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In the Amazon, deforestation and climate change lead to increased vulnerability to forest degradation, threatening its existing carbon stocks and its capacity as a carbon sink. We use satellite L-Band Vegetation Optical Depth (L-VOD) data that provide an integrated (top-down) estimate of biomass carbon to track changes over 2011–2019. Because the spatial resolution of L-VOD is coarse (0.25°), it allows limited attribution of the observed changes. We therefore combined high-resolution annual maps of forest cover and disturbances with biomass maps to model carbon losses (bottom- up) from deforestation and degradation, and gains from regrowing secondary forests. We show an increase of deforestation and associated degradation losses since 2012 which greatly outweigh secondary forest gains. Degradation accounted for 40% of gross losses. After an increase in 2011, old-growth forests show a net loss of above-ground carbon between 2012 and 2019. The sum of component carbon fluxes in our model is consistent with the total biomass change from L-VOD of 1.3 Pg C over 2012-2019. Across nine Amazon countries, we found that while Brazil contains the majority of biomass stocks (64%), its losses from disturbances were disproportionately high (79% of gross losses). Our multi-source analysis provides a pessimistic assessment of the Amazon carbon balance and highlights the urgent need to stop the recent rise of deforestation and degradation, particularly in the Brazilian Amazon. [ABSTRACT FROM AUTHOR]

Forest cover disturbances due to processes such as logging and forest fires are a widespread issue especially in the tropics, and have heavily affected forest biomass and functioning in the Brazilian Amazon in the past decades. Satellite remote sensing has played a key role for assessing logging activities in this region; however, there are still remaining challenges regarding the quantification and monitoring of these processes affecting forested lands. In this study, we propose a new method for monitoring areas affected by selective logging in one of the hotspots of Mato Grosso state in the Brazilian Amazon, based on a combination of object-based and pixel-based classification approaches applied on remote sensing data. Logging intensity and changes over time are assessed within grid cells of 300 m × 300 m spatial resolution. Our method encompassed three main steps: (1) mapping forest/non-forest areas through an object-based classification approach applied to a temporal series of Landsat images during the period 2000–2015, (2) mapping yearly logging activities from soil fraction images on the same Landsat data series, and (3) integrating information from previous steps within a regular grid-cell of 300 m × 300 m in order to monitor disturbance intensities over this 15-years period. The overall accuracy of the baseline forest/non-forest mask (year 2000) and of the undisturbed vs disturbed forest (for selected years) were 93% and 84% respectively. Our results indicate that annual forest disturbance rates, mainly due to logging activities, were higher than annual deforestation rates during the whole period of study. The deforested areas correspond to circa 25% of the areas affected by forest disturbances. Deforestation rates were highest from 2001 to 2005 and then decreased considerably after 2006. In contrast, the annual forest disturbance rates show high temporal variability with a slow decrease over the 15-year period, resulting in a significant increase of the ratio between disturbed and deforested areas. Although the majority of the areas, which have been affected by selective logging during the period 2000–2014, were not deforested by 2015, more than 70% of the deforested areas in 2015 had been at least once identified as disturbed forest during that period. [ABSTRACT FROM AUTHOR]

In this paper we analyse the extent of fire-induced forest degradation in Mato Grosso State, Brazil. Weutilise a sample based approach used in a previous pan-tropical deforestation survey to derive information on land cover and burned areas in the two major biomes of Mato Grosso: Amazon and Cerrado. Land cover and burned area are mapped for three years (2000-2005-2010) over 77 sample sites (10 000 ha each) distributed systematically throughout the state which covers 90.337 Mha. Our results indicate continuing forest degradation by fires in the state and potentially increasing fire susceptibility of the Amazon forests, regardless of the decrease in deforestation. 2010 witnessed the most extensive fireinduced forest degradation (~300 000 ha) in the forests of the Amazon biome among the study years, regardless of the fact that the fire season was less severe than in 2005. Deforestation in the Amazon biome in Mato Grosso dropped from 590 000 ha year-1 in the 2000-2005 period to 190 000 ha year-1 in the second half of the decade. The findings of this study advocate the inclusion of forest fire effects into carbon accounting initiatives. [ABSTRACT FROM AUTHOR]

