Egidio Arai

Cropland expansion changes deforestation dynamics in the southern Brazilian Amazon

Intensive mechanized agriculture in the Brazilian Amazon grew by >3.6 million hectares (ha) during 2001–2004. Whether this cropland expansion resulted from intensified use of land previously cleared for cattle ranching or new deforestation has not been quantified and has major implications for future deforestation dynamics, carbon fluxes, forest fragmentation, and other ecosystem services. We combine deforestation maps, field surveys, and satellite-based information on vegetation phenology to characterize the fate of large (>25-ha) clearings as cropland, cattle pasture, or regrowing forest in the years after initial clearing in Mato Grosso, the Brazilian state with the highest deforestation rate and soybean production since 2001. Statewide, direct conversion of forest to cropland totaled >540,000 ha during 2001–2004, peaking at 23% of 2003 annual deforestation. Cropland deforestation averaged twice the size of clearings for pasture (mean sizes, 333 and 143 ha, respectively), and conversion occurred rapidly; >90% of clearings for cropland were planted in the first year after deforestation. Area deforested for cropland and mean annual soybean price in the year of forest clearing were directly correlated (R2 = 0.72), suggesting that deforestation rates could return to higher levels seen in 2003–2004 with a rebound of crop prices in international markets. Pasture remains the dominant land use after forest clearing in Mato Grosso, but the growing importance of larger and faster conversion of forest to cropland defines a new paradigm of forest loss in Amazonia and refutes the claim that agricultural intensification does not lead to new deforestation.

Remote sensing detection of droughts in Amazonian forest canopies

*Remote sensing data are a key tool to assess large forested areas, where limitations such as accessibility and lack of field measurements are prevalent. Here, we have analysed datasets from moderate resolution imaging spectroradiometer (MODIS) satellite measurements and field data to assess the impacts of the 2005 drought in Amazonia. *We combined vegetation indices (VI) and climatological variables to evaluate the spatiotemporal patterns associated with the 2005 drought, and explore the relationships between remotely-sensed indices and forest inventory data on tree mortality. *There were differences in results based on c4 and c5 MODIS products. C5 VI showed no spatial relationship with rainfall or aerosol optical depth; however, distinct regions responded significantly to the increased radiation in 2005. The increase in the Enhanced VI (EVI) during 2005 showed a significant positive relationship (P < 0.07) with the increase of tree mortality. By contrast, the normalized difference water index (NDWI) exhibited a significant negative relationship (P < 0.09) with tree mortality. *Previous studies have suggested that the increase in EVI during the 2005 drought was associated with a positive response of forest photosynthesis to changes in the radiation income. We discuss the evidence that this increase could be related to structural changes in the canopy.

Fraction images derived from Terra Modis data for mapping burnt areas in Brazilian Amazonia

The objective of this paper is to present a method for mapping burnt areas in Brazilian Amazonia using Terra MODIS data. The proposed approach is based on image segmentation of the shade fraction images derived from MODIS, using a non‐supervised classification algorithm followed by an image editing procedure for minimizing misclassifications. Acre State, the focus of this study, is located in the western region of Brazilian Amazonia and undergoing tropical deforestation. The extended dry season in 2005 affected this region creating conditions for extensive forest fires in addition to fires associated with deforestation and land management. The high temporal resolution of MODIS provides information for studying the resulting burnt areas. Landsat 5 TM images and field observations were also used as ground data for supporting and validating the MODIS results. Multitemporal analysis with MODIS showed that about 6500 km2 of land surface were burnt in Acre State. Of this, 3700 km2 corresponded to the previously deforested areas and 2800 km2 corresponded to areas of standing forests. This type of information and its timely availability are critical for regional and global environmental studies. The results showed that daily MODIS sensor data are useful sources of information for mapping burnt areas, and the proposed method can be used in an operational project in Brazilian Amazonia.

