Assessment, monitoring, and early warning of droughts: the potential for satellite remote sensing and beyond

Abstract The intensity and frequency of droughts is increasing worldwide and triggers the demand to understand the characteristics of a drought event and its impacts on the environmental and social system. Ranking among the most severe large-scale extreme weather events with highest impacts on livelihoods, there is an increasing demand to understand the characteristics of droughts. A number of countries express their great concern about the challenges posed to their sustainable development agenda due to droughts, as well as to desertification and land degradation and their relations to drought, especially in Africa. By monitoring related climatic conditions and their impact on the ground, remote sensing (RS) serves as an outstanding tool to monitor changes on the land surfaces without being in situ. It allows to cover large areas and to detect impacts on different land variables such as water bodies, soil conditions, and vegetation. Depending on different sensors and various spatial and temporal resolutions, analyses can be carried out from local to national and even to global scales. In addition, with the combined use of archived and up-to-date satellite data, it is possible to compare the geographical extent and severity of droughts in different years. The overall aim of this chapter is to review the role and contribution of satellite RS data for assessing and monitoring droughts and their impacts, its potential to provide early warning of future drought events, and remaining challenges. We explore additional information that needs to be provided in order to complement RS-based information for assessing impacts on human livelihoods, using the conceptual framing of hazard, exposure, and vulnerability. An example of a comprehensive analysis framework is the EvIDENZ (Earth Observation–based Information Product for Drought Risk Reduction on the National Level) project which takes advantage from the integration of RS information and socioeconomic data.