The area of land covered by forest and trees is an important indicator of environmental condition. This study presents and analyses results from the Global Forest Resources Assessment 2015 (FRA 2015) of the Food and Agriculture Organization of the United Nations. FRA 2015 was based on responses to surveys by individual countries using a common reporting framework, agreed definitions and reporting standards. Results indicated that total forest area declined by 3%, from 4128 M ha in 1990 to 3999 M ha in 2015. The annual rate of net forest loss halved from 7.3 M ha y −1 in the 1990s to 3.3 M ha y −1 between 2010 and 2015. Natural forest area declined from 3961 M ha to 3721 M ha between 1990 and 2015, while planted forest (including rubber plantations) increased from 168 M ha to 278 M ha. From 2010 to 2015, tropical forest area declined at a rate of 5.5 M ha y −1 – only 58% of the rate in the 1990s – while temperate forest area expanded at a rate of 2.2 M ha y −1 . Boreal and sub-tropical forest areas showed little net change. Forest area expanded in Europe, North America, the Caribbean, East Asia, and Western-Central Asia, but declined in Central America, South America, South and Southeast Asia and all three regions in Africa. Analysis indicates that, between 1990 and 2015, 13 tropical countries may have either passed through their forest transitions from net forest loss to net forest expansion, or continued along the path of forest expansion that follows these transitions. Comparing FRA 2015 statistics with the findings of global and pan-tropical remote-sensing forest area surveys was challenging, due to differences in assessment periods, the definitions of forest and remote sensing methods. More investment in national and global forest monitoring is needed to provide better support for international initiatives to increase sustainable forest management and reduce forest loss, particularly in tropical countries. [ABSTRACT FROM AUTHOR]

A method has been developed to identify and map areas of forest degradation caused by either selective logging or fires in tropical humid ecosystems. Our study area is located in the Mato Grosso state of Brazil, in a region known as ‘Deforestation Arc’. Eight consecutive Landsat Enhanced Thematic Mapper Plus (ETM+) images were available over this study area during the dry season of 2002 (from June to October). The proposed method is based on multi-temporal image segmentation and classification of a data set of soil and shade fraction images derived from Landsat ETM+ imagery. Areas of selectively logged forest are identified and mapped from the soil fraction images, whereas burned forest areas are identified and mapped from the shade fraction images combined with a map of deforestation happening during 2002. The main benefit of this approach is the capability to discriminate selectively logged forest from burned forest, which is a very important issue for estimating carbon emissions from forest degradation. [ABSTRACT FROM AUTHOR]

We estimate changes in forest cover (deforestation and forest regrowth) in the tropics for the two last decades (1990-2000 and 2000-2010) based on a sample of 4000 units of 10 ×10 km size. Forest cover is interpreted from satellite imagery at 30 × 30 m resolution. Forest cover changes are then combined with pan-tropical biomass maps to estimate carbon losses. We show that there was a gross loss of tropical forests of 8.0 million ha yr−1 in the 1990s and 7.6 million ha yr−1 in the 2000s (0.49% annual rate), with no statistically significant difference. Humid forests account for 64% of the total forest cover in 2010 and 54% of the net forest loss during second study decade. Losses of forest cover and Other Wooded Land (OWL) cover result in estimates of carbon losses which are similar for 1990s and 2000s at 887 MtC yr−1 (range: 646-1238) and 880 MtC yr−1 (range: 602-1237) respectively, with humid regions contributing two-thirds. The estimates of forest area changes have small statistical standard errors due to large sample size. We also reduce uncertainties of previous estimates of carbon losses and removals. Our estimates of forest area change are significantly lower as compared to national survey data. We reconcile recent low estimates of carbon emissions from tropical deforestation for early 2000s and show that carbon loss rates did not change between the two last decades. Carbon losses from deforestation represent circa 10% of Carbon emissions from fossil fuel combustion and cement production during the last decade (2000-2010). Our estimates of annual removals of carbon from forest regrowth at 115 MtC yr−1 (range: 61-168) and 97 MtC yr−1 (53-141) for the 1990s and 2000s respectively are five to fifteen times lower than earlier published estimates. [ABSTRACT FROM AUTHOR]

