Maps - References
i-Tree Landscape offers users a wide variety of data and map layers.
More information can be found in the Landscape section of the i-Tree Tools Archives.
The references are grouped in separate pages.
Maps Layer Metadata¶
- US Census Block Groups¶
- Administrative boundary data displaying the 2010 block group boundaries. Block groups are clusters of blocks within the same census tract. Block groups generally contain between 600 and 3,000 people.
- US Census Places¶
- Administrative boundary data displaying the 2010 place boundaries. Places include both incorporated places and census designated places. Incorporated places are established for the provision of services for a concentration of places, whereas census designated places are not legally incorporated under state laws.
- US 111th Congressional Districts¶
- Administrative boundary data displaying the 2010 congressional district boundaries for the 111th United State's Congress. Congressional districts are the areas from which people are elected to the U.S. House of Representatives. Each area is roughly equal in population to the other congressional districts in the same state.
- US Counties¶
- Administrative boundary data displaying the 2010 county boundaries. Counties and county equivalents are the primary legal divisions of most U.S. states.
- US States¶
- Administrative boundary data displaying the 2010 state boundaries.
- US National Forests¶
- A depiction of the boundary that encompasses a National Forest.
- US Ranger Districts¶
- A depiction of the boundary that encompasses a Ranger District.
- CFLR Boundaries¶
- Depicts the boundaries for the Collaborative-Forest Landscape Restoration (CFLR) and High Priority Restoration (HPR) projects.
- Watershed (HUC12)¶
- Depicts the geographic division of the United States into hydrologic units based on watershed boundaries. These divisions are sixth-level classifications identified by a 12-digit unique hydrologic unit code (HUC).
Canopy & Land¶
- Tree Canopy¶
- Tree cover estimates are derived directly from 2011 National Land Cover Data (NLCD) or 2001 NLCD data in Alaska, Hawaii and Puerto Rico (as 2011 data are not available). These data estimate percent tree cover using satellite data with a 30 meter resolution (www.mrlc.gov). For areas where high resolution land cover data are available, that dataset will be displayed by default.
- Impervious cover estimates are derived directly from 2011 National Land Cover Data (NLCD) or 2001 NLCD data in Hawaii and Puerto Rico (as 2011 data are not available). These data estimate percent impervious cover using satellite data with a 30 meter resolution (www.mrlc.gov). For areas where high resolution land cover data are available, that dataset will be displayed by default.
- Plantable Space¶
- Available planting space estimates are derived from National Land Cover Data (NLCD) where plantable space = land area - (canopy + impervious).
- Total Basal Area¶
- Forest Basal Area describes the extent to which an area is occupied by trees by estimating the relative size and density of tree trunks. Basal area is usually expressed in square feet per acre (ft2/acre), and can act as an indicator of forest volume and growth. No data means Basal Area was not measured at that location. The data can be found at the USFS Remote Sensing & Image Analysis site.
- Forest Type¶
- The FIA (Forest Inventory and Analysis) Forest Type data shows the extent, distribution, and composition (species type/group) of forested areas in the United States. The data can be found at the USFS FIA page National Forest Type Dataset.
- Land Cover¶
- 2011 and 2001 National Land Cover Database (NLCD) provides a synoptic nationwide classification of land cover into 16 classes at a spatial resolution of 30 meters.
Homer, C.G.; Dewitz, J.A.; Yang, L.; Jin, S.; Danielson, P.; Xian, G.; Coulston, J.; Herold, N.D.; Wickham, J.D.; Megown, K., 2015, Completion of the 2011 National Land Cover Database for the conterminous United States – Representing a decade of land cover change information. Photogrammetric Engineering and Remote Sensing. 81 (5): 345-354.
- Wildfire Potential¶
- A map classified by the relative potential for wildfire that would be difficult for suppression resources to contain. The intended use of this layer is to help inform evaluations of wildfire risk or prioritization of fuels management needs across large spatial scales. This map layer was derived by the U.S. Forest Service by classifying the Wildfire Hazard Potential (WHP) continuous dataset values. The process entailed converting the WHP values to integers, evaluating the statistical distribution of WHP values and then classifying them into fire classes: very high, high, moderate, low, very low. WHP ranges for each class are unknown. The non-burnable and water values were incorporated from the LANDFIRE FBFM40 layer to produce the final classified WFP. (source)
- Hardiness Zones¶
- Hardiness zones are based on the average annual extreme minimum temperature during a 30-year period. The zones can be used to determine the threshold at which certain plantings can thrive. The dataset is available here: http://planthardiness.ars.usda.gov.
- Forest Pests¶
- Disease and Insects
- Determined by whether or not the range of known pests appears within the boundary of a location area. Pest range maps are derived from the Forest Health Technology Enterprise Team (FHTET) and can be viewed at the Insect and Disease Detection Survey Data Explorer.
