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This data set is a combination of Urban Forestry Division managed trees and tree locations from 2023, and estimated trees modeled using an automated feature extraction process applied to 2022 LiDAR data. All trees were then processed using i-Tree eco software to estimate the environmental benefits of trees. |
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This data set is a combination of Urban Forestry Division managed trees and tree locations from 2023, and estimated trees modeled using an automated feature extraction process applied to 2022 LiDAR data. All trees were then processed using i-Tree eco software to estimate the environmental benefits of trees. |
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District Department of Transportation |
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<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>DC 2022 LiDAR was used and processed using the “Extract Trees using Cluster Analysis” script which is included as part of Esri’s 3D Basemap solution. All LiDAR-derived trees within 2 meters of a Urban Forestry Division tree were removed as being duplicates.</SPAN></P><P><SPAN>Tree diameter (DBH, in inches) was estimated for the LiDAR-derived trees from calculated tree height (in feet) based on the equation: DBH = 0.4003*height - 1.9557. This equation was derived from a statistical analysis of a detailed park inventory tree data set and has an R^2 = 0.7418.</SPAN></P><P><SPAN>Extreme outliers were also modified, with any DBH larger than 80 inches being converted to a DBH of 80 inches.</SPAN></P><P><SPAN>The combined data set was processed using the USDA Forest Service i-Tree eco software, where structure and environmental benefits were estimated.</SPAN></P></DIV></DIV></DIV> |
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<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>This work is licensed under a </SPAN><A href="https://creativecommons.org:443/licenses/by/4.0/" STYLE="text-decoration:underline;"><SPAN>Creative Commons Attribution 4.0 International License</SPAN></A><SPAN>.</SPAN></P></DIV></DIV></DIV> |
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Tree Benefits (2023) |
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["DC trees","estimate trees","extracted trees","environmental benefits","urban forestry","washington","dc"] |
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en-US |
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50000 |
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