Aim This study provides regional estimates of forest cover in dry African ecoregions and the changes in forest cover that occurred there between 1990 and 2000, using a systematic sample of medium-resolution satellite imagery which was processed consistently across the continent. Location The study area corresponds to the dry forests and woodlands of Africa between the humid forests and the semi-arid regions. This area covers the Sudanian and Zambezian ecoregions. Methods A systematic sample of 1600 Landsat satellite imagery subsets, each 20 km × 20 km in size, were analysed for two reference years: 1990 and 2000. At each sample site and for both years, dense tree cover, open tree cover, other wooded land and other vegetation cover were identified from the analysis of satellite imagery, which comprised multidate segmentation and automatic classification steps followed by visual control by national forestry experts. Results Land cover and land-cover changes were estimated at continental and ecoregion scales and compared with existing pan-continental, regional and local studies. The overall accuracy of our land-cover maps was estimated at 87%. Between 1990 and 2000, 3.3 million hectares (Mha) of dense tree cover, 5.8 Mha of open tree cover and 8.9 Mha of other wooded land were lost, with a further 3.9 Mha degraded from dense to open tree cover. These results are substantially lower than the 34 Mha of forest loss reported in the FAO's 2010 Global Forest Resources Assessment for the same period and area. Main conclusions Our method generates the first consistent and robust estimates of forest cover and change in dry Africa with known statistical precision at continental and ecoregion scales. These results reduce the uncertainty regarding vegetation cover and its dynamics in these previously poorly studied ecosystems and provide crucial information for both science and environmental policies. [ABSTRACT FROM AUTHOR]

Forest monitoring from earth observation is crucial over tropical regions to assess forest extent and provide up-to-date estimates of deforestation rates. Based on a systematic sample of 20x20 km size sites, a processing chain has been developed at the European Commission's Joint Research Centre (JRC) for producing deforestation estimates between years 1990, 2000 and 2005. Whereas this monitoring exercise was based on Landsat imagery, limitations in Landsat availability over Central Africa for year 2010 required alternative imagery such as the Disaster Monitoring Constellation (DMC). The classification module of the existing JRC processing chain is based on tasseled caps analysis (TCap-based). We adapted this module to DMC imagery by selecting the most suitable object-features through their assessments using a sub-sample of existing land-cover maps of years 1990 and 2000. The processing chain is adapted for the production of land-cover change maps between years 2000 and 2010. The accuracy of the land-cover maps produced for year 2010 with the two methods (original TCap-based and adapted Multi-Sensor) is assessed through a reference dataset. Overall accuracies are similar for both approaches (93% and 95% respectively), but the Multi-Sensor approach shows a significant improvement when considering only changed objects (83% overall accuracy versus 56% for TCap-based). Our results show that, even by using DMC imagery with lower radiometric quality (compared to Landsat) an automated classification can provide land-cover maps with similar accuracy thanks to an appropriate object-features selection. Similar adaptations need to be developed for other satellite imagery such as SPOT and RapidEye. [ABSTRACT FROM PUBLISHER]

This paper outlines the methods and results for monitoring forest change and resulting carbon emissions for the 1990-2000 and 200-2005 periods carried out over tropical Central and South America. To produce our forest change estimates we used a systematic sample of medium resolution satellite data processed to forest change maps covering 1230 sites of 20 km by 20 km, each located at the degree confluence. Biomass data were spatially associated to each individual sample site so that annual carbon emissions could be estimated. For our study area we estimate that forest cover in the study area had fallen from 763 Mha (s.e. 10 Mha) in 1990 to 715 Mha (s.e. 10 Mha) in 2005. During the same period other wooded land (i.e., non-forest woody vegetation) had fallen from 191 Mha (s.e. 5.5 Mha) to 184 Mha (s.e. 5.5 Mha). This equates to an annual gross loss of 3.74 Mha·y-1 of forests (0.50% annually) between 1990 and 2000, rising to 4.40 Mha·y-1 in the early 2000s (0.61% annually), with Brazil accounting for 69% of the total losses. The annual carbon emissions from the combined loss of forests and other wooded land were calculated to be 482 MtC·y-1 (s.e. 29 MtC·y-1) for the 1990s, and 583 MtC·y-1 (s.e. 48 MtC·y-1) for the 2000 to 2005 period. Our maximum estimate of sinks from forest regrowth in tropical South America is 92 MtC·y-1. These estimates of gross emissions correspond well with the national estimates reported by Brazil, however, they are less than half of those reported in a recent study based on the FAO country statistics, highlighting the need for continued research in this area. [ABSTRACT FROM AUTHOR]

This paper presents a new accounting mechanism in the context of the UNFCCC issue on reducing emissions from deforestation in developing countries, including technical options for determining baselines of forest conversions. This proposal builds on the recent scientific achievements related to the estimation of tropical deforestation rates and to the assessment of 'intac' forest areas. The distinction between 'intact' and 'non intact' forests used here arises from experience with satellite-based deforestation measurements and allows accounting for carbon losses from forest degradation. The proposed accounting system would use forest area conversion rates as input data. An optimal technical solution to set baselines would be to use historical average figures during the time period from 1990 to 2005. The system introduces two different schemes to account for preserved carbon: one for countries with high forest conversion rates where the desired outcome would be a reduction in their rates, and another for countries with low rates. A 'global' baseline rate would be used to discriminate between these two country categories (high and low rates). For the hypothetical accounting period 2013-2017 and considering 72% of the total tropical forest domain for which data are available, the scenario of a 10% reduction of the high rates and of the preservation of low rates would result in approximately 1.6 billion tCO2 of avoided emissions. The resulting benefits of this reduction would be shared between those high-rate countries which reduced deforestation and those low-rate countries which did not increase their deforestation over an agreed threshold (e.g., half of "global" baseline rate). [ABSTRACT FROM AUTHOR]

