEM. Convert RASTERVALU to feet by multiplying by 3.2808 (and rename as Elev_ft). Select by Attributes, find all NULL values, and in an edit session, delete them from LiDARPointsonLines. Then, merge the 2 datasets and call it LidarPointsonLines. Do the same above with dune lines and create LidarPointsonDunes.Next, use the Cumberland and York flood zone layers to intersect the points with the appropriate flood zone data. Create ….CumbFIRM and …YorkFIRM files for the dunes and lines.Select those points from the Dunes feature class that are within the X zone – these will NOT have an associated BFE for comparison with the Lidar data. Export the Dune Points as Cumberland_York_Dunes_XZone. Run NEAR and use the merged flood zone feature class (with only V, AE, and AO zones selected). Then, join the flood zone data to the feature class using FID (from the feature class) and OBJECTID (from the flood zone feature class). Export as Cumberland_York_Dunes_XZone_Flood. Delete ancillary columns of data, leaving the original FLD_ZONE (X), Elev_ft, NEAR_DIST (distance, in m, to the nearest flood zone), FLD_ZONE_1 (the near flood zone), and the STATIC_BFE_1 (the nearest static BFE).Do the same as above, except with the Structures file (Cumberland_York_Structures_Lidar_DFIRM_Merged), but also select those features that are within the X zone and the OPEN WATER. Export the points as Cumberland_York_Structures_XZone. Again, run the NEAR using the merged flood zone and only AE, VE, and AO zones selected. Export the file as Cumberland_York_Structures_XZone_Flood.Merge the above feature classes with the original feature classes. Add a field BFE_ELEV_COMPARE. Select all those features whose attributes have a VE or AE flood zone and use field calculator to calculate the difference between the Elev_ft and the BFE (subtracting the STATIC_BFE from Elev_ft). Positive values mean the maximum wall value is higher than the BFE, while negative values mean the max is below the BFE. Then, select the remaining values with switch selection. Calculate the same value but use the NEAR_STATIC_BFE value instead. Select by Attributes>FLD_ZONE=AO, and use the DEPTH value to enter into the above created fields as negative values. Delete ancilary attribute fields, leaving those listed in the _FINAL feature classes described above the process steps section.

This layer is a subset of the Maine Conserved Lands layer. The full dataset is here. The conserved lands layer is an inventory of Maine’s terrestrial protected areas that are dedicated to the preservation of biological diversity and to other natural, recreation and cultural uses, and which are managed for these purposes through legal or other effective means. Conserved Lands contains conservation lands ownership boundaries at 1:24,000 scale for Maine land in federal, state, municipal and non-profit ownership with easements. State, county, town, and coast boundary data were obtained from MEGIS town boundary dataset METWP24. 1:24,000 US Geological Survey (USGS) digital line graph data was used for hydrography and transportation features. Where state, county, and town boundaries were coincident with property boundaries, the coincident features were taken from METWP24. Where hydrography, roads, railroads and power-lines were coincident with property boundaries, the coincident features were taken from 1:24,000 digital line graph data. The ownership lines do not represent legal boundaries nor are the ownership lines a survey. Conserved Lands is an inventory of approximate property boundaries.Conserved Lands was created to provide GIS coverage for the conservation lands database. The ownership lines do not represent legal boundaries nor are the ownership lines a survey. The data contained in Conserved Lands is an inventory only. Users must assume responsibility in determining the usability of this data for their purposes. Data at this scale is suitable for local and regional planning. Original mapping was produced in 1989, updated in 1993 by R.D. Kelly Jr. of the State Planning Office.

