Insights from remote sensing for the study of deforestation drivers in savannas

Abstract

Savannas are the second largest biome in the world and are known for being essential hotspots of diversity, playing a crucial role in carbon storage, nutrient cycling, and climate regulation. Given its importance at a global level, this research presents a literature review on the application of remote sensing to identify the drivers of deforestation in savannas worldwide. The Web of Science and Scopus databases were used for this purpose, and systematic analyses was conducted. From a systematic perspective, articles addressing the main drivers of deforestation in savannas, remote sensing products, perspectives, and methodologies for identifying deforestation drivers at different spatial scales were considered. From a bibliographic perspective, the results revealed 169 papers. The results of the systematic review showed that agriculture and cattle grazing are the main drivers of deforestation in savannas. Other important drivers of savanna degradation, such as forestry, reforestation, mining activities, and the invasion of exotic grasses, are generally underrepresented drivers of deforestation. Regarding the methodological approaches used to identify the drivers of deforestation in savannas, the most common include assessing transition matrices and land cover changes. LANDSAT and MODIS were the most commonly used remote sensing products. Finally, despite the crucial role of savannas at the global level, studies on deforestation drivers in this biome are less developed compared to biomes such as tropical forests, which have received greater academic attention. Thus, this research contributes to identifying gaps in current knowledge, highlighting the relevance of new methods and new studies in this ecosystem.