Growing Shade in Gresham

Combining environmental and social data to help identify where trees are most needed in Gresham, Oregon.

Presented by the City of Gresham and CAPA Strategies

Introduction

In Gresham, the degree of canopy cover − that is, where trees are present and where they are not − impacts the health and well-being of our residents, environment and infrastructure. Trees provide an important cooling effect through shade and evapotranspiration during the summertime. In winter, trees help reduce excess stormwater by absorbing precipitation and groundwater. Their aesthetic value in our neighborhoods is well appreciated. However, not all of our neighbors receive the same degree of benefit from trees, due to a lack of existing canopy cover.

To address this problem, the City of Gresham has worked with local firm CAPA Strategies to develop a mapping tool that can identify and prioritize locations in most need of trees. This tool, called Growing Shade, allows users to filter environmental and social factors with an easy-to-use interface. The instructional guide here will show you how to best use the tool and its various functionalities. Check out the video below to learn more!

Gresham Growing Shade

Now that you've watched the tutorial video, click the link below to use the Growing Shade tool.

Data Sources

Geographies

Census block group polygon data are downloaded from 2020 TIGER/Line Shapefiles  here . Taxlots are download from Metro RLIS  here .

Social

Demographic data are sourced from the Census using ACS 5-Year estimates in 2020  here .

Heat

Heat data was downloaded from OSF for East Multnomah County :  https://osf.io/jg6nk/ 

Canopy

Canopy data are derived using LiDAR data that are retrieved from DOGAMI  here . Height and reflectance are used to determine the canopy outlines and subsequently generated polygons.

Process

Canopy data are derived from  LiDAR (light detection and ranging)  datasets. After extensive processing and error-correction, the resulting dataset is a group of polygon features that represent the crowns, or canopy, of trees in Gresham. The area of the tree canopy is then subtracted from each geography (Census Block Groups and Taxlots) after which the areal percentage is calculated and added to the each polygon.

Heat data follows a similar process, except that the initial dataset is  raster  instead of vector. This requires the use of a GIS tool called  Zonal Statistics as Table  that extracts the values of the raster and produces a table that can be joined with the desired geography.

Social data is a table joined using a key (Census Block Group ID) that links the spatial polygons and the social data.