Predicted number of trees per acre. Units = count / acre.

This EnviroAtlas dataset addresses the tree buffer along heavily traveled roads. The roads are interstates, arterials, and collectors within the EnviroAtlas community boundary. In this community, tree cover is defined as Trees & Forest, and Woody Wetlands. Sufficient tree bufferage is defined as 25% coverage within the circular moving window with a radius of 14.5m at any given point along the roadway. There are potential negative health effects for those living in a location without a sufficient tree buffer. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. This dataset was produced the US EPA to support research and online mapping activities related to EnviroAtlas. This dataset was produced the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

This dataset provides maps of aboveground forest biomass (AGB) of living trees and standing dead trees in Mg/ha across portions of Northwestern United States, including Washington, Oregon, Idaho, and Montana, at a spatial resolution of 30 m. Forest inventory data were compiled from 29 stakeholders that had overlapping lidar imagery. The collection totaled 3805 field plots with lidar imagery for 176 collections acquired between 2002 and 2016. Plot-level AGB estimates were calculated from tree measurements using the default allometric equations found in the Fire Fuels Extension (FFE) of the Forest Vegetation Simulator (FVS). The random forest algorithm was used to model AGB from lidar height and density metrics that were generated from the lidar returns within fixed-radius field plot footprints, gridded climate metrics obtained from the Climate-FVS Ready Data Server, and topographic estimates extracted from Shuttle Radar Topography Mission (SRTM) 1 Arc-Second Global elevation rasters. AGB was then mapped from the same lidar metrics gridded across the extent of the lidar collections at 30-m resolution. The standard deviation of estimated AGB of the terminal nodes from the random forest predictions was also mapped to show pixel-level model uncertainty. Note that the AGB estimates are, for the most part, a single snapshot in time and that the forest conditions are not necessarily representative of the larger study area.

Trees captured in 1999. Contract NCPC 93-02. This document describes the planimetric map production for the 350 tiles located in Washington DC and the surrounding states of MD and VA.

This EnviroAtlas dataset shows the total block group population and the percentage of the block group population that has little access to potential window views of trees at home. Having little potential access to window views of trees is defined as having no trees and forest land cover within 50 meters. The window views are considered "potential" because the procedure does not account for presence or directionality of windows in one's home. In this community, tree cover is defined as Trees & Forest, and Woody Wetlands. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. This dataset was produced the US EPA to support research and online mapping activities related to EnviroAtlas. This dataset was produced the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

Click to downloadClick for metadataService URL: https://gis.dnr.wa.gov/site2/rest/services/Public_Forest_Practices/WADNR_PUBLIC_FP_Unstable_Slopes/MapServer/3The siteclass data layer was created for use in implementing Forest Practices' Riparian Management Rules. (See WAC 222-30-021 and 222-30-022.)