- Air Quality¶
- Pollution concentrations are estimated for ozone (O3) and particulate matter less than 2.5 microns (PM2.5) and derived from the U.S. Environmental Protection Agency’s (EPA) Downscaler Model. Average and maximum values are estimated from the pollution concentration for all days in 2008. (source)
- EPA Non-Attainment Areas¶
- Indicates whether an area has received a status of Non-Attainment from the Environmental Protection Agency with respect to air quality standards for the following pollutants:
- 8-Hour Ozone (2008 Standard)
- PM2.5 (2012 Standard)
- Sulfur Dioxide (2010 Standard)
- Carbon Monoxide (1971 Standard)
- PM10 (1987 Standard)
- Nitrogen Dioxide (1971 Standard)
Information regarding standards and non-attainment evaluations can be found here: https://www.epa.gov/green-book.
- UV Index¶
- Ultraviolet (UV) index values displayed as the average UV index at solar noon for all days between 2008 and 2012 and the maximum UV index at solar noon for all days between 2008 and 2012. The UV index scale was developed by the World Health Organization to more easily communicate daily levels of UV radiation and alert people to when protection from overexposure is needed most. (source)
- Land Surface Temperature¶
- Determining the difference between localized surface temperatures and regional mean temperatures can help qualify the impacts of land use. Generally speaking, areas with more impervious surface tend to be warmer than average, while areas with more canopy cover tend to be cooler than average. Land Surface Temperature data is derived from Landsat-8 Thermal Infrared Sensor Data. Temperature values are the difference from the median surface temperature for each Landsat scene available through landsat.usgs. Temperature differences were estimated for the United States based on data and standard procedures from the literature as described in the Data Land Surface Temperature section.
- Land Surface Temperature Hotspots Methods¶
- To illustrate areas with relatively warm land surface temperatures (LST) and large amounts of growing space (to potentially cool the environment) or high human populations (areas with greatest human health risks to warm temperatures), two temperature indices were produced. In each index, the LST value used is the calculated LST difference from the Landsat mean as described above.
- Google Streets¶
- Street map provided by Google Maps.
- Google Aerial¶
- Aerial imagery provided by Google Maps.
- Bing Streets¶
- Street map provided by Microsoft Bing.
- Bing Aerial¶
- Aerial imagery provided by Microsoft Bing.
- Open Street Map¶
- Street map provided by Open Street Map.
- White Canvas¶
- White base layer with no map data.
- Black Canvas¶
- Black base layer with no map data.
- Hirabayashi, S., 2015. i-Tree Eco Precipitation Interception Model Descriptions. http://www.itreetools.org/eco/resources/iTree_Eco_Precipitation_Interception_Model_Descriptions.pdf (accessed April 2015).
- Hirabayashi, S., Endreny, T.A., 2015. Surface and Upper Weather Pre-processor for i-Tree Eco and Hydro. http://www.itreetools.org/eco/resources/Surface_weather_and_upper_air_preprocessor_description.pdf (accessed April 2015).
- Hirabayashi, S., D.J. Nowak. 2015. i-Tree Eco United States County-Based Hydrologic Estimates and Estimates of Species Differentiation
- Technical Support Document: Technical Update of the Social Cost of Carbon for Regulatory Impact Analysis Under Executive Order 12866. Interagency Working Group on Social Cost of Carbon, United States Government. 2016. (accessed October 2018). https://www.epa.gov/sites/production/files/2016-12/documents/sc_co2_tsd_august_2016.pdf
- Nowak, D.J., E.J. Greenfield. 2010. Evaluating the National Land Cover Database tree canopy and impervious cover estimates across the conterminous United States: A comparison with photo-interpreted estimates. Environmental Management. 46: 378-390.
- Nowak, D.J., E.J. Greenfield, R. Hoehn, and E. LaPoint. 2013. Carbon storage and sequestration by trees in urban and community areas of the United States. Environmental Pollution. 178: 229-236.
- Nowak, D.J. S. Hirabayashi, A. Bodine and E.J. Greenfield. 2014. Tree and forest effects on air quality and human health in the United States. Environmental Pollution 193:119-129
- U.S. Environmental Protection Agency. 2015. Report on the Environment: Land Cover http://cfpub.epa.gov/roe/indicator_pdf.cfm?i=49 (accessed October 2015).
- Sobrino, J.A., N. Raissouni, Z.L. Li. 2001. A Comparative Study of Land Surface Emissivity Retrieval from NOAA Data. Remote Sensing of Environment, 75(2): 256-266. http://www.sciencedirect.com/science/article/pii/S0034425700001711 (accessed June 2017).
- USGS. 2017. Using the USGS Landsat 8 Product. https://landsat.usgs.gov/using-usgs-landsat-8-product (accessed June 2017).
- Weng, Q., D. Lu, J. Schubring. 2004. Estimation of land surface temperature–vegetation abundance relationship for urban heat island studies. Remote Sensing of Environment, 89(4): 467-483. http://www.sciencedirect.com/science/article/pii/S0034425703003390 (accessed June 2017).
- Whalen, K.C. 2017. A map system to disseminate national science on forests for the creation of regional tree planting prioritization plans. Electronic Thesis. Kent State University. http://rave.ohiolink.edu/etdc/view?acc_num=kent1510664712622379