Relative % Change

This data layer references data from a high-resolution tree canopy change-detection layer for Seattle, Washington. Tree canopy change was mapped by using remotely sensed data from two time periods (2016 and 2021). Tree canopy was assigned to three classes: 1) no change, 2) gain, and 3) loss. No change represents tree canopy that remained the same from one time period to the next. Gain represents tree canopy that increased or was newly added, from one time period to the next. Loss represents the tree canopy that was removed from one time period to the next. Mapping was carried out using an approach that integrated automated feature extraction with manual edits. Care was taken to ensure that changes to the tree canopy were due to actual change in the land cover as opposed to differences in the remotely sensed data stemming from lighting conditions or image parallax. Direct comparison was possible because land-cover maps from both time periods were created using object-based image analysis (OBIA) and included similar source datasets (LiDAR-derived surface models, multispectral imagery, and thematic GIS inputs). OBIA systems work by grouping pixels into meaningful objects based on their spectral and spatial properties, while taking into account boundaries imposed by existing vector datasets. Within the OBIA environment a rule-based expert system was designed to effectively mimic the process of manual image analysis by incorporating the elements of image interpretation (color/tone, texture, pattern, location, size, and shape) into the classification process. A series of morphological procedures were employed to ensure that the end product is both accurate and cartographically pleasing. No accuracy assessment was conducted, but the dataset was subjected to manual review and correction.University of Vermont Spatial Analysis LaboratoryThis dataset consists of hexagons 50-acres in area, or several city blocks. The dataset covers the following tree canopy categories:Existing tree canopy percentPossible tree canopy - vegetation percentRelative percent changeAbsolute percent changeAverage maximum afternoon temperature (F)Tree canopy percentage & average afternoon temperature (F)For more information, please see theĀ 2021 Tree Canopy Assessment.

Data and Resources

Additional Info

Field Value
Source https://cos-data.seattle.gov/resource/juei-63hu
Author Allen Grissom
Last Updated July 22, 2025, 19:42 (UTC)
Created July 22, 2025, 19:42 (UTC)
Contact Email mailto:mapgis.mapgis@seattle.gov
Contact Name SeattleData
Geographic Coverage -122.4561,47.4725,-122.2233,47.7370
Homepage https://data-seattlecitygis.opendata.arcgis.com/datasets/SeattleCityGIS::relative-change-1
Issued 2023-06-29T21:52:09.000Z
Last Update 2023-06-29T21:55:13.596Z
License <div style='text-align:Left; font-size:12pt;'><p style='margin-top:0px; margin-bottom:1.5rem; font-family:&quot;Avenir Next W01&quot;, &quot;Avenir Next W00&quot;, &quot;Avenir Next&quot;, Avenir, &quot;Helvetica Neue&quot;, sans-serif; font-size:12pt;'>The University of Vermont makes no representations of any kind, including but not limited to the warranties of merchantability or fitness for a particular use, nor are any such warranties to be implied with respect to the data. Although every effort has been made to assure the accuracy of features and their attributes, the University of Vermont is not accountable for any errors or misuse of the data. The data should be used for general mapping purposes only.</p><p style='margin-top:0px; margin-bottom:1.5rem; font-family:&quot;Avenir Next W01&quot;, &quot;Avenir Next W00&quot;, &quot;Avenir Next&quot;, Avenir, &quot;Helvetica Neue&quot;, sans-serif;'>The City of Seattle makes no representation or warranty as to its accuracy, and in particular, its accuracy as to labeling, dimensions, contours, property boundaries, or placement or location of any map feature thereof.</p></div>
Public Access Level public
Publisher City of Seattle ArcGIS Online
Theme geospatial
Unique Identifier https://www.arcgis.com/home/item.html?id=7f3c4b7be2cd46719d9691f35f362573&sublayer=3
harvest_object_id 14a1affe-72aa-485e-9978-4480021574cf
harvest_source_id 5365fd4f-4dee-4a64-8b1c-c2025205baa9
harvest_source_title seattle