The siteclass data layer was derived from the DNR soils data layer's site index codes and major tree species codes for western and eastern Washington soils contained in the layer's Soils-Main table and Soils-Pflg (private forest land grade) table. Site index ranges in the Soils_PFLG took precedence over site index ranges in the Soils-Main table where data existed.The siteclass data layer was created for use in implementing new ForestPractices' Riparian Management Rules. (See WAC 222-30-021 and 222-30-022.) The siteclass information was derived from the DNR soils data layer's site indexcodes and major tree species codes for western and eastern Washington soilscontained in the layer's Soils-Main table and Soils-Pflg (private forest landgrade) table. Site index ranges in the Soils_PFLG took precedence over siteindex ranges in the Soils-Main table where data existed.Siteclass codes as derived from the soil survey:For Western Washington, the 50 year site index is used SITECLASS SITE INDEX RANGE I 137+ II 119-136 III 97-118 IV 76-96 V 1-75For Eastern Washington, the 100 year site index is used SITECLASS SITE INDEX RANGE I 120+ II 101-120 III 81-100 IV 61-80 V 1-60In addition to the coding scheme above, the following codes were added forrule compliance: SITECLASS DESCRIPTION 6 (Red Alder) The soils major species code indicated Red Alder 7 (ND/GP) No data), NA, or gravel pit 8 (NC/MFP) Non-commercial or marginal commercial forest land 9 (WAT) Water body(Rule note: If the site index does not exist or indicates red alder,noncommercial, or marginally commercial species, the following apply:If the whole RMZ width is within those categories, use site class V.If those categories occupy only a portion of the RMZ width, then use thesite index for conifer in the adjacent soil polygon.)WADNR SOILS LAYER INFORMATION LAYER: SOILS GEN.SOURCE: State soils mapping program CODE DOCUMENT: State soil surveys CONTACT: NA COVER TYPE: Spatial polygon coverage DATA TYPE: Primary data Information for the SOILS data layer was derived from the Private Forest Land Grading system (PFLG) and subsequent soil surveys. PFLG was a five year mapping program completed in 1980 for the purpose of forest land taxation. It was funded by the Washington State Department of Revenue in cooperation with the Department of Natural Resources, Soil Conservation Service (SCS), USDA Forest Service and Washington State University. State and private lands which had the potential of supporting commercial forest stands were surveyed. Some Indian tribal and federal lands were surveyed. Because this was a cooperative soil survey project, agricultural and non- commercial forest lands were also included within some survey areas. After the Department of Natural Resources originally developed its geographic information system, digitized soils delineations and a few soil attributes were transferred to the system. Remaining PFLG soil attributes were added at a later time and are now available through associated lookup tables. SCS soils data on agricultural lands also have subsequently been added to this data layer. Approximately 1100 townships wholly or partially contain digitized soils data (2101 townships would provide complete coverage of the state of Washington). SOILS data are currently stored in the Polygon Attribute Table (.PAT) and INFO expansion files. COORDINATE SYSTEM: WA State Plane South Zone (5626) (N. zone converted to S. zone) COORDINATE UNITS: Feet HORIZONTAL DATUM: NAD27 PROJECTION NAME: Lambert Conformal Conic **** MAJOR CODES USED FOR SITECLASS DATA*****PFLG DATA: ITEM: PFLG.MAJ.SPEC TITLE: Potential major tree species for given soil FORMAT: INPUT OUTPUT DATA DECIMAL ARRAY ARRAY WIDTH WIDTH TYPE PLACES OCCUR. INDEX ------------------------------------------------- 3 3 C 0 0 0 CODE TABLE OR VALUE RANGE: SOIL.MAJ.SPEC.CODE DESCRIPTION: Potentially major tree species for a given soil type. The data carried by this item describes a major commercial tree species that could potentially grow on a specific soil type as identified in the Private Forest Land Grading program (PFLG). Non-tree codes are also included to map non-soil ground cover, e.g. water, gravel pits. ITEM: PFLG.SITE.INDEX TITLE: Mean site index calc.from trees on given soil FORMAT: INPUT OUTPUT DATA DECIMAL ARRAY ARRAY WIDTH WIDTH TYPE PLACES OCCUR. INDEX ------------------------------------------------- 3 3 I 0 0 0 CODE TABLE OR VALUE RANGE: 0-200 DESCRIPTION: Site index data collected for the Private Forest Land Grading soils program (PFLG). It is a designation of the quality of a forest site based on the height of of the tallest trees (dominant and co-dominant trees) in a stand at an arbitrarily chosen age. Usually the age chosen is 50 or 100 years. For example, if the average height attained by the tallest trees in a fully stocked stand at the age of 50 years is 75 feet, the site index is 75 feet. Westside site conditions are estimated by using an index age of 50 years, while eastside site conditions are estimated by using an index age of 100 years.--------------------------------------------------------------------SOILS-MAIN DATA: CODE TABLE NAME: SOIL.MAJ.SPEC.CODE ----------------------------------------------------------------------------- CODE MAP/REPORT MAP CODE DESCRIPTION LABEL SYMB --------- ------------ ---- -------------------------------------------------- AF ALPINE FIR 0 Subalpine fir DF DOUGLAS FIR 0 Douglas fir GF GRAND FIR 0 Grand fir GP GRAVEL PIT 0 Gravel pit LP LODGEPOLE PN 0 Lodgepole pine MFP MAR FOR PROD 0 Marginal forest productivity NA N/A 0 Not applicable NC NON-COMMERC 0 Non-commercial ND NO DATA 0 No data PP PONDEROSA PN 0 Ponderosa pine RA RED ALDER 0 Red alder WAT WATER 0 Water WH W HEMLOCK 0 Western hemlock WL W LARCH 0 Western larch WP W WHITE PINE 0 Western white pine ITEM: SITE.INDEX.SIDE TITLE: Indicates 100 yr or 50 yr soil site index FORMAT: INPUT OUTPUT DATA DECIMAL ARRAY ARRAY WIDTH WIDTH TYPE PLACES OCCUR. INDEX ------------------------------------------------- 1 1 C 0 0 0 CODE FILE OR VALUE RANGE: SITE.INDEX.SIDE.CODE DESCRIPTION: Code used to indicate whether 100 year or 50 year site index tables are used to calculate the site index of a soil type. Note that some site indexes for "eastside" soils are based on the 50 year index table. SITE.INDEX.SIDE Indicates 100 yr or 50 yr soil site index CODE FILE SITE.INDEX.SIDE.CODE IS NOT USED BY OTHER ITEMS CODE MAP/REPORT MAP CODE DESCRIPTION LABEL SYMB --------- ------------ ---- -------------------------------------------------- E 100 YR SITE 0 Soil site index based on 100 year table W 50 YR SITE 0 Soil site index based on 50 year table------------------------------------------------------------------

