René Beuchle

Determination of tropical deforestation rates and related carbon losses from 1990 to 2010

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.

Forest Cover Changes in Tropical South and Central America from 1990 to 2005 and Related Carbon Emissions and Removals

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.

The Effect of Climate Anomalies and Human Ignition Factor on Wildfires in Russian Boreal Forests

Over the last few years anomalies in temperature and precipitation in northern Russia have been regarded as manifestations of climate change. During the same period exceptional forest fire seasons have been reported, prompting many authors to suggest that these in turn are due to climate change. In this paper, we examine the number and areal extent of forest fires across boreal Russia for the period 2002–2005 within two forest categories: ‘intact forests’ and ‘non-intact forests’. Results show a far lower density of fire events in intact forests (5–14 times less) and that those events tend to be in the first 10 km buffer zone inside intact forest areas. Results also show that, during exceptional climatic years (2002 and 2003), fire event density is twice that found during normal years (2004 and 2005) and average areal extent of fire events (burned area) in intact forests is 2.5 times larger than normal. These results suggest that a majority of the fire events in boreal Russia are of human origin and a maximum of one-third of their impact (areal extension) can be attributed to climate anomalies alone, the rest being due to the combined effect of human disturbances and climate anomalies.

Mapping of the tropical forest cover of insular Southeast Asia from SPOT4-Vegetation images

The objective of this study was to refine the methodology for a regional assessment of tropical forest cover in insular Southeast Asia from coarse resolution satellite images. SPOT4-Vegetation 10-day composites from 1998 to 2000 were used for the generation of a cloud free sub-regional mosaic image. Pixel selection was based on minimum values in the short-wave (monthly composites) and near-infrared spectral bands (annual composites), providing a maximum discrimination between forest and non-forest. A forest cover map was derived from digital classification of the dataset. The classification result was validated by comparison with the interpretation of 19 Landsat Thematic Mapper (TM) reference sites distributed over the sub-region. Forest area estimates were derived from the map and compared to Forest Resources Assessment 2000 data compiled by the Food and Agricultural Organization (FAO) of the United Nations. Results show that the new coarse resolution satellite sensor can provide sufficient information for mapping of tropical forest cover at the regional and sub-regional level.

Automatic Updating of an Object-Based Tropical Forest Cover Classification and Change Assessment

The TREES-3 project of the European Commissions Joint Research Centre is producing estimates of tropical forest cover changes for two time periods: 1990–2000 and 2000–2010. This paper presents the method developed for the automatic change detection and classification of year 2010 imagery integrating the existing segmentation and classification results of the period 1990–2000. The year 2010 imagery is processed in three automatic steps: segmentation, change detection and object spectral classification. The validated maps of forest cover for the years 1990 and 2000 are integrated as thematic input layer into the image segmentation and classification process for the year 2010 data. An object-based change detection technique is applied using Tasseled Cap components and spectral Euclidean distances. Objects detected as changed are classified in two steps: parametric classification based on membership functions and change vector analysis for the remaining unclassified objects. All objects identified as ‘unchanged’ are used as training areas for parametric classification and spectral signatures are extracted from 2010 imagery. The change vectors are defined according to the validated land cover classification of the year 2000. The segmentation approach was tested on 568 sample units spread over Brazil. The segmentation results for year 2010 demonstrated consistency with the segmentation of imagery for the period 1990–2000. The resulting overall accuracy of the automatic classification was calculated for the 281 sample units of the Brazilian Amazon biome and for 201 sample units of three more complex Brazilian biomes, Caatinga, Cerrado and Pantanal, at 92% and 91% respectively.

Assessment of forest degradation in Brazilian Amazon due to selective logging and fires using time series of fraction images derived from Landsat ETM+ images

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.

Estimating Burned Area in Mato Grosso, Brazil, Using an Object-Based Classification Method on a Systematic Sample of Medium Resolution Satellite Images

This paper presents a new approach for estimating burned areas at a regional scale, using a systematic sample of medium spatial resolution satellite images. This approach is based on a pan-tropical deforestation survey developed by the Joint Research Centre. We developed and tested our approach over Mato Grosso State, located in the Brazilian Legal Amazon region, with a total area of 903 366 km2. We analyze Landsat-5 TM imagery over 77 sample sites (20 km × 20 km in size) located at each full degree confluence of latitude and longitude. Our new approach leads to an