Towards Uncovering Three Decades of LULC in the Brazilian Drylands: Caatinga Biome Dynamics (1985–2019)

Author:

Franca Rocha Washington J. S.1ORCID,Vasconcelos Rodrigo N.12,Costa Diego P.123,Duverger Soltan Galano124,Lobão Jocimara S. B.1,Souza Deorgia T. M.1,Herrmann Stefanie M.5,Santos Nerivaldo A.2,Franca Rocha Rafael O.2,Ferreira-Ferreira Jefferson6ORCID,Oliveira Mariana6,Barbosa Leonardo da Silva6ORCID,Cordeiro Carlos Leandro6,Aguiar Willian M.1ORCID

Affiliation:

1. Postgraduate Program in Earth Modeling and Environmental Sciences—PPGM, State University of Feira de Santana—UEFS, Feira de Santana 44036-900, BA, Brazil

2. GEODATIN—Data Intelligence and Geoinformation, Bahia Technological Park Rua Mundo, 121—Trobogy, Salvador 41301-110, BA, Brazil

3. Interdisciplinary Center for Energy and Environment (CIEnAm), Federal University of Bahia UFBA, Salvador 40170-115, BA, Brazil

4. Multidisciplinary and Multi-Institutional Postgraduate Program in Knowledge Diffusion (DMMDC), Federal University of Bahia—UFBA, Salvador 40110-100, BA, Brazil

5. School of Natural Resources and the Environment (SNRE), The University of Arizona, 1064 E. Lowell St, Tucson, AZ 85721, USA

6. World Resources Institute Brasil, Rua Cláudio Soares, 72 Cj. 1510, Sao Paulo 05422-030, SP, Brazil

Abstract

Dryland regions around the world are facing intricate challenges due to climate change and human activities. The Caatinga biome in Brazil, an exceptional dryland ecosystem covering approximately 86.3 million hectares, is particularly impacted by human influence. We conducted an extensive study analyzing changes in land use and land cover within the Caatinga region over a span of 35 years, from 1985 to 2019. This study leverages collective knowledge and collaborative effort with the MapBiomas project to provide valuable insights into the biome’s landscape. It maps eight principal land cover classes using Landsat Collection 1 Tier 1 data normalized to top-of-atmosphere reflectance. All data processing was carried out within the Google Earth Engine platform, and the graphics were generate using R version 3.6.2. This study achieved an impressive 80% global accuracy in the time series of Caatinga land use and land cover (LULC) changes, with allocation and area discrepancies of 11.6% and 8.5%, respectively. The extensive 35-year LULC dataset reveals a substantial 11% reduction in natural vegetation in the Caatinga biome, translating to a loss of 6.57 million hectares. This decline is primarily attributed to the expansion of cattle ranching and agriculture; all types of natural vegetation have experienced decreases, with Savanna Formation (SF) areas declining by 11% and Forest Formation (FF) areas declining by 8%. In contrast, pasturelands expanded by 62% and agricultural land expanded by 284% during this period. With their urgent and significant real-world for informing social, economic, and environmental policy decisions within the Caatinga and other dryland regions globally, these findings underscore the importance and immediacy of our research.

Publisher

MDPI AG

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