This EnviroAtlas dataset addresses the tree buffer along heavily traveled roads. The roads are interstates, arterials, and collectors within the EnviroAtlas community boundary. In this community, tree cover is defined as Trees & Forest, and Woody Wetlands. Sufficient tree bufferage is defined as 25% coverage within the circular moving window with a radius of 14.5m at any given point along the roadway. There are potential negative health affects for those living in a location without a sufficient tree buffer. Those populations are estimated here using dasymetric data calculated for the EnviroAtlas. There are potential negative health effects for those living in a location without a sufficient tree buffer. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. This dataset was produced the US EPA to support research and online mapping activities related to EnviroAtlas. This dataset was produced the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

This EnviroAtlas dataset shows the total block group population and the percentage of the block group population that has little access to potential window views of trees at home. Having little potential access to window views of trees is defined as having no trees and forest land cover within 50 meters. The window views are considered "potential" because the procedure does not account for presence or directionality of windows in one's home. In this community, tree cover is defined as Trees & Forest, and Woody Wetlands. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

This EnviroAtlas dataset addresses the tree buffer along heavily traveled roads. The roads are interstates, arterials, and collectors within the EnviroAtlas community boundary. In this community, tree cover is defined as Trees & Forest, and Woody Wetlands. Sufficient tree bufferage is defined as 25% coverage within the circular moving window with a radius of 14.5m at any given point along the roadway. There are potential negative health affects for those living in a location without a sufficient tree buffer. Those populations are estimated here using dasymetric data calculated for the EnviroAtlas. There are potential negative health effects for those living in a location without a sufficient tree buffer. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

This EnviroAtlas dataset categorizes forest land cover into structural elements (e.g. core, edge, connector, etc.). In this community, tree cover is defined as Trees & Forest, and Woody Wetlands. Water was considered background (value 129) during the analysis to create this dataset, however it has been converted into value 10 to distinguish it from land area background. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

This EnviroAtlas dataset estimates tree cover along walkable roads. The road width is estimated for each road and percent tree cover is calculated in a 8.5 meter strip beginning at the estimated road edge. Percent tree cover is calculated for each block between road intersections. In this community, tree cover is defined as Trees & Forest, and Woody Wetlands. Tree cover provides valuable benefits to neighborhood residents and walkers by providing shade, improved aesthetics, and outdoor gathering spaces. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

This EnviroAtlas dataset estimates tree cover along walkable roads. The road width is estimated for each road and percent tree cover is calculated in a 8.5 meter strip beginning at the estimated road edge. Percent tree cover is calculated for each block between road intersections. In this community, tree cover is defined as Trees & Forest, and Woody Wetlands. Tree cover provides valuable benefits to neighborhood residents and walkers by providing shade, improved aesthetics, and outdoor gathering spaces. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. This dataset was produced the US EPA to support research and online mapping activities related to EnviroAtlas. This dataset was produced the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

