The Cerrado is the second largest biome in Brazil after the Amazon and is the savanna with the highest biodiversity in the world. Serra Tombador Natural Reserve (STNR) is the largest private reserve located in Goiás State, and the fourth largest in the Cerrado biome. The present study aimed to map the burnt areas and to describe the spatial patterns of fire recurrence and its interactions with the classes of land-cover that occurred in STNR and its surroundings in the period between 2001 and 2010. Several Landsat TM images acquired around the months of July, August and September, coinciding with the region’s dry season when fire events intensify, were employed to monitor burnt areas. Fire scars were mapped using the supervised Mahalanobis-distance classifier and further refined using expert visual interpretation. Burnt area patterns were described by spatial landscape metrics. The effects of fire on landscape structure were obtained by comparing results among different land-cover classes, and results summarized in terms of fire history and frequencies. During the years covered by the study, 69% of the areas analyzed had fire events. The year with the largest burnt area was 2004, followed by 2001, 2007 and 2010. Thus, the largest fire events occurred in a 3-year cycle, which is compatible with other areas of the Brazilian savanna. The regions with higher annual probabilities of fire recurrence occur in the buffer zone around the park. The year 2004 also had the highest number of burnt area patches (831). In contrast, the burnt area in 2007 showed the most extensive fires with low number of patches (82). The physiognomies that suffered most fires were the native savanna formations. The study also identified areas where fires are frequently recurrent, highlighting priority areas requiring special attention. Thus, the methodology adopted in this study assists in monitoring and recovery of areas affected by fire over time.

The Brazilian semiarid region (BSR) has faced severe drought over the last three decades, which has led to a significant decline in land productivity, posing a considerable threat to food security and the local economy and communities. The United Nations Convention to Combat Desertification (UNCCD) has proposed the use of Earth observation-derived vegetation indices for monitoring land degradation across regions. In this study, we aim to evaluate three comprehensive UNCCD-recommended land productivity dynamic (LPD) approaches in the BSR by utilizing the standardized precipitation–evapotranspiration index (SPEI) at 12-month time scales as a benchmark drought index obtained from ground-based measurements. Our findings indicate that the LPD methods utilizing residual trends analysis (RESTREND), Trends.Earth (TE), and the Food and Agricultural Organization’s World Overview of Conservation Approaches and Technologies (FAO-WOCAT) are best suited for identifying degraded land areas in the BSR region compared to other approaches. However, it is advisable to use these methods with caution, since they do not fully capture the impact of drought on vegetation and may result in underestimating the extent of degraded areas. The RESTREND-based LPD, TE, and FAO-WOCAT estimate that the BSR region reached 213,248 km², 248,075 km², and 246,783 km² of degraded land, respectively, between 2001 and 2015. These findings may be valuable for decision-makers involved in land management and conservation efforts in the Sertão region of Brazil.

Despite sustained global efforts to avoid, reduce, and reverse land degradation, estimates of land degradation nationally and regionally vary considerably. Land degradation reduces agricultural productivity, impacts the provision of vital ecosystem services, and disproportionately affects vulnerable populations. The 2030 Agenda for Sustainable Development, through Sustainable Development Goal 15.3, sets out to achieve land degradation neutrality (LDN) by improving the livelihoods of those most affected and building resilience in areas affected by or at risk from degradation. The United Nations Convention to Combat Desertification (UNCCD) leads the charge in creating a spatially explicit framework for monitoring and reporting on LDN goals that countries can integrate into their land planning policies. However, it remains difficult to operationalize the integration of biophysical indicators of land degradation with climatic and socio‐economic indicators to assess the impact of land degradation on vulnerable populations. We present an integrative framework that demonstrates how freely available global geospatial data sets can be leveraged through an open‐source platform (Trends.Earth) to simplify and operationalize monitoring and reporting on progress towards achieving LDN. Then, we summarize a suite of data sets and approaches that can be used to understand and quantify the socio‐ecological interactions between drought, land degradation and population exposed to desertification, land degradation and drought. We discuss how improvements in Earth observation data sets and algorithms will allow UNCCD land‐based progress sub‐indicators (changes in primary productivity, land cover, soil organic carbon, drought, and population exposure) to be computed at enhanced spatial resolutions.