Drought Monitoring using MODIS derived indices and Google Earth Engine Platform

Abstract

Drought is one of the frequently observed natural hazard resulting from precipitation deficit and increased evapotranspiration caused by high temperatures. Remote sensing indices are used to analyze spatio-temporal distribution of drought conditions and identify drought severity. In this study, we analyzed the spatio-temporal distribution of drought conditions in Turkey from February 2000 to January 2019 by using different drought indices produced from MODIS satellite data in Google Earth Engine (GEE) platform. Vegetation Health Index (VHI), Normalized Multiband Drought Index(NMDI) and Normalized Difference Drought Index (NDDI) maps in country level for different years and months of the related years were utilized to assess the drought conditions. Time series were also created for some specific locations to deeply analyze the drought conditions in 20-year period. Our results show that MODIS derived drought indices provide useful geospatial information to assess drought conditions in country level. Moreover, GEE platform is very handy and rapid tool to reach related satellite images and conduct remote sensing analysis of huge and long term date efficiently. Geospatial big data could be successfully accessed and processed in this platform not only for drought monitoring but also for other environmental monitoring applications.