Record of self-reported stewardship activity on DPR trees performed by members of the public. This dataset can be joined to the Forestry Tree Points dataset (https://data.cityofnewyork.us/Environment/Forestry-Tree-Points/hn5i-inap/data) by joining the TreeId from this dataset to OBJECTID from Forestry Tree Points.

Ecological benefits from street trees. Indicates the physical impact and monetary value of that impact for each tree. These values were calculated using i-Tree https://www.itreetools.org/

Current number of times a given tree has been marked as a favorite by registered users of the NYC Street Tree Map (nyc.gov/parks/treemap). This dataset can be joined to the Forestry Tree Points dataset (https://data.cityofnewyork.us/Environment/Forestry-Tree-Points/k5ta-2trh) by joining the TreeId to OBJECTID from Forestry Tree Points. Live data feed: https://www.nycgovparks.org/tree-map-feeds/favorite-trees.json

These maps are a digital representation of the individual tree species range maps of the "Atlas of the United States Trees" by Elbert L. Little, Jr. The atlas shows the natural distribution or range of the native tree species of North America. These coverages represent 3 volumes of the atlas.

Maps of the ranges of tree species in North America compiled by Elbert Little, of the U.S. Department of Agriculture, Forest Service, and others were digitized for use in USGS vegetation-climate modeling studies. These digital map files are available here for download.

The maps are available in ArcView® shapefile format. Geographic ranges are represented as polygons. There is one shapefile (with associated data files) for each tree species. At present, not all of the maps have been digitized, quality checked, and made available here, but the investigators plan to make most or all of the digitized maps available over time.

Urban Tree Canopy Assessment. This was created using the Urban Tree Canopy Syracuse 2010 (All Layers) file HERE.The data for this map was created using LIDAR and other spatial analysis tools to identify and measure tree canopy in the landscape. This was a collaboration between the US Forest Service Northern Research Station (USFS), the University of Vermont Spatial Laboratory, and SUNY ESF. Because the full map is too large to be viewed in ArcGIS Online, this has been reduced to a vector tile layer to allow it to be viewed online. To download and view the shapefiles and all of the layers, you can download the data HERE and view this in either ArcGIS Pro or QGIS.Data DictionaryDescription source  USDA Forest ServiceList of values  Value 1 Description Tree CanopyValue 2 Description Grass/ShrubValue 3 Description Bare SoilValue 4 Description WaterValue 5 Description BuildingsValue 6 Description Roads/RailroadsValue 7 Description Other PavedField Class Alias Class Data type String Width 20Geometric objects  Feature class name landcover_2010_syracusecity Object type  complex Object count 7ArcGIS Feature Class Properties Feature class name landcover_2010_syracusecity Feature type  Simple Geometry type Polygon Has topology FALSE Feature count 7 Spatial index TRUE Linear referencing  FALSEDistributionAvailable format  Name ShapefileTransfer options  Transfer size 163.805Description Downloadable DataFieldsDetails for object landcover_2010_syracusecityType Feature Class Row count  7 Definition  UTCField FIDAlias FID Data type OID Width  4 Precision 0 Scale 0Field descriptionInternal feature number.Description source ESRIDescription of valueSequential unique whole numbers that are automatically generated.Field ShapeAlias Shape Data type Geometry Width 0 Precision 0 Scale 0Field description Feature geometry.Description source  ESRIDescription of values Coordinates defining the features.Field CodeAlias Code Data type Number Width 4Overview Description  Metadata DetailsMetadata language  English Metadata character set utf8 - 8 bit UCS Transfer FormatScope of the data described by the metadata  dataset Scope name  datasetLast update 2011-06-02ArcGIS metadata properties Metadata format ArcGIS 1.0 Metadata style North American Profile of ISO19115 2003Created in ArcGIS for the item 2011-06-02 16:48:35 Last modified in ArcGIS for the item 2011-06-02 16:44:43Automatic updates Have been performed Yes Last update 2011-06-02 16:44:43Item location history  Item copied or moved 2011-06-02 16:48:35 From T:\TestSites\NY\Syracuse\Temp\landcover_2010_syracusecity To \T7500\F$\Export\LandCover_2010_SyracuseCity\landcover_2010_syracusecity

Directory of suggested edits to information in NYC Street Tree Map. Users can suggest a different species, diameter, or other notes about the tree. Edits are reviewed by a NYC Street Tree Map administrator before they are incorporated into the Map. This directory tracks the content and status of each suggested edit.

