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Remote sensing is valuable for estimating aboveground biomass (AGB) stocks. However, its application in agricultural and pasture areas is limited compared with forest areas. This study quantifies AGB in agriculture–pasture mosaics within Brazil's Campo Maior Complex (CMC). The methodology employs remote sensing cloud processing and utilizes an estimator to incorporate vegetation indices. The results reveal significant changes in biomass values among land use and land cover classes over the past ten years, with notable variations observed in forest plantation, pasture, sugar cane, and soybean areas. The estimated AGB values range from 0 to 20 Mg.ha−1 (minimum), 53 to 419 Mg.ha−1 (maximum), and 19 to 57 Mg.ha−1 (mean). In Forest formation areas, AGB values range from approximately 0 to 278 Mg.ha−1, with an average annual value of 56.44 Mg.ha−1. This study provides valuable insights for rural landowners and government officials in managing the semiarid territory and environment. It aids in decision making regarding agricultural management, irrigation and fertilization practices, agricultural productivity, land use and land cover changes, biodiversity loss, soil degradation, conservation strategies, the identification of priority areas for environmental restoration, and the optimization of resource utilization. [ABSTRACT FROM AUTHOR]

Protected areas (PAs) help in strategies for maintaining biodiversity and inhibiting deforestation of the Amazon rainforest. However, there are few studies that evaluate the effectiveness of lands protected by states (or federation units). Our goal was to compare land use change over 35 years in state-level PAs with another area of protection, both in the Amazon of the Maranhão state, Brazil. We employed remote sensing techniques, the geographic information system (GIS), and statistical analysis with the use of analyses of covariance (ANCOVAS) to analyze the presence of the classes of land use and change in the PA. The results indicate that the state PAs were effective in preserving forest cover and decelerating grazing. The implications of the results are discussed in the context of supporting public policies at the state level for the protection of the Amazon. [ABSTRACT FROM AUTHOR]

Climate variability, land use and land cover changes (LULCC) have a considerable impact on runoff–erosion processes. This study analyzed the relationships between climate variability and spatiotemporal LULCC on runoff–erosion processes in different scenarios of land use and land cover (LULC) for the Almas River basin, located in the Cerrado biome in Brazil. Landsat images from 1991, 2006, and 2017 were used to analyze changes and the LULC scenarios. Two simulations based on the Soil and Water Assessment Tool (SWAT) were compared: (1) default application using the standard model database (SWATd), and (2) application using remote sensing multiple gridded datasets (albedo and leaf area index) downloaded using the Google Earth Engine (SWATrs). In addition, the SWAT model was applied to analyze the impacts of streamflow and erosion in two hypothetical scenarios of LULC. The first scenario was the optimistic scenario (OS), which represents the sustainable use and preservation of natural vegetation, emphasizing the recovery of permanent preservation areas close to watercourses, hilltops, and mountains, based on the Brazilian forest code. The second scenario was the pessimistic scenario (PS), which presents increased deforestation and expansion of farming activities. The results of the LULC changes show that between 1991 and 2017, the area occupied by agriculture and livestock increased by 75.38%. These results confirmed an increase in the sugarcane plantation and the number of cattle in the basin. The SWAT results showed that the difference between the simulated streamflow for the PS was 26.42%, compared with the OS. The sediment yield average estimation in the PS was 0.035 ton/ha/year, whereas in the OS, it was 0.025 ton/ha/year (i.e., a decrease of 21.88%). The results demonstrated that the basin has a greater predisposition for increased streamflow and sediment yield due to the LULC changes. In addition, measures to contain the increase in agriculture should be analyzed by regional managers to reduce soil erosion in this biome. [ABSTRACT FROM AUTHOR]

Hydroelectric energy generates more than 50% of all renewable electricity in the world. The Amazon is home to a large part of these ventures, promoted as a strategy of energy independence in order to reduce greenhouse gas emissions in the countries of the region. However, these hydroelectric plants lead to changes in land cover, fragmentation, degradation, and loss of tropical forests. This article analyzes the spatial pattern of alterations in the land cover of the municipality of Goianésia do Pará, one of the seven municipalities affected by the artificial lake of the Tucuruí hydroelectric plant. This case study integrates remote sensing and landscape metrics to identify, quantify, and spatialize the loss of tropical forest within the municipality by using satellite images of the TM-Landsat 5, ETM+-Landsat 7 and OLI-Landsat 8 sensors. The results show that the average deforestation rates were high in the first two periods: 1984–1988 (23,101.2 ha per year) and 1988–1999 (13,428.6 ha per year). However, this rate drastically fell in the last period because, by 2010, more than 60% of the territory was already deforested, which shows the consolidation of the municipality's deforestation process. [ABSTRACT FROM AUTHOR]