A novel time series based approach to detect gradual vegetation changes in forests

Yashu Chamber, Ashish Garg, Varun Mithal, Ivan Brugere, Michael Lau, Vikrant Krishna, Shyam Boriah, Michael Steinbach, Vipin Kumar, Chris Potter, Steve Klooster

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Scopus citations

Abstract

It is well-known that forests play a vital role in maintaining biodiversity and the health of ecosystems across the Earth. This important ecological resource is under threat from both anthropogenic and biogenic pressures, ranging from insect infestations to commercial logging. Detecting, quantifying and reporting the magnitude of forest degradation are therefore critical to efforts towards minimizing the loss of one of Earth's most crucial resources. Traditional approaches that use image-based comparison for detecting forest degradation are frequently domain- or region-specific, which require expensive training, and are thus not suited for application at global scale. More recently, time series based change detection methods applied on remote sensing datasets have gained much attention because of their scalability, accuracy, and monitoring capability at frequent regular intervals. In this paper, we propose a novel approach to identify regions where forest degradation occurs gradually. The proposed approach complements traditional domain- and region-specific approaches by providing information on where degradation is occurring, and during what time, at a global scale.

Original languageEnglish (US)
Title of host publicationProceedings of the 2011 Conference on Intelligent Data Understanding, CIDU 2011
Pages248-262
Number of pages15
StatePublished - Dec 1 2011
EventNASA Conference on Intelligent Data Understanding, CIDU 2011 - Mountain View, CA, United States
Duration: Oct 19 2011Oct 21 2011

Other

OtherNASA Conference on Intelligent Data Understanding, CIDU 2011
CountryUnited States
CityMountain View, CA
Period10/19/1110/21/11

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