Abstract: In response to the United Nations Framework Convention on Climate Change (UNFCCC) process investigating the technical issues surrounding the ability to reduce greenhouse gas (GHG) emissions from deforestation in developing countries, this paper reviews technical capabilities for monitoring deforestation and estimating emissions. Implementation of policies to reduce emissions from deforestation require effective deforestation monitoring systems that are reproducible, provide consistent results, meet standards for mapping accuracy, and can be implemented at the national level. Remotely sensed data supported by ground observations are key to effective monitoring. Capacity in developing countries for deforestation monitoring is well-advanced in a few countries and is a feasible goal in most others. Data sources exist to determine base periods in the 1990s as historical reference points. Forest degradation (e.g. from high impact logging and fragmentation) also contribute to greenhouse gas emissions but it is more technically challenging to measure than deforestation. Data on carbon stocks, which are needed to estimate emissions, cannot currently be observed directly over large areas with remote sensing. Guidelines for carbon accounting from deforestation exist and are available in approved Intergovernmental Panel on Climate Change (IPCC) reports and can be applied at national scales in the absence of forest inventory or other data. Key constraints for implementing programs to monitor greenhouse gas emissions from deforestation are international commitment of resources to increase capacity, coordination of observations to ensure pan-tropical coverage, access to free or low-cost data, and standard and consensual protocols for data interpretation and analysis. [Copyright &y& Elsevier]

An accurate estimate of carbon fluxes associated with tropical deforestation from the last two decades is needed to balance the global carbon budget. Several studies have already estimated carbon emissions from tropical deforestation, but the estimates vary greatly and are difficult to compare due to differences in data sources, assumptions, and methodologies. In this paper, we review the different estimates and datasets, and the various challenges associated with comparing them and with accurately estimating carbon emissions from deforestation. We performed a simulation study over legal Amazonia to illustrate some of these major issues. Our analysis demonstrates the importance of considering land-cover dynamics following deforestation, including the fluxes from reclearing of secondary vegetation, the decay of product and slash pools, and the fluxes from regrowing forest. It also suggests that accurate carbon-flux estimates will need to consider historical land-cover changes for at least the previous 20 years. However, this result is highly sensitive to estimates of the partitioning of cleared carbon into instantaneous burning vs. Long-timescale slash pools. We also show that carbon flux estimates based on ‘committed flux’ calculations, as used by a few studies, are not comparable with the ‘annual balance’ calculation method used by other studies. [ABSTRACT FROM AUTHOR]

Abstract: A global systematic sampling scheme has been developed by the UN FAO and the EC TREES project to estimate rates of deforestation at global or continental levels at intervals of 5 to 10 years. This global scheme can be intensified to produce results at the national level. In this paper, using surrogate observations, we compare the deforestation estimates derived from these two levels of sampling intensities (one, the global, for the Brazilian Amazon the other, national, for French Guiana) to estimates derived from the official inventories. We also report the precisions that are achieved due to sampling errors and, in the case of French Guiana, compare such precision with the official inventory precision. We extract nine sample data sets from the official wall-to-wall deforestation map derived from satellite interpretations produced for the Brazilian Amazon for the year 2002 to 2003. This global sampling scheme estimate gives 2.81 million ha of deforestation (mean from nine simulated replicates) with a standard error of 0.10 million ha. This compares with the full population estimate from the wall-to-wall interpretations of 2.73 million ha deforested, which is within one standard error of our sampling test estimate. The relative difference between the mean estimate from sampling approach and the full population estimate is 3.1%, and the standard error represents 4.0% of the full population estimate. This global sampling is then intensified to a territorial level with a case study over French Guiana to estimate deforestation between the years 1990 and 2006. For the historical reference period, 1990, Landsat-5 Thematic Mapper data were used. A coverage of SPOT-HRV imagery at 20 m × 20 m resolution acquired at the Cayenne receiving station in French Guiana was used for year 2006. Our estimates from the intensified global sampling scheme over French Guiana are compared with those produced by the national authority to report on deforestation rates under the Kyoto protocol rules for its overseas department. The latter estimates come from a sample of nearly 17,000 plots analyzed from same spatial imagery acquired between year 1990 and year 2006. This sampling scheme is derived from the traditional forest inventory methods carried out by IFN (Inventaire Forestier National). Our intensified global sampling scheme leads to an estimate of 96,650 ha deforested between 1990 and 2006, which is within the 95% confidence interval of the IFN sampling scheme, which gives an estimate of 91,722 ha, representing a relative difference from the IFN of 5.4%. These results demonstrate that the intensification of the global sampling scheme can provide forest area change estimates close to those achieved by official forest inventories (<6%), with precisions of between 4% and 7%, although we only estimate errors from sampling, not from the use of surrogate data. Such methods could be used by developing countries to demonstrate that they are fulfilling requirements for reducing emissions from deforestation in the framework of an REDD (Reducing Emissions from Deforestation in Developing Countries) mechanism under discussion within the United Nations Framework Convention on Climate Change (UNFCCC). Monitoring systems at national levels in tropical countries can also benefit from pan-tropical and regional observations, to ensure consistency between different national monitoring systems. [Copyright &y& Elsevier]

