21st Century drought-related fires counteract the decline of Amazon deforestation carbon emissions

Tropical carbon emissions are largely derived from direct forest clearing processes. Yet, emissions from drought-induced forest fires are, usually, not included in national-level carbon emission inventories. Here we examine Brazilian Amazon drought impacts on fire incidence and associated forest fire carbon emissions over the period 2003–2015. We show that despite a 76% decline in deforestation rates over the past 13 years, fire incidence increased by 36% during the 2015 drought compared to the preceding 12 years. The 2015 drought had the largest ever ratio of active fire counts to deforestation, with active fires occurring over an area of 799,293 km2. Gross emissions from forest fires (989 ± 504 Tg CO2 year−1) alone are more than half as great as those from old-growth forest deforestation during drought years. We conclude that carbon emission inventories intended for accounting and developing policies need to take account of substantial forest fire emissions not associated to the deforestation process

Detection of logging infrastructure in the state of rondônia using remotely sensed data

Logging lands (forest roads and log decks) are an underlying issue during selective logging activities, but they are responsible for most impacts on the forest. This study aimed to apply and assess the performance of five geoprocessing techniques on remotely sensed data using three different spatial resolutions to detect logging lands under forest management at the Jamari National Forest, state of Rondônia, Brazil. The research results showed that Normalized Difference Vegetation Index (NDVI) and Principal Components Analysis (PCA) presented the best overall accuracy using spatial resolutions of 5 and 10 meters, and 30 meters, respectively. Generally, the overall accuracy and Kappa statistics for the selectively logged forest classifications were not good (39.2% or lower, and 0.38 or lower, respectively). The low performance of the geoprocessing techniques is related to the subtle changes on the forest canopy cover under selective logging activities

Estimates of selective logging impacts in tropical forest canopy cover using RapidEye imagery and field data

© SISEF. Selective logging is one of the leading causes of forest degradation in the Brazilian Amazon region. The Brazilian Federal government has adopted a forest concession policy as a strategy to mitigate impacts of selective logging and regulate operations of the tropical timber industry in Brazil. This study used fractional forest coverage derived from satellite imagery and field data to assess forest degradation in two selectively logged study sites within the Jamari National Forest, a protected area located in the western Brazilian state of Rondônia. Initially, we estimated the fractional coverage from vegetation indices using RapidEye imagery and compared to gap fraction data derived from hemispherical photos acquired in the field. Subsequently, we estimated the impacts of different types of selective logging activities (log decks, primary and secondary roads, tree fall gaps, and skid trails) on forest cover using the fractional coverage dataset. The NDVI showed the highest R2 (0.56), indicating that 56% of the sample variation in fractional coverage derived from ground measurements can be explained by fractional coverage derived from the NDVI model. Our results also showed that the intensity of canopy impacts may vary according to the selective logging activity, ranging from skid trails to log decks which had the lightest and the heaviest canopy impacts, respectively