Date of Publication: 2015Name of Person Responsible: Alan HalterDate to be removed/updated: Updated every 5 years. Last updated on 11/24/2020.This map shows U.S. Census tracts (2010) containing tabular data related to community forestry priorities determined by the Community Tree Preservation Division’s Urban Forest Program. Prioritization is determined through the attribute field, “PRIORITY_SCORE_2020” aka the “Priority Score.” This score combines nine measures normalized and summarized into four broad categories outlined below. The score is aggregated at the neighborhood (U.S. Census tract) level. Scores can range from 0 to 100 with higher scores meaning a higher need for community forestry activities to achieve more equitable canopy distribution.Layers in this map:Community Tree Priorities 2020 - the most recent Community Tree Priorities layer for 2020 (formerly Planting Prioritization). Colors in red are areas we want to see more tree planting happen.Community Tree Priorities 2015 - the Community Tree Priorities layer for 2015 (formerly Planting Prioritization). This is a deprecated layer and is for historical reference only.City Funded Tree Planting (last 3 years) - address locations where trees were distributed through the NeighborWoods, Ready Set Plant, and Austin Community Trees programs. Data are filtered to show only the last three years of distribution.Zipcodes - zipcode boundaries for reference.An additional gray layer is added to mask areas outside the City of Austin's city limits.

Stewardship groups involved with street trees. This data indicates how many and which type of activities stewardship groups have done.

Download this data or get more information. This data publication contains 2015 high-resolution land cover data for each of the 105 counties within Kansas. These data are a digital representation of land cover derived from 1-meter aerial imagery from the National Agriculture Imagery Program (NAIP). There is a separate file for each county. Data are intended for use in rural areas and therefore do not include land cover in cities and towns. Land cover classes (tree cover, other land cover, water, or city/town) were mapped using an object-based image analysis approach and supervised classification.

This database contains distribution maps of 135 eastern U.S. tree species based on Importance Values (IV) derived from Forest Inventory Analysis (FIA) data and a geographical information system (GIS) database of Elbert L. Jr. Little's published ranges. Between 1971 and 1977, Elbert L. Jr. Little, Chief Dendrologist with the U.S. Forest Service, published a series of maps of tree species ranges based on botanical lists, forest surveys, field notes ad herbarium specimens. These published maps have become the standard reference for most U.S. and Canadian tree species ranges.

The USDA Forest Service's FIA units are charged with periodically assessing the extent, timber potential, and health of the trees in the United States. The investigators have created a spatial database of individual species IV based on the number of stems and basal area of understory and overstory trees using FIA data from more than 100,000 plots in the eastern United States. The IV ranges from 0 to 100 and gives a measure of the abundance of the species. (See the investigator's Climate Change Atlas for 80 Forest Tree Species of the Eastern United States at [http://www.fs.fed.us/ne/delaware/atlas/web_atlas.html] for details). The investigators have aggregated the plot-level IV to 20km cells.

Both sets of maps (Little's ranges and IV based on FIA data) are available for download. The Little's range maps (little.shp) are vector based and are provided as shape files. These maps can span United States or United States and Canada in extent depending on the species. The Importance Value (IV) are raster maps (asciigrid) in asciigrid format. This is an ascii file with header information that can be used to import data into ArcInfo GRID or ArcView's Spatial Analyst GIS software. The spatial resolution is 20km. These raster maps span the eastern U.S. (east of the 100th meridian) in extent.

This shapefile is the dataset that underlies the historic MillionTreesNYC Adopt-a-Tree web mapping application. For up to date stewardship data see https://data.cityofnewyork.us/Environment/NYC-Street-Tree-Map-Stewardship-Activity/rnnj-5mmi.