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.Deforestation carbon emissions from the Brazilian Amazon have declined steeply, but how much drought-induced forest fire emissions add to this process is still unclear. Here the authors show that gross emissions from forest fires are more than half as great as those from deforestation during drought years.

Large-scale heterogeneity of Amazonian phenology revealed from 26-year long AVHRR/NDVI time-series

Depiction of phenological cycles in tropical forests is critical for an understanding of seasonal patterns in carbon and water fluxes as well as the responses of vegetation to climate variations. However, the detection of clear spatially explicit phenological patterns across Amazonia has proven difficult using data from the Moderate Resolution Imaging Spectroradiometer (MODIS). In this work, we propose an alternative approach based on a 26-year time-series of the normalized difference vegetation index (NDVI) from the Advanced Very High Resolution Radiometer (AVHRR) to identify regions with homogeneous phenological cycles in Amazonia. Specifically, we aim to use a pattern recognition technique, based on temporal signal processing concepts, to map Amazonian phenoregions and to compare the identified patterns with field-derived information. Our automated method recognized 26 phenoregions with unique intra-annual seasonality. This result highlights the fact that known vegetation types in Amazonia are not only structurally different but also phenologically distinct. Flushing of new leaves observed in the field is, in most cases, associated to a continuous increase in NDVI. The peak in leaf production is normally observed from the beginning to the middle of the wet season in 66% of the field sites analyzed. The phenoregion map presented in this work gives a new perspective on the dynamics of Amazonian canopies. It is clear that the phenology across Amazonia is more variable than previously detected using remote sensing data. An understanding of the implications of this spatial heterogeneity on the seasonality of Amazonian forest processes is a crucial step towards accurately quantifying the role of tropical forests within global biogeochemical cycles.

A Multi-Resolution Multi-Temporal Technique for Detecting and Mapping Deforestation in the Brazilian Amazon Rainforest

The analysis of rapid environment changes requires orbital sensors with high frequency of data acquisition to minimize cloud interference in the study of dynamic processes such as Amazon tropical deforestation. Moreover, a medium to high spatial resolution data is required due to the nature and complexity of variables involved in the process. In this paper we describe a multiresolution multitemporal technique to simulate Landsat 7 Enhanced Thematic Mapper Plus (ETM+) image using Terra Moderate Resolution Imaging Spectroradiometer (MODIS). The proposed method preserves the spectral resolution and increases the spatial resolution for mapping Amazon Rainfores deforestation using low computational resources. To evaluate this technique, sample images were acquired in the Amazon rainforest border (MODIS tile H12-V10 and ETM+/Landsat 7 path 227 row 68) for 17 July 2002 and 05 October 2002. The MODIS-based simulated ETM+ and the corresponding original ETM+ images were compared through a linear regression method. Additionally, the bootstrap technique was used to calculate the confidence interval for the model to estimate and to perform a sensibility analysis. Moreover, a Linear Spectral Mixing Model, which is the technique used for deforestation mapping in Program for Deforestation Assessment in the Brazilian Legal Amazonia (PRODES) developed by National Institute for Space Research (INPE), was applied to analyze the differences in deforestation estimates. The results showed high correlations, with values between 0.70 and 0.94 (p < 0.05, student’s t test) for all ETM+ bands, indicating a good assessment between simulated and observed data (p < 0.05, Z-test). Moreover, simulated image showed a good agreement with a reference image, originating commission errors of 1% of total area estimated as deforestation in a sample area test. Furthermore, approximately 6% or 70 km² of deforestation areas were missing in simulated image classification. Therefore, the use of Landsat simulated image provides better deforestation estimation than MODIS alone.