Every summer for approximately the past seventy years, an insect and disease aerial detection survey has been flown of all the forested acres of Washington state (except where noted in the digital data by large 'NF' (not flown) areas). This survey is a cooperative effort between the U.S. Forest Service and the WADNR with two different flight observers each sketching a two mile swath out their side of the plane. The primary mission of the survey is to record recently killed and defoliated groups of trees throughout the state, and to continually build a historical record of these trends. The vast majority of damage found is caused by insect and disease damage agents; however, trees killed by early spring feeding of black bears or by events such as winter storms, fires, floods and landslides are recorded as well. Current defoliation can be detected as soon as the affected foliage changes color that year. However, whole tree mortality is not current since only flagged trees (i.e., trees which have a bright red, orange, or yellow foliage color) are recorded. This means that trees killed the year of the survey will not have changed color yet and so a one year lag time results. Since only this distinctive color or "signature" of the tree can be seen. It is an educated guess as to the causal agent. We therefore use ground surveys to reinforce our estimates as much as possible. Example: When bear damage is spotted while surveying, a polygon is drawn on the map of the size and location of the damage. The polygon is then labeled with the appropriate damage agent (i.e. Bear) and the number of trees affected rounded to the nearest five. No vertical data is recorded.

Using CSIRO’s Urban Monitor high resolution digital photography, vegetation height strata of endemic and exotic species has been calculated and reported as an area for each height strata of 0 – 3 m, 3 – 8 m, 8 – 15 m and 15+ m. The area of grass covered areas falling into the 0 – 50 cm range has also been calculated and recorded in square metres and percentage of total parcel area. Vegetation coverage greater than 3 metres in height has been deemed tree canopy. The canopies have been aggregated and reported as total canopy coverage in square metres, percentage of total parcel area and percentage range. Parcels to be analysed were sourced from the 2016 Integrated Land Information Database (ILID) and supplied to CSIRO by the Department of Planning, Lands and Heritage. The results were assembled into Urban Forest features where the Urban Monitor coverage was complete and published for the following years: 2009, 2014, 2016, 2018. Land parcels were assigned locational data (2016 ABS meshblocks, suburbs, local government authority (LGA) and planning sub-region) based on the parcel centroid. They were then attributed with the following land use categories: • Street Block: residential, commercial, industrial, hospital/medical, educational, and some agricultural and transport land uses • Parks: public parks, open space, private recreation grounds and State Forest • Roads: roads including road reserves • Other Infrastructure: rail, airports and utilities infrastructure • Other: land uses in transition that have not progressed sufficiently to be Street Blocks or do not conform to urban form • Rural: primary production land that does not fall in categories above • Water: ocean and other waterways, including reservoirs The vegetation height strata areas and total canopy coverage values were calculated for each land parcel, with percentage and range values based on total parcel area. Some parcels have incomplete coverage or are excluded from Urban Forest in some years. When undertaking comparative analysis between years, especially at an aggregated level (higher than parcel level), a filter must be applied using the In[YEAR] field. Failure to filter may result in higher levels of change being reported. For example, if undertaking percentage change in total canopy coverage between 2009 and 2018 at a LGA level, apply a filter on the 2018 data of In2009 = Yes first before aggregating to LGA level. This removes all parcels that were not represented in the 2009 data and allows a like-for-like comparison. NOTE: As locational attributes were populated based on the location of the parcel centroid, aggregating areas for larger administrative boundary units (Mesh block, Suburb, Local Government Authority or Sub-region) must be undertaken carefully as parcels sometimes cross boundaries. When calculating percentage cover for these boundaries, the total area based on the aggregated boundaries should be used, not the area based on the administrative boundary polygon.

For large areas, like Washington State, download as a file geodatabase. Large data sets like this one, for the State of Washington, may exceed the limits for downloading as shape files, excel files, or KML files. For areas less than a county, you may use the map to zoom to your area and download as shape file, excel or KML, if that format is desired.Every summer for approximately the past seventy years, an insect and disease aerial detection survey has been flown of all the forested acres of Washington state (except where noted in the digital data by large 'NF' (not flown) areas). This survey is a cooperative effort between the U.S. Forest Service and the WADNR with two different flight observers each sketching a two mile swath out their side of the plane. The primary mission of the survey is to record recently killed and defoliated groups of trees throughout the state, and to continually build a historical record of these trends. The vast majority of damage found is caused by insect and disease damage agents; however, trees killed by early spring feeding of black bears or by events such as winter storms, fires, floods and landslides are recorded as well. Current defoliation can be detected as soon as the affected foliage changes color that year. However, whole tree mortality is not current since only flagged trees (i.e., trees which have a bright red, orange, or yellow foliage color) are recorded. This means that trees killed the year of the survey will not have changed color yet and so a one year lag time results. Since only this distinctive color or "signature" of the tree can be seen. It is an educated guess as to the causal agent. We therefore use ground surveys to reinforce our estimates as much as possible. Example: When bear damage is spotted while surveying, a polygon is drawn on the map of the size and location of the damage. The polygon is then labeled with the appropriate damage agent (i.e. Bear) and the number of trees affected rounded to the nearest five. No vertical data is recorded.