The island of Madagascar has a unique biodiversity, mainly located in the tropical forests of the island. This biodiversity is highly threatened by anthropogenic deforestation. Existing historical forest maps at national level are scattered and have substantial gaps which prevent an exhaustive assessment of long-term deforestation trends in Madagascar. In this study, we combined historical national forest cover maps (covering the period 1953–2000) with a recent global annual tree cover loss dataset (2001–2014) to look at six decades of deforestation and forest fragmentation in Madagascar (from 1953 to 2014). We produced new forest cover maps at 30 m resolution for the year 1990 and annually from 2000 to 2014 over the full territory of Madagascar. We estimated that Madagascar has lost 44% of its natural forest cover over the period 1953–2014 (including 37% over the period 1973–2014). Natural forests cover 8.9 Mha in 2014 (15% of the national territory) and include 4.4 Mha (50%) of moist forests, 2.6 Mha (29%) of dry forests, 1.7 Mha of spiny forests (19%) and 177 000 ha (2%) of mangroves. Since 2005, the annual deforestation rate has progressively increased in Madagascar to reach 99 000 ha/yr during 2010–2014 (corresponding to a rate of 1.1%/yr). Around half of the forest (46%) is now located at less than 100 m from the forest edge. Our approach could be replicated to other developing countries with tropical forest. Accurate forest cover change maps can be used to assess the effectiveness of past and current conservation programs and implement new strategies for the future. In particular, forest maps and estimates can be used in the REDD+ framework which aims at “Reducing Emissions from Deforestation and forest Degradation” and for optimizing the current protected area network. [ABSTRACT FROM AUTHOR]

The main objective of our study was to provide consistent information on land cover changes between the years 1990 and 2010 for the Cerrado and Caatinga Brazilian seasonal biomes. These areas have been overlooked in terms of land cover change assessment if compared with efforts in monitoring the Amazon rain forest. For each of the target years (1990, 2000 and 2010) land cover information was obtained through an object-based classification approach for 243 sample units (10 km × 10 km size), using (E)TM Landsat images systematically located at each full degree confluence of latitude and longitude. The images were automatically pre-processed, segmented and labelled according to the following legend: Tree Cover (TC), Tree Cover Mosaic (TCM), Other Wooded Land (OWL), Other Land Cover (OLC) and Water (W). Our results indicate the Cerrado and Caatinga biomes lost (gross loss) respectively 265,595 km 2 and 89,656 km 2 of natural vegetation (TC + OWL) between 1990 and 2010. In the same period, these areas also experienced gain of TC and OWL. By 2010, the percentage of natural vegetation cover remaining in the Cerrado was 47% and in the Caatinga 63%. The annual (net) rate of natural vegetation cover loss in the Cerrado slowed down from −0.79% yr −1 to −0.44% yr −1 from the 1990s to the 2000s, while in the Caatinga for the same periods the rate increased from −0.19% yr −1 to −0.44% yr −1 . In summary, these Brazilian biomes experienced both loss and gains of Tree Cover and Other Wooded Land; however a continued net loss of natural vegetation was observed for both biomes between 1990 and 2010. The average annual rate of change in this period was higher in the Cerrado (−0.6% yr −1 ) than in the Caatinga (−0.3% yr −1 ). [ABSTRACT FROM AUTHOR]