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Monitoring forest changes in Borneo on a yearly basis by an object-based change detection algorithm using SPOT-VEGETATION time series

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Bontemps, Sophie [UCL] Langner, Andreas [Kansai Research Centre, Forestry and Forest Products Research Institute, Kyoto, Japan] Defourny, Pierre [UCL]

Monitoring land cover over large areas on a yearly basis is challenging. The spatial and temporal consistency of an object-based change detection algorithm was tested through a multi-year application on the forest of Borneo, using SPOT-VEGETATION time series from 2000 to 2008. Continuous change thresholds allowed the tuning of the algorithm according to specific requirements in terms of omission and commission errors. The accuracy of the method was assessed using the ROC (relative operating characteristics) curves, which were found useful to evaluate the performance of the method independently of the selected threshold and to support the selection of an optimal threshold. The forest area that annually changed between 2000 and 2008 was detected and a cumulative change map was produced. The resulting change rates and the distribution of the forest change patterns were in agreement with other sources of information. These results demonstrated the very promising temporal consistency of the proposed approach. Further work aims at testing it at larger scales.

Document type Article de périodique (Journal article) – Article de recherche
Publication date 2009
Language Anglais
Journal information "International Journal of Remote Sensing" - Vol. 33, no. 15, p. 1-31 (2009)
Peer reviewed yes
Publisher Taylor & Francis Ltd. ((United Kingdom) Abingdon)
issn 0143-1161
e-issn 1366-5901
Publication status Publié
Affiliation UCL - AGRO/MILA - Département des sciences du milieu et de l'aménagement du territoire
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Bibliographic reference Bontemps, Sophie ; Langner, Andreas ; Defourny, Pierre. Monitoring forest changes in Borneo on a yearly basis by an object-based change detection algorithm using SPOT-VEGETATION time series. In: International Journal of Remote Sensing, Vol. 33, no. 15, p. 1-31 (2009)
Permanent URL http://hdl.handle.net/2078.1/73150