Urban Tree Canopy 2016

Published by NashvilleOpenData

<div><p>The results, based on 2016 imagery from the USDA’s National Agriculture Imagery Program (NAIP).  This study utilized modern machine learning techniques to create tree canopy data that are reproducible and allow for a more uniform comparison in future tree canopy analysis.  LiDAR data was used to assist the classification model by applying a 10ft threshold to the LiDAR-derived canopy, chosen for its effectiveness in identifying young trees. The primary use of LiDAR was to supplement the AI-canopy by capturing small trees. Using this supplemental data, anything below 10ft was categorized as herbaceous or shrubs.&lt;o:p&gt;&lt;/o:p&gt;</p></div><div><br /></div><div><div><font size='3'>Source Link: </font><a href='https://www.nashville.gov/departments/water/stormwater/tree-information/urban-tree-canopy' target='_blank' rel='nofollow ugc noopener noreferrer'>https://www.nashville.gov/departments/water/stormwater/tree-information/urban-tree-canopy</a><font size='3'><br /></font><div><font size='3'>Metadata Document: </font><a href='https://nashville.maps.arcgis.com/sharing/rest/content/items/de010bd12a2c4c09b0fef800d48cbe54/data' target='_blank' rel='nofollow ugc noopener noreferrer'>Urban Tree Canopy 2016 Metadata.pdf</a></div></div><div><font size='3'>Contact Data Owner: </font><a href='mailto:opendata@nashville.gov?subject=Urban Tree Canopy 2016' target='_blank' rel='nofollow ugc noopener noreferrer'>opendata@nashville.gov</a></div></div>