This EnviroAtlas dataset describes the percentage of forested, vegetated, and impervious land within 15- and 50-meters of hydrologically connected streams, rivers, and other water bodies within the EnviroAtlas community area. In this community, tree cover is defined as Trees & Forest, and Woody Wetlands. and In this community, vegetated land is defined as Trees & Forest, Grass & Herbaceous, Woody Wetlands, and Emergent Wetlands. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

Every summer for approximately the past seventy years, an insect and disease aerial detection survey has been flown of all the forested acres of Washington state (except where noted in the digital data by large 'NF' (not flown) areas). This survey is a cooperative effort between the U.S. Forest Service and the WADNR with two different flight observers each sketching a two mile swath out their side of the plane. The primary mission of the survey is to record recently killed and defoliated groups of trees throughout the state, and to continually build a historical record of these trends. The vast majority of damage found is caused by insect and disease damage agents; however, trees killed by early spring feeding of black bears or by events such as winter storms, fires, floods and landslides are recorded as well. Current defoliation can be detected as soon as the affected foliage changes color that year. However, whole tree mortality is not current since only flagged trees (i.e., trees which have a bright red, orange, or yellow foliage color) are recorded. This means that trees killed the year of the survey will not have changed color yet and so a one year lag time results. Since only this distinctive color or "signature" of the tree can be seen. It is an educated guess as to the causal agent. We therefore use ground surveys to reinforce our estimates as much as possible. Example: When bear damage is spotted while surveying, a polygon is drawn on the map of the size and location of the damage. The polygon is then labeled with the appropriate damage agent (i.e. Bear) and the number of trees affected rounded to the nearest five. No vertical data is recorded.

Every summer for approximately the past seventy years, an insect and disease aerial detection survey has been flown of all the forested acres of Washington state (except where noted in the digital data by large 'NF' (not flown) areas). This survey is a cooperative effort between the U.S. Forest Service and the WADNR with two different flight observers each sketching a two mile swath out their side of the plane. The primary mission of the survey is to record recently killed and defoliated groups of trees throughout the state, and to continually build a historical record of these trends. The vast majority of damage found is caused by insect and disease damage agents; however, trees killed by early spring feeding of black bears or by events such as winter storms, fires, floods and landslides are recorded as well. Current defoliation can be detected as soon as the affected foliage changes color that year. However, whole tree mortality is not current since only flagged trees (i.e., trees which have a bright red, orange, or yellow foliage color) are recorded. This means that trees killed the year of the survey will not have changed color yet and so a one year lag time results. Since only this distinctive color or "signature" of the tree can be seen. It is an educated guess as to the causal agent. We therefore use ground surveys to reinforce our estimates as much as possible. Example: When bear damage is spotted while surveying, a polygon is drawn on the map of the size and location of the damage. The polygon is then labeled with the appropriate damage agent (i.e. Bear) and the number of trees affected rounded to the nearest five. No vertical data is recorded.

This EnviroAtlas dataset describes the breakdown of the land cover classes with each Census Block Group. In this commmunity, forest is defined as Trees & Forest, and Woody Wetlands. Green space is defined as Trees & Forest, Grass & Herbaceous, Agriculture, Woody Wetlands, and Emergent Wetlands. Agriculture is defined as Agriculture alone.Wetlands are defined as Woody Wetlands and Emergent Wetlands. This dataset also includes the area per capita for each block group for some land cover types. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

This EnviroAtlas dataset describes the percentage of a 51-m riparian buffer that is forested. In this community, tree cover is defined as Trees & Forest, and Woody Wetlands. There is a potential for decreased water quality in areas where the riparian buffer is less forested. The displayed line represents the center of the analyzed riparian buffer. The water bodies analyzed include hydrologically connected streams, rivers, connectors, reservoirs, lakes/ponds, ice masses, washes, locks, and rapids within the EnviroAtlas community area. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. This dataset was produced the US EPA to support research and online mapping activities related to EnviroAtlas. This dataset was produced the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).