Maps of the number, size, and species of trees in forests across the western United States are desirable for many applications such as estimating terrestrial carbon resources, predicting tree mortality following wildfires, and for forest inventory. However, detailed mapping of trees for large areas is not feasible with current technologies, but statistical methods for matching the forest plot data with biophysical characteristics of the landscape offer a practical means to populate landscapes with a limited set of forest plot inventory data. We used a modified random forests approach with Landscape Fire and Resource Management Planning Tools (LANDFIRE) vegetation and biophysical predictors as the target data, to which we imputed plot data collected by the USDA Forest Service’s Forest Inventory Analysis (FIA) to the landscape at 30-meter (m) grid resolution (Riley et al. 2016). This method imputes the plot with the best statistical match, according to a “forest” of decision trees, to each pixel of gridded landscape data. In this work, we used the LANDFIRE data set as the gridded target data because it is publicly available, offers seamless coverage of variables needed for fire models, and is consistent with other data sets, including burn probabilities and flame length probabilities generated for the continental United States. The main output of this project (the GeoTIFF available in this data publication) is a map of imputed plot identifiers at 30×30 m spatial resolution for the western United States for landscape conditions circa 2009. The map of plot identifiers can be linked to the FIA databases available through the FIA DataMart or to the ACCDB/CSV files included in this data publication to produce tree-level maps or to map other plot attributes. These ACCDB/CSV files also contain attributes regarding the FIA PLOT CN (a unique identifier for each time a plot is measured), the inventory year, the state code and abbreviation, the unit code, the county code, the plot number, the subplot number, the tree record number, and for each tree: the status (live or dead), species, diameter, height, actual height (where broken), crown ratio, number of trees per acre, and a unique identifier for each tree and tree visit. Application of the dataset to research questions other than those related to aboveground biomass and carbon should be investigated by the researcher before proceeding. The dataset may be suitable for other applications and for use across various scales (stand, landscape, and region), however, the researcher should test the dataset's applicability to a particular research question before proceeding.Geospatial data describing tree species or forest structure are required for many analyses and models of forest landscape dynamics. Forest data must have resolution and continuity sufficient to reflect site gradients in mountainous terrain and stand boundaries imposed by historical events, such as wildland fire and timber harvest. Such detailed forest structure data are not available for large areas of public and private lands in the United States, which rely on forest inventory at fixed plot locations at sparse densities. While direct sampling technologies such as light detection and ranging (LiDAR) may eventually make broad coverage of detailed forest inventory feasible, no such data sets at the scale of the western United States are currently available.When linking the tree list raster (“CN_text” field) to the FIA data via the plot CN field (“CN” in the “PLOT” table and “PLT_CN” in other tables), note that this field is unique to a single visit to a plot. The raster contains a “Value” field, which also appears in the ACCDB/CSV files in the “tl_id” field in order to facilitate this linkage. All plot CNs utilized in this analysis were single condition, 100% forested, physically located in the Rocky Mountain Research Station (RMRS) and Pacific Northwest Research Station (PNW) obtained from FIA in December of 2012.

Original metadata date was 01/03/2018. Minor metadata updates made on 04/30/2019.

Open the Data Resource: https://www.treeequityscore.org/map Trees are critical urban infrastructure that are essential to public health and well-being. Tree Equity Score was created to help address damaging environmental inequities by prioritizing human-centered investment in areas with the greatest need. It measures how well the benefits of trees are reaching communities living on low-incomes, communities of color and others disproportionately impacted by extreme heat and other environmental hazards. Scores are calculated at the neighborhood (Census block group) level, and range from 0-100. The lower the score, the greater priority for tree planting. A score of 100 means the neighborhood has enough trees. Tree Equity Score covers every urban Census block group in the United States, including Hawaii and Alaska. Data for Puerto Rico and the U.S. Virgin Islands are due for release in 2024.

The Urban Community Forestry Tree Inventory Map is used to VIEW inventoried tree locations. This map is developed in AGO's Classic Map Viewer and scripts for attributes have been optimized for the web appbuilder map viewer. Trees that have been inventoried and have tree health and tree maintenance surveys are viewable in this map.

FIA Modeled Abundance:�This dataset portrays the live tree mean basal area (square feet per acre) of the species across the contiguous United States. The underlying data publication contains raster maps of live tree basal area for each tree species along with corresponding assessment data. An efficient approach for mapping multiple individual tree species over large spatial domains was used to develop these raster datasets. The method integrates vegetation phenology derived from MODIS imagery and raster data describing relevant environmental parameters with extensive field plot data of tree species basal area to create maps of tree species abundance and distribution at a 250-meter (m) pixel size for the contiguous United States. The approach uses the modeling techniques of k-nearest neighbors and canonical correspondence analysis, where model predictions are calculated using a weighting of nearest neighbors based on proximity in a feature space derived from the model. The approach also utilizes a stratification derived from the 2001 National Land-Cover Database tree canopy cover layer.�This data depicts current species abundance and distribution across the contiguous United States, modeled by using FIA field plot data. Although the absolute values associated with the maps differ from species to species, the highest values within each map are always associated with darker colors. The Little's Range Boundaries show the historical tree species ranges across North America. This is a digital representation of maps by Elbert L. Little, Jr., published between 1971 and 1977. These maps were based on botanical lists, forest surveys, field notes and herbarium specimens.Forest-type Groups:This dataset portrays the forest type group. Each group is a subset of the National Forest Type dataset which portrays 28 forest type groups across the contiguous United States. These data were derived from MODIS composite images from the 2002 and 2003 growing seasons in combination with nearly 100 other geospatial data layers, including elevation, slope, aspect, ecoregions, and PRISM climate data.Harvest Growth:This data shows the percentage of timber that is harvested when compared to the total live volume, at a county-by-county level. Timber volume in forests is constantly in flux, and harvest plays an important role in shaping forests. While most counties have some timber harvest, harvest volumes represent low percentages of standing timber volume.Carbon Harvest:The Carbon Harvest raster dataset represents Mg of annual pulpwood harvested (carbon) by county, derived from the Forest Inventory Analysis in 2016.