Disentangling the contribution of multiple land covers to fire-mediated carbon emissions in Amazonia during the 2010 drought

Abstract In less than 15 years, the Amazon region experienced three major droughts. Links between droughts and fires have been demonstrated for the 1997/1998, 2005, and 2010 droughts. In 2010, emissions of 510 ± 120 Tg C were associated to fire alone in Amazonia. Existing approaches have, however, not yet disentangled the proportional contribution of multiple land cover sources to this total. We develop a novel integration of multisensor and multitemporal satellite‐derived data on land cover, active fires, and burned area and an empirical model of fire‐induced biomass loss to quantify the extent of burned areas and resulting biomass loss for multiple land covers in Mato Grosso (MT) state, southern Amazonia—the 2010 drought most impacted region. We show that 10.77% (96,855 km2) of MT burned. We estimated a gross carbon emission of 56.21 ± 22.5 Tg C from direct combustion of biomass, with an additional 29.4 ± 10 Tg C committed to be emitted in the following years due to dead wood decay. It is estimated that old‐growth forest fires in the whole Brazilian Legal Amazon (BLA) have contributed to 14.81 Tg of C (11.75 Tg C to 17.87 Tg C) emissions to the atmosphere during the 2010 fire season, with an affected area of 27,555 km2. Total C loss from the 2010 fires in MT state and old‐growth forest fires in the BLA represent, respectively, 77% (47% to 107%) and 86% (68.2% to 103%) of Brazils National Plan on Climate Change annual target for Amazonia C emission reductions from deforestation.

Monitoring land cover in Acre State, western Brazilian Amazonia, using multitemporal remote sensing data

This article presents the use of multitemporal remote sensing data for monitoring land cover changes in Acre State, western Brazilian Amazonia. For this study, the 2000 Landsat ETM+ (ETM+, Enhanced Thematic Mapper Plus), the 1990 Landsat TM (TM, Thematic Mapper) and 1980 Landsat MSS (MSS, Multispectral Scanner System) were used. The 2005 and 2007 Terra MODIS (MODIS, Moderate Resolution Imaging Spectroradiometer) images were also used to map deforestation that had occurred during the recent years and to map burned areas that occurred in the 2005 dry year. The ETM+, TM, MSS and MODIS images were converted to vegetation, soil and shade fraction images, using linear spectral mixing model, in order to reduce the data volume for digital processing. Then land cover maps were produced by digital classification of these fraction images. The results showed that deforestation increased by 7100 km2 from 1980 to 1990, by 5100 km2 from 1990 to 2000 and by 3300 km2 from 2000 to 2007. About 2100 km2 of vegetation regrowth areas were observed in the 2000 ETM+ images. The analysis of 2005 MODIS images showed that 3700 km2 of deforested areas and 2800 km2 of forested areas were burned in Acre State in 2005. This kind of information is important for regional and global environmental studies and for efforts to control such burning and deforestation activities in the future.

An integrated remote sensing and GIS approach for monitoring areas affected by selective logging: A case study in northern Mato Grosso, Brazilian Amazon

Highlights • A new approach for monitoring areas affected by selective logging is proposed.• We use combination of object-based and pixel-based classification approaches.• Logging intensity and changes over time are assessed within grid cells.• Changes in forest cover are assessed consistently through time.

Fires in Amazonia

Fire has been used since the first humans arrived in Amazonia; however, it has recently become a widely used instrument for large-scale forest clearance. Patterns of fire incidence in the region have been exacerbated by recent drought events. Understanding temporal and spatial fire patterns as well as their consequences for forest structure, species composition, and the carbon cycle is critical for minimising global change impacts on Amazonian ecosystems and people. In this chapter, we provide an overview of the state of our knowledge on the spatial and temporal patterns of fire incidence in Amazonia, depicting the historical fire usage in the region, their relationship with land use and land cover, and their responses to climate seasonality and droughts. We subsequently focus on the impacts of fire, by quantifying the extent of burnt forests during major droughts and describing the main impacts on forest structure, composition, and carbon stocks. Finally, we present an overview of modelling initiatives for forecasting fire incidence in the region. We conclude by providing a comprehensive view of the processes that influence fire occurrence, potential feedbacks, and impacts in Amazonia. We also highlight how key areas within fire ecology must be improved for a better understanding of the long-term effect of fire on the Amazon forest ‘biome’.