Abstract
Abstract. An object-based approach for forest disaster change detection using High Resolution (HR) satellite images is proposed. An automatic feature selection process is used to optimize image segmentation via an original calibration-like procedure. A multitemporal classification then enables the separation of wind-fall from intact areas based on a new descriptor that depends on the level of fragmentation of the detected regions. The mean shift algorithm was used in both the segmentation and the classification processes. The method was tested on a high resolution Formosat-2 multispectral satellite image pair acquired before and after the Klaus storm. The obtained results are encouraging and the contribution of high resolution images for forest disaster mapping is discussed.
Highlights
An object-based approach for forest disaster change detection using High Resolution (HR) satellite images is proposed
We propose a nearly automatic method requiring very limited data for rapid mapping at a regional scale
In this paper, an object-based multitemporal change detection method, well-suited for emergency mapping
Summary
An object-based approach for forest disaster change detection using High Resolution (HR) satellite images is proposed. An auare complex due to fallen trees, remote-sensing techniques en- tomatic feature selection process is used to optimize image segable fast monitoring of large and unreachable areas. The former works in forestry produced low scale maps, near to the hectare and studied essentially the clear-cuts
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
