Bezerra, FGS; Aguiar, APD; Alvala, RCS; Giarolla, A; Bezerra, KRA; Lima, PVPS; do Nascimento, FR; Arai, E (2020). Analysis of areas undergoing desertification, using EVI2 multi-temporal data based on MODIS imagery as indicator. ECOLOGICAL INDICATORS, 117, 106579.

Desertification is a global problem that impacts a significative part of the Earth's surface, which cause a large environmental and social losses in several regions of the world. The Brazilian semiarid region, located mainly in the northeast part of the country, includes areas of moderate to very high susceptibility to desertification. In order to contribute to a comprehension of the dimensions of desertification in the Brazilian semiarid region, this paper aimed to develop a potential indicator for the evaluation and monitoring of this area, considering an appropriate temporal and spatial scales. For this objective, satellite data were used for the identification and monitoring of sub-areas potentially undergoing degradation/desertification. Thus multitemporal series of Enhanced Vegetation Index 2 (EVI2) covering the period between 2000 and 2016 was used, which were calculated from data provided by the MODIS sensor carried aboard the Terra satellite. Besides, previous samples were selected for the calibration and validation of the methodology. The results show an increase of areas potentially undergoing degradation/desertification, covering an area equal to 167,814.24 km(2) at the end of the period analyzed (around 16.7% of the study area). Approximately 23.63% of the total degraded area comprises both the Very High Degradation Trajectory and High Degradation Trajectory. The proposed methodology contributed to the determination of the degree of the degradation through the determination of Degradation Trajectories, which differentiates it from the ones proposed in other studies; however, it is emphasized that this approach must be analyzed in association with additional information, such as trends and climatic scenarios of land use and land cover, as well as retrospective analyses of the landscape, soil erosion, field recognition, socioeconomic conditions, among others.