This layer is a subset of the Maine Conserved Lands layer. The full dataset is here. The conserved lands layer is an inventory of Maine’s terrestrial protected areas that are dedicated to the preservation of biological diversity and to other natural, recreation and cultural uses, and which are managed for these purposes through legal or other effective means. Conserved Lands contains conservation lands ownership boundaries at 1:24,000 scale for Maine land in federal, state, municipal and non-profit ownership with easements. State, county, town, and coast boundary data were obtained from MEGIS town boundary dataset METWP24. 1:24,000 US Geological Survey (USGS) digital line graph data was used for hydrography and transportation features. Where state, county, and town boundaries were coincident with property boundaries, the coincident features were taken from METWP24. Where hydrography, roads, railroads and power-lines were coincident with property boundaries, the coincident features were taken from 1:24,000 digital line graph data. The ownership lines do not represent legal boundaries nor are the ownership lines a survey. Conserved Lands is an inventory of approximate property boundaries.Conserved Lands was created to provide GIS coverage for the conservation lands database. The ownership lines do not represent legal boundaries nor are the ownership lines a survey. The data contained in Conserved Lands is an inventory only. Users must assume responsibility in determining the usability of this data for their purposes. Data at this scale is suitable for local and regional planning. Original mapping was produced in 1989, updated in 1993 by R.D. Kelly Jr. of the State Planning Office. Data is continually updated.

Wildlife Management Areas (WMAs)The mission and purpose of the State owned WMAs is to provide a statewide, ecologically based system of land holdings for the protection and enhancement of important wildlife habitats that also provide opportunities for all types of public recreation, where those forms of recreation do not unduly impact the wildlife resources.Wildlife Management Areas are a subset of the Conserved Lands feature layer:Conserved Lands contains conservation lands ownership boundaries at 1:24,000 scale for Maine land in federal, state, municipal and non-profit ownership with easements. State, county, town, and coast boundary data were obtained from MEGIS town boundary dataset METWP24. 1:24,000 US Geological Survey (USGS) digital line graph data was used for hydrography and transportation features. Where state, county, and town boundaries were coincident with property boundaries, the coincident features were taken from METWP24. Where hydrography, roads, railroads and power-lines were coincident with property boundaries, the coincident features were taken from 1:24,000 digital line graph data. The ownership lines do not represent legal boundaries nor are the ownership lines a survey. Conserved Lands is an inventory of approximate property boundaries.Original Source Data: Maine Conserved Lands

Download .zipMaps and data associated with oil-and-gas wells represent one of the largest datasets at the Ohio Department of Natural Resources. This GIS data layer contains all the locatable oil-and-gas wells in Ohio. The feature is derived from coordinates obtained from the Division of Oil and Gas Resources Management (DOGRM) oil and gas well database – Risk Based Data Management System (RBDMS). The RBDMS database has a long history and is a comprehensive collection of well data from historic pre-1980 paper well records (digitized by the Division of Geological Survey (DGS)) to post-1980 DOGRM database solutions.Since 1860, it is estimated that more than 267,000 oil-and-gas wells have been drilled in Ohio. The compressed file also includes a feature used to connect the surface location to the bottom location of a well that has been drilled directionally or horizontally. This feature is NOT the actual wellbore path, it is simply a graphical representation indicating the relationship between the two well points.Contact Information:GIS Support, ODNR GIS ServicesOhio Department of Natural ResourcesDivision of Oil & Gas ResourcesOil and Gas Resources Management2045 Morse Road Bldg F-2Columbus, OH, 43229-6693Telephone: 614-265-6462Email: gis.support@dnr.ohio.gov

BIOPHY depicts boundaries of 15 Biophysical Regions in Maine at 1:250,000 scale. The regions were developed in a statewide classification (McMahon, 1990) by Janet McMahon who examined spatial patterns in a number of mapped environmental variables. These patterns were statistically evaluated using canonical correspondence analysis. Ordinations of 1,966 samples, 95 woody taxa, and 22 environmental variables, reveal that both biophysical regions and woody species vary primarily along a climatic gradient of increasing annual temperature, potential evapotransportation, heat sum, and other factors associated with temperature. Boundaries were mapped for 'Biophysical Regions of Maine' at 1:700000 scale by Maine State Planning Office (MESPO) staff in 1990. Maine Office of Geographic Information Systems (MEGIS) staff digitized these boundaries from the 1990 publication, recompiling the data onto a 1:250,000 scale base. The state boundary and coastline were extracted from the coverage METWP250. Each region contains attribute fields extracted from a summary table on the 1990 publication. The coverage was renamed from BIOPHY250 to BIOPHY in 2001.