Abstract
AbstractLand degradation can be defined as a persistent reduction or loss of the biological and economic productivity resulting from climatic variations and human activities. To quantify relevant surface changes with Earth observation sensors requires a rigorous definition of the observables and an understanding of their seasonal and inter-annual temporal dynamics as well as of the respective spatial characteristics. This chapter starts with brief overviews of suitable remote sensing sources and a short history of degradation mapping. Focus is on arising possibilities with the new European Sentinel satellite fleet, which ensures unprecedented spatial, spectral, and temporal monitoring capabilities. Synergistic retrieval of innovative degradation indices is illustrated with mapping examples from the SPACES II (Science Partnerships for the Adaptation/Adjustment to Complex Earth System Processes) SALDi (South Africa Land Degradation Monitor) and EMSAfrica projects plus South African contributions. Big data approaches require adapted exploration techniques and infrastructures—both aspects conclude this chapter.
Publisher
Springer International Publishing
Reference120 articles.
1. AghaKouchak A, Farahmand A, Melton FS, Teixeira J, Anderson MC, Wardlow BD, Hain CR (2015) Remote sensing of drought: progress, challenges and opportunities. Rev Geophys 53:452–480
2. Alexakis DD, Mexis FDK, Vozinaki AEK, Daliakopoulos IN, Tsanis IK (2017) Soil moisture content estimation based on Sentinel-1 and auxiliary earth observation products. A hydrological approach. Sensors 17(6):1–16
3. Appel M, Pebesma E (2019) On-demand processing of data cubes from satellite image collections with the Gdalcubes library. Data 4(3):1–16. https://doi.org/10.3390/data4030092
4. Aschbacher J (2017) ESA’s earth observation strategy and Copernicus. In: Onoda M, Young OR (eds) Satellite earth observations and their impact on society and policy. Springer, Singapore, pp 81–86
5. Bai ZG, Dent DL (2007) Land degradation and improvement in South Africa 1. Identification by remote sensing. Report 2007/03, ISRIC World Soil Information, Wageningen, 58 pp. https://www.isric.org/sites/default/files/isric_report_2007_03.pdf