Ecosystem Analysis

Urban Land Management

Objective
Document the value of tree-covered landscapes to the metropolitan areas. Provide urban decision-makers with the information and tools needed to measure the value of natural landscapes and incorporate more trees into future development.

Challenges
· Tree cover varies not only within each mixed scene, but also over time from one year’s image to the next.
· On-the-ground survey over the large area is impractical and cost prohibitive, especially retroactively to judge change over time.
· At any point during the study years, significant tree cover throughout the area will occupy less than whole image pixels.
· Signatures need to classify different categories (percentages) of tree cover, display and quantify the categories, and do so in multiple images from different years.

Approach
DeltaCue software can be used to identify areas of change over broad areas.
IMAGINE Subpixel Classifier can then be used to characterize and quantify that change.

	Puget Sound metropolitan area 1972
1986	1996

Solution and Results
Raw satellite data can be analyzed using ERDAS IMAGINE software and IMAGINE Subpixel Classifier to determine eight categories of tree cover and one category of less than 20% tree cover. Green areas are at one end of this spectrum representing tree cover over 50%; urban areas are black. Citizens from Bellevue used these images along with CITYgreen software from American Forests to conduct a detailed analysis of the tree cover in their city.