This raster layer trees per acre information for the Tongass project area, prepared for the Tongass National Forest to provide up-to-date and more complete information about vegetative communities, structure, and patterns across the Forest. Approximately 26 million acres, 18.2 million acres of which are terrestrial, including inland waterbodies and rivers, were mapped through a partnership between the Geospatial Office (GO), Tongass National Forest, and the Alaska Regional Office. The Tongass National Forest and their partners prepared the regional classification system, identified the desired map units (map classes) and provided general project guidance. GO provided project support and expertise in vegetation mapping.The modeling units (mapping polygons) were characterized with the following vegetation attributes: 1) map group, 2) vegetation type, 3) tree canopy cover percent, 4) tree canopy cover class, 5) tree size class, 6) change percent, 7) change year, 8) biomass for trees ≥ 2” dbh, 9) crown competition factor, 10) gross board feet (GBF) for trees ≥ 9” dbh, 11) quadratic mean diameter (QMD) for trees ≥ 2” dbh, 12) quadratic mean diameter for trees ≥ 9” dbh, 13) rumple index, 14) stand density index (SDI) for trees ≥ 9” dbh, 15) trees per acre (TPA) for trees ≥ 1’ tall, 16) trees per acre for trees ≥ 6” diameter at breast height (dbh), and 17) acres. The minimum map feature depicted on the map is 0.25 acres. This map product was generated using imagery primarily acquired between 2020 – 2024, reference information collected in the summers of 2023 – 2024, and LiDAR data flown in 2015. Every effort was taken to ensure consistency in the final products and these can be considered indicative of the existing vegetation conditions found within the project boundary during the growing season of 2024. All map products were designed according to National Forest Service vegetation mapping standards and are stored in federal databases. For more detailed information on mapping methodology please see the Tongass-Wide Vegetation Mapping Report: Tongass-Wide Vegetation Mapping Report (in progress): Bellante, G.; Dangerfield, C.; Foss, J.; Lund, A.; Caster, A.; Mohatt, K.; Homan, K.; Wittwer, D.; Johnson, T.; Goetz, W.; Moody, R.; Vernier, M.; Hemingway, B.; Achtenhagen, A.; Ryerson, D.; Megown, K.. 2025. Tongass National Forest Existing Vegetation Map. Salt Lake City, UT. In progress.

The National Land Cover Database 2011 (NLCD2011) percent tree canopy cover (TCC 2011) layer was produced through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium (www.mrlc.gov). The MRLC Consortium is a partnership of federal agencies, consisting of the U.S. Geological Survey, the National Oceanic and Atmospheric Administration, the U.S. Environmental Protection Agency, the U.S. Department of Agriculture (USDA) National Agricultural Statistics Service, the U.S. Forest Service, the National Park Service, the U.S. Fish and Wildlife Service, the Bureau of Land Management, NASA, and the U.S. Army Corps of Engineers. One of the primary goals of the project was to generate a current, consistent, and seamless national land cover, percent tree canopy cover, and percent impervious cover at medium spatial resolution. TCC 2011 is the NLCD tree canopy cover dataset at medium spatial resolution (30 m). It was produced by the USDA Forest Service Remote Sensing Applications Center (RSAC). The TCC 2011 dataset has two layers: percent tree canopy cover and standard error. For the tree canopy cover layer, the pixel values range from 0 to 100 percent. For the standard error layer, the pixel values range from 0 to 45 percent. The standard error represents the model uncertainty associated with the corresponding pixel in the tree canopy cover layer. The tree canopy cover layer was produced using a Random Forests' regression algorithm and the standard error layer was calculated from the variance of the canopy cover estimates from the random forest regression trees.This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: ISO-19139 metadata ArcGIS Hub Dataset ArcGIS GeoService For complete information, please visit https://data.gov.

