Potential of land classification by CubeSat in Monsoon Asia

F Kondo1, K Noda1,3, and C Phompila2

1 Faculty of Applied Biological Sciences, Gifu University, Yanagido 1-1, Gifu, 501-1193, Japan.
2Faculty of Forest Science, The National University of Laos, Vientiane Capital 0100, Lao People’s Democratic Republic
3Corresponding author: anod@gifu-u.ac.jp

Abstract. Frequent and severe flood by climate change is a big problem in the world. But there are many areas where water use and flood control facilities are not fully installed especially in developing countries. In these areas, a flood caused by heavy rainfall is getting frequent and now more serious. Few previous researches have analyzed the range and season of inundation due to lack of high resolution and frequency satellite imagery. Today,Planet Labs provides high resolution (+3.0m~) and high frequency (1 day~) CubeSat imagery. The primary goal of this research is to develop a model to analyze the range and season of springing in rainy season for Laos with clear rainy and dry season. We analyzed some land use areas from satelite imagery during rainy season with two indexes. Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) are the indexes where is identify vegetation and water covers. We analyzed seasonal change of two individual values and the relationship of two values and we distincted from the degree of two indexesfor each land use (City area, Water area, Wetland, Paddy Field). It suggests that each land use has its own value depending on the season.