Abstract
This study introduces active contours for multitemporal monitoring of urban trees using fine resolution imagery. In our implementation active contours locally identify tree crown image regions using a localized data energy term and competition of energy forces between adjacent contours. The simultaneous evolution of n contours represents an equivalent number of tree crowns which are initialized based on a fast and efficient image fitting procedure. We incorporate prior information into the multitemporal analysis, as optimized contours are propagated through a sequence of images. We demonstrate the applicability of the method to monitor individual trees and tree groups in two residential areas in the Netherlands using multispectral aerial images acquired over a period of five years. The method allowed the identification of abrupt and gradual tree crown changes in both areas and performed superior to an alternative region growing segmentation approach. We conclude that the method extracts meaningful image objects that facilitate tree crown monitoring and is effective to update tree crown spatial-databases in urban areas.
| Original language | English |
|---|---|
| Pages (from-to) | 413-426 |
| Journal | Remote sensing of environment |
| Volume | 124 |
| DOIs | |
| Publication status | Published - 2012 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 11 Sustainable Cities and Communities
Keywords
- 2023 OA procedure
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