Assessment of Land Degradation and Droughts in an Arid Area Using Drought Indices, Modified Soil-Adjusted Vegetation Index and Landsat Remote Sensing Data

Abstract

Ain Sefra is part of the Ksour Mountains and it's situated in southwestern Algeria, where the climate is arid. The study area is progressively facing regression and degradation exacerbated by climate change. These trends point to a significant acceleration of desertification and drought and the loss of production systems that play a critical social, ecological, and economic role in the region. To better understand the natural hazard of dryness in Ain Sefra and the impact of climate change, we used various drought indices and remote sensing data. Hence, analyzing precipitation records from 1965 to 2021, through several drought indices, droughts were identified as a recurring phenomenon. Moreover, the frequency of successive dry years is relatively high. There were three most extended continuous dry periods. The first phase lasted seven years from 1980 to 1987, the second twelve years from 1994 to 2006, and the third nine years from 2012 to 2021. Calculation of the Modified Soil-Adjusted Vegetation Index (MSAVI) for five multidate satellite images allowed us to follow the evolution of land use elements in this region from 1977 to 2017. Indeed, the study of these multi-temporal images reveals a considerable growth of sands, moving towards the north and northeast of the zone during the last decades. The combination of drought indices and remote sensing seems to be most promising; whose results are valuable tools for guidance and decision support to local and regional authorities.

Long-Term Water Quality Monitoring: Using Satellite Images for Temporal and Spatial Monitoring of Thermal Pollution in Water Resources

“…The considered remote sensing sources have been demonstrated to be useful tools to detect and quantify temperature changes in rivers, and the same goes for numerous water and environmental bodies (such as aquifers, wetlands, agricultural plots, etc.) that usually depict the same limitation to apply remote sensing data: the reduced spatial size of these elements, which encompass low pixels from the mentioned satellite sources [56][57][58][59][60]. Therefore, studying, investigating, and presenting appropriate solutions in this area can be very useful and practical to the scientific community and to local authorities.…”