Detection of Peri-urban and Agricultural Expansion 1990-2015 in Pakse, Laos, Using Dense Time Stacks of Landsat Imagery

Abstract

Built-up areas in Southeast Asia have been expanding rapidly in the export-oriented economies of Vietnam, China, and Thailand, but less attention has been paid to cities in more rural nations such as Laos. The Laotian landscape has been shaped by both internal migration to burgeoning urban areas and large-scale foreign agricultural investment, but these trends have never been assessed together using remotely sensed satellite data. This study presents results from efforts to characterize and quantify expansion of built-up and agricultural land over a 35 km radius surrounding Pakse, the third largest city in Laos, using a multi-date composite change detection approach applied to dense time stacks of Landsat imagery. The method relies on a supervised, boosted decision tree classification that exploits training data of stable/changed areas interpreted from Google Earth and Landsat images spanning 1990 to 2015. The results show that the decision tree approach provides a land cover change map with an overall accuracy of 92%, despite noisy and missing data, frequent cloud cover, and high land cover heterogeneity across small areas. The results also show that, while built-up areas in greater Pakse expanded 28% over 25 years, agricultural lands expanded 48% over the same period. This work provides the most up-to-date land cover map of greater Pakse at the highest spatial and temporal resolution available, and adds useful data to regional environmental monitoring and sustainability efforts.