Utility of Landsat 7 satellite data for continued monitoring of forest cover change in protected areas in Southeast Asia

TitleUtility of Landsat 7 satellite data for continued monitoring of forest cover change in protected areas in Southeast Asia
Publication TypeJournal Article
Year of Publication2006
AuthorsTrigg SN, Curran LM, McDonald AK
JournalSingapore Journal of Tropical Geography
Date PublishedMar
Type of ArticleArticle
ISBN Number0129-7619
Accession NumberISI:000236026900005
KeywordsAMAZON, BIODIVERSITY, BORNEO, CLASSIFICATION, CONSERVATION, deforestation, EL-NINO, habitat, LAND-USE, LOGGED FORESTS, Logging, MAST-FRUITING DIPTEROCARPACEAE, protected areas, satellite sensors, tropical, Tropical deforestation

Satellite instruments, particularly the Landsat TM (Thematic Mapper) and ETM+ (Enhanced Thematic Mapper Plus) series of sensors, are important tools in the interdisciplinary study of tropical forests that are increasingly integrated into studies that monitor changes in vegetation cover within tropical forests and tropical protected areas, and also applied with other types of data to investigate the drivers of land cover change. However, further advances in the use of Landsat to study and monitor tropical forests and protected areas are threatened by the scan line corrector failure on the ETM+ sensor, as well as uncertainty about the continuity of the Landsat mission. Given these problems, this paper illustrates how ETM+ data were used in an interdisciplinary study that effectively monitored forest cover change in Gunung Palung National Park in West Kalimantan, Indonesian Borneo. Following 31 May 2003, when the ETM+ sensor's scan line corrector failed, we analysed how this failure impedes our ability to perform a similar study from this date onwards. This analysis uses six simulated post-scan line corrector failure (SLC-off) images and reveals that data gaps caused by SLC-off introduce maximum errors of 1.47 per cent and 4.04 per cent in estimates of forest cover and rates of forest loss, respectively. The analysis also demonstrates how SLC-off has transformed ETM+ data from a complete inventory dataset to a statistical sample with variable sample fraction, and notes how this data loss will confound the use of Landsat data to model land cover change in a spatially explicit manner. We discuss potential limited uses of SLC-off data and suggest alternative sensors that may provide essential remotely sensed data for monitoring tropical forests in Southeast Asia.

URL<Go to ISI>://000236026900005
Alternate JournalSingap. J. Trop. Geogr.