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Forest degradation in the Brazilian Amazon due to selective logging and forest fires may greatly increase the human footprint beyond outright deforestation. We demonstrate a method to quantify annual deforestation and degradation simultaneously across the entire region for the years 2000-2010 using high-resolution Landsat satellite imagery. Combining spectral mixture analysis, normalized difference fraction index, and knowledge-based decision tree classification, we mapped and assessed the accuracy to quantify forest (0.97), deforestation (0.85) and forest degradation (0.82) with an overall accuracy of 0.92. We show that 169,074 km2 of Amazonian forest was converted to human-dominated land uses, such as agriculture, from 2000 to 2010. In that same time frame, an additional 50,815 km2 of forest was directly altered by timber harvesting and/or fire, equivalent to 30% of the area converted by deforestation. While average annual outright deforestation declined by 46% between the first and second halves of the study period, annual forest degradation increased by 20%. Existing operational monitoring systems (PRODES: Monitoramento da Florestal Amazônica Brasileira por Satélite) report deforestation area to within 2% of our results, but do not account for the extensive forest degradation occurring throughout the region due to selective logging and forest fire. Annual monitoring of forest degradation across tropical forests is critical for developing land management policies as well as the monitoring of carbon stocks/emissions and protected areas. [ABSTRACT FROM AUTHOR]

Estimation of fire impacts and forest recovery using remote sensing is difficult because of the heterogeneity of fire history (frequency, severity, and time since last fire) across burned forest landscapes. The authors analyzed impacts of fire frequency and severity within recovering forests in the Amazon region using remote sensing. A multispectral Landsat time series dataset was used to reconstruct the fire history from 1990 to 2002 in a portion of Mato Grosso, Brazil. Five narrowband vegetation indices were then calculated from a hyperspectral Earth Observing One (EO-1) Hyperion image for spectral analysis of physiological characteristics of fire-disturbed forests and their recovery. A total of 30%% of the forests burned during the study period, with 72%% burned once, 24%% burned twice, and less than 4%% burned three times. In terms of severity, 70%% of burned forest was lightly burned, 21.1%% was moderately burned, and 9.1%% was severely burned. Analyses of spectral indices [normalized difference vegetation index (NDVI), carotenoid reflectance index (CRI), and photochemical reflectance index (PRI)] showed that those related to canopy greenness and pigment contents can discriminate between burned forests and undisturbed forest for the first 3 years after forest fire, whereas the effectiveness of canopy water content indices [normalized difference water index (NDWI) and normalized difference infrared index (NDII)] varied from 1 to 3 years, depending on the fire severity. Despite the relatively low signal-to-noise ratios of Hyperion imagery, we show that narrowband-derived indices provide useful information for monitoring degraded forests beyond what is currently possible with Landsat. This illustrates the great potential for environmental monitoring using satellite-borne hyperspectral sensors, such as the Hyperspectral Infrared Imager (HyspIRI), which have better signal-to-noise ratios. [ABSTRACT FROM AUTHOR]

• Forest fires in Acre in 2005 and 2010 formed 120,000 ha of bamboo-dominated forest. • After fire, tree damage caused by the growth of bamboo culms can double or triple. • The bamboo-dominated forest has less trees and species diversity than other forests. • Besides the fire, human-climate interactions increase the risk of bamboo expansion. Since the late 1980s the Amazon rainforest has been affected by major forest fires every 3–5 years, mainly in the southwestern portion of the region. Besides the reduction of forest biomass and changes in structure and floristic composition, these forest fires favor the expansion of bamboo in forests in the southwestern Amazon. However, we know little about the impact of fire on bamboo expansion and changes in forest structure. The goal of this study is to quantify forest degradation by fire in areas with bamboo in the eastern portion of the state of Acre, Brazil, based upon a combination of forest-inventory and satellite remote-sensing data. The forest fires were defined by remote sensing as those in which the crowns of the trees were directly or indirectly affected by fire to the point that they cause a detectable impact on the optical satellite images in the 1984–2016 period. We measured trees and bamboo in 6 ha distributed in twelve 0.5-ha plots (100 m × 50 m) in unburned forest, forest burned in 2005, burned forest in 2010 and forest burned in both 2005 and 2010. Our results show change in the structure of the forest with a reduction in the number of live trees as the number of bamboo culms increases after the forest fires. The amount of breakage and damage to the trees by the bamboo culms can double or triple with the expansion of the bamboo after fire impact. Bamboo expansion was identified based on an increase of the proportion of pixels with near-infrared channel reflectance values > 3500. The impact of forest fires resulted in incursion and dominance of bamboo culms over an area of 120,000 ha, changing the forest type of this area to "bamboo-dominated forest." Our results clearly show that drought-induced forest fires with anthropogenic sources are capable of shifting the structure of forest in southwestern Amazonia towards bamboo-dominated forest. With future climate scenarios indicating more frequent and extensive droughts due to global warming, which, together with the use of fire for new deforestation and for managing pasture and agricultural fields, can be expected to cause more forests in southwestern Amazonia to be exposed to extensive fires and potential increase in bamboo density. [ABSTRACT FROM AUTHOR]