Monitoring expansion of plantations in Lao tropical forests using Landsat time series

Chittana Phompila; Megan Lewis; Kenneth Clarke; Bertram Ostendorf

doi:10.1117/12.2068283

8 November 2014 Monitoring expansion of plantations in Lao tropical forests using Landsat time series

Chittana Phompila, Megan Lewis, Kenneth Clarke, Bertram Ostendorf

Proceedings Volume 9260, Land Surface Remote Sensing II; 92601M (2014) https://doi.org/10.1117/12.2068283
Event: SPIE Asia-Pacific Remote Sensing, 2014, Beijing, China

Abstract

Clearing of native forest for plantation expansion is a significant component of land use change in many tropical regions. The continuing expansion of plantations has many environmental consequences, including the loss and fragmentation of habitat, alteration of nutrient cycling processes, reduction in environmentally sequestered carbon, increased soil erosion and land degradation, and loss of biodiversity. The primary goal of this research was to develop and test remote sensing methods to detect the expansion of plantations in the southern part of the Lao People’s Democratic Republic (PDR). We used Landsat satellite imagery acquired between 2003 and 2012. Principal component analysis (PCA) was applied to three Landsat temporal image pairs (2003-2006, 2006-2009 and 2009-2012) to identify areas of change. Change identification accuracy was evaluated by comparison against 1,240 random sample locations which had been independently classified from Google Earth imagery from 2006 and 2012. It was found that one of the principal components detected change in areas of plantation in the study area, with producer's accuracy of 92% and user's accuracy of 79%. This method was relatively easy to implement, involved no image purchase costs, and could be used by ecologists or forestry managers seeking to monitor forest loss or plantation expansion.

Citation Download Citation

Chittana Phompila, Megan Lewis, Kenneth Clarke, and Bertram Ostendorf "Monitoring expansion of plantations in Lao tropical forests using Landsat time series", Proc. SPIE 9260, Land Surface Remote Sensing II, 92601M (8 November 2014); https://doi.org/10.1117/12.2068283

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