City of Austin Open Data Terms of Use https://data.austintexas.gov/stories/s/ranj-cccq The City of Austin’s Community Tree Priority Map (formerly Planting Prioritization) serves as a decision support tool to determine where to focus forestry activities in Austin, Texas. This map shows U.S. Census tracts (2010) containing tabular data related to community forestry priorities determined by the Community Tree Preservation Division’s Urban Forest Program. Prioritization is determined through the priority score. This score combines nine measures normalized and summarized into four broad categories. The score is aggregated at the neighborhood (U.S. Census tract) level. Scores can range from 0 to 100 with higher scores meaning a higher need for community forestry activities to achieve more equitable canopy distribution. Finally, the priority level provides a categorical representation of the data for a simplified view. Priority Score = ( Σ Natural Environment + Σ Social Vulnerability + Σ Community Investment + Σ Health & Well-Being ) / 4 This map was updated in 2020. Minor updates are made as-needed with a review and data update scheduled for 2025 (every 5 years). Ultimately, this map is used to aggregate Urban Forest Grant/Portal projects and tree planting/distribution data to assess program performance. This dataset is intended to be downloaded as a GIS Shapefile but may also be viewed in Excel. It's also available in ArcGIS Online at https://austin.maps.arcgis.com/home/item.html?id=7d7c5260e60c4f8ab811d2c5fda6c40f

The National Insect and Disease Risk map identifies areas with risk of significant tree mortality due to insects and plant diseases. The layer identifies lands in three classes: areas with risk of tree mortality from insects and disease between 2013 and 2027, areas with lower tree mortality risk, and areas that were formerly at risk but are no longer at risk due to disturbance (human or natural) between 2012 and 2018. Areas with risk of tree mortality are defined as places where at least 25% of standing live basal area greater than one inch in diameter will die over a 15-year time frame (2013 to 2027) due to insects and diseases.The National Insect and Disease Risk map, produced by the US Forest Service FHAAST, is part of a nationwide strategic assessment of potential hazard for tree mortality due to major forest insects and diseases. Dataset Summary Phenomenon Mapped: Risk of tree mortality due to insects and diseaseUnits: MetersCell Size: 30 meters in Hawaii and 240 meters in Alaska and the Contiguous USSource Type: DiscretePixel Type: 2-bit unsigned integerData Coordinate System: NAD 1983 Albers (Contiguous US), WGS 1984 Albers (Alaska), Hawaii Albers (Hawaii)Mosaic Projection: North America Albers Equal Area ConicExtent: Alaska, Hawaii, and the Contiguous United States Source: National Insect Disease Risk MapPublication Date: 2018ArcGIS Server URL: https://landscape11.arcgis.com/arcgis/This layer was created from the 2018 version of the National Insect Disease Risk Map.What can you do with this Layer? This layer is suitable for both visualization and analysis across the ArcGIS system. This layer can be combined with your data and other layers from the ArcGIS Living Atlas of the World in ArcGIS Online and ArcGIS Pro to create powerful web maps that can be used alone or in a story map or other application.Because this layer is part of the ArcGIS Living Atlas of the World it is easy to add to your map:In ArcGIS Online you can add this layer to a map by selecting Add then Browse Living Atlas Layers. A window will open. Type "insects and disease" in the search box and browse to the layer. Select the layer then click Add to Map.In ArcGIS Pro open a map and select Add Data from the Map Tab. Select Data at the top of the drop down menu. The Add Data dialog box will open on the left side of the box, expand Portal if necessary, then select Living Atlas. Type "insects and disease" in the search box, browse to the layer then click OK.In ArcGIS Pro you can use raster functions to create your own custom extracts of the data. Imagery layers provide fast, powerful inputs to geoprocessing tools, models, or Python scripts in Pro. For example, Zonal Statistics as Table tool can be used to summarize risk of tree mortality across several watersheds, counties, or other areas that you may be interested in such as areas near homes.In ArcGIS Online you can change then layer's symbology in the image display control, set the layer's transparency, and control the visible scale range.The ArcGIS Living Atlas of the World provides an easy way to explore many other beautiful and authoritative maps on hundreds of topics like this one.