Gaps are openings within tropical forest canopies created by natural or anthropogenic disturbances. Important aspects of gap dynamics that are not well understood include how gaps close over time and their potential for contagiousness, indicating whether the presence of gaps may or may not induce the creation of new gaps. This is especially important when we consider disturbances from selective logging activities in rainforests, which take away large trees of high commercial value and leave behind a forest full of gaps. The goal of this study was to quantify and understand how gaps open and close over time within tropical rainforests using a time series of airborne LiDAR data, attributing observed processes to gap types and origins. For this purpose, the Jamari National Forest located in the Brazilian Amazon was chosen as the study area because of the unique availability of multi-temporal small-footprint airborne LiDAR data covering the time period of 2011–2017 with five data acquisitions, alongside the geolocation of trees that were felled by selective logging activities. We found an increased likelihood of natural new gaps opening closer to pre-existing gaps associated with felled tree locations (<20 m distance) rather than farther away from them, suggesting that small-scale disturbances caused by logging, even at a low intensity, may cause a legacy effect of increased mortality over six years after logging due to gap contagiousness. Moreover, gaps were closed at similar annual rates by vertical and lateral ingrowth (16.7% yr⁻¹) and about 90% of the original gap area was closed at six years post-disturbance. Therefore, the relative contribution of lateral and vertical growth for gap closure was similar when consolidated over time. We highlight that aboveground biomass or carbon density of logged forests can be overestimated if considering only top of the canopy height metrics due to fast lateral ingrowth of neighboring trees, especially in the first two years of regeneration where 26% of gaps were closed solely by lateral ingrowth, which would not translate to 26% of regeneration of forest biomass. Trees inside gaps grew 2.2 times faster (1.5 m yr⁻¹) than trees at the surrounding non-gap canopy (0.7 m yr⁻¹). Our study brings new insights into the processes of both the opening and closure of forest gaps within tropical forests and the importance of considering gap types and origins in this analysis. Moreover, it demonstrates the capability of airborne LiDAR multi-temporal data in effectively characterizing the impacts of forest degradation and subsequent recovery.

The Amazon is home to a vast biodiversity and plays a crucial role in the maintenance and conservation of the planet. The progress of anthropogenic activities in the region is one of the drivers of land cover change. Studying these changes through remote sensing enables the monitoring of degradation and deforestation in the Amazon rainforest. Using bibliometric tools this study analyses the different remote sensing approaches for land use and land cover monitoring in the Amazon. The methodology includes 1) data search and collection, 2) tool selection and data processing, and 3) data and trend analysis. The results indicate that studies on forest loss and biodiversity are trending in the field. Emerging topics focus on new tools for environmental impact assessment and evaluating new computational technologies for satellite data management.

Fires affect the Amazon rainforest and cause various socio-environmental problems. Analyses of forest fire dynamics supporting actions to combat and prevent forest fires. However, many studies have reported discrepancies in the quantification of fire, especially in the tropics. We evaluated four operational products for estimating burned areas (MAPBIOMAS, MCD64A1, GABAM, and GWIS) in a part of the southwestern Brazilian Amazon. We used the year 2019 as a reference to assess the relative performance of each product through stratification by forest and non-forest areas. Statistical (Kolmogorov–Smirnov test) and geospatial analyses were performed using fuzzy similarity analysis and mapping of burned areas for forest and non-forest classes. The four products showed a divergence of up to 90.6% in the total area burned. MAPBIOMAS was the product with the largest area burned (3379 km²), and MCD64A1 detected the smallest area (325 km²). MAPBIOMAS and GABAM generally overestimates burn scars in forest areas compared to MCD64A1 and GWIS. Factors that influence the mapping of burned areas include cloud shadow, the spatial resolution of sensors, and external noises (drought and decomposition of bamboo forests). We highlight the importance of field validation when mapping imagery to differentiate the truly burned areas from targets with similar spectral behavior.

Between 2023 and 2024, Brazil experienced one of the most severe droughts in the century, with temperatures in the Amazon reaching 2–4 °C above average. Amplified by El Niño and North Atlantic warming, the drought disrupted the hydrological cycle and essential ecosystem services, affecting agriculture, transportation, and the livelihoods of urban, rural, and Indigenous communities. This event revealed substantial shortcomings in Brazil’s fire governance framework. Moreover, it demonstrated that drought conditions exacerbate Brazil’s susceptibility to wildfires, underscoring the urgent need for coordinated and immediate policy action. This study maps and quantifies hydrological stress, forest degradation, and fire dynamics associated with the drought, identifying critical implications for environmental management. Our analysis reveals the intensification of a drought–fire–degradation feedback loop. Wildfire-affected areas increased by 9%, and degradation alerts rose by 19% in relation to long-term average levels (2016-2024). At the drought’s peak (in 2024), 4.2 Mha of fire-affected areas were detected. Maximum Cumulative Water Deficit anomalies exceeded historical thresholds, signaling a continuous dry increase in Brazil. These results highlight the urgent need for integrated fire governance. This includes comprehensive environmental education, enhanced early warning systems, targeted investments in ecosystem restoration, and stronger coordination between federal and state policies. By linking scientific evidence to actionable policy recommendations, this work guides decision-makers seeking to reduce socio-environmental risks and strengthen climate adaptation in the Amazon.