Assessment of Land Desertification in the Brazilian East Atlantic Region Using the Medalus Model and Google Earth Engine

Theilon Henrique de Jesus Macêdo, Cristiano Tagliaferre, Bismarc Lopes da Silva (), Alessandro de Paula, Odair Lacerda Lemos, Felizardo Adenilson Rocha, Rosilene Gomes de Souza Pinheiro and Ana Carolina Santos Lima
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Theilon Henrique de Jesus Macêdo: Forest Sciences Graduate Program, State University of Southwestern Bahia, Vitória da Conquista 45029-000, Bahia, Brazil
Cristiano Tagliaferre: Department of Agricultural Engineering and Soils (DEAS), State University of Southwestern Bahia, Vitória da Conquista 45029-000, Bahia, Brazil
Bismarc Lopes da Silva: Graduate Program in Agronomy, State University of Southwestern Bahia, Vitória da Conquista 45029-000, Bahia, Brazil
Alessandro de Paula: Department of Agricultural Engineering and Soils (DEAS), State University of Southwestern Bahia, Vitória da Conquista 45029-000, Bahia, Brazil
Odair Lacerda Lemos: Department of Agricultural Engineering and Soils (DEAS), State University of Southwestern Bahia, Vitória da Conquista 45029-000, Bahia, Brazil
Felizardo Adenilson Rocha: Federal Institute of Bahia, Vitória da Conquista 45029-000, Bahia, Brazil
Rosilene Gomes de Souza Pinheiro: Graduate Program in Agronomy, State University of Southwestern Bahia, Vitória da Conquista 45029-000, Bahia, Brazil
Ana Carolina Santos Lima: Graduate Program in Agronomy, State University of Southwestern Bahia, Vitória da Conquista 45029-000, Bahia, Brazil

Land, 2023, vol. 13, issue 1, 1-16

Abstract: Many factors drive land desertification, especially in arid and semi-arid regions. However, the sheer number of these driving factors of desertification makes analyses computer-intensive. Cloud computing offers a solution to address this problem, especially in developing countries. The objective of this work was to assess the sensitivity of the East Atlantic Basin, Brazil, to desertification using the Mediterranean Desertification and Land Use (MEDALUS) model and Google Earth Engine (GEE). The model is composed of four environmental Quality Indices (QIs) associated with soil (SQI), vegetation (VQI), climate (CQI), and management (MQI), each encompassing factors that influence the desertification process. Digital databases corresponding to these factors were pre-processed and uploaded to GEE for analysis. We report Environmentally Sensitive Areas (ESAs) and Environmentally Critical Factors (ECF) maps of the East Atlantic Basin, which show that most of the basin is in either a critical (49.4%) or fragile (35.7%) state of sensitivity. In contrast, only a smaller portion of the area is unaffected (5%) or potentially affected (10.1%). The analysis also revealed an inverse correlation between desertification sensitivity and the presence of vigorous vegetation. A joint evaluation of ESAs and ECF shed light on the importance of each factor in the sensitivity to desertification. The East Atlantic Basin shows a high degree of sensitivity to desertification, thereby demanding more attention and the establishment of measures to mitigate the negative impacts of the desertification process.

Keywords: environmental sensitivity; cloud computing; GIS; land degradation; Brazil (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2023
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