Application of Remote Sensing in the Analysis of Climate Extremes Due to Global Climate Change

In this chapter, several remote sensing applications involving different analytical approaches are illustrated to assess the resulting vulnerability and impacts of climate extremes such as riverbank erosion, floods, cyclones, and droughts. In this regard, at the first stage, an erosion vulnerability analysis is presented where four criteria, namely, the normalized difference water index (NDWI), distance from the river, soil adjusted vegetation index (SAVI), and land use and land cover (LULC), are used in erosion vulnerability assessment. At the second stage, a flood vulnerability extension is highlighted using multicriteria analysis (NDWI, distance from the river, elevation, and rainfall) based on fuzzy expert systems and remote sensing datasets. At the third stage, the damage area attributed to cyclones is assessed using different indices, including the normalized difference vegetation index (NDVI), modified vegetation condition index (mVCI), and damage difference vegetation damage index (DVDI), where the occurrence and frequency of cyclones are examined by analyzing global datasets. At the fourth stage, the drought severity is determined using several satellite remote sensing indices, such as the normalized difference vegetation index (NDVI), vegetation condition index (VCI), temperature condition index (TCI), and standard precipitation index (SPI). Finally, an inventory of community perception-based knowledge is established as a source of indigenous knowledge to mitigate climate change impacts. These combined approaches may help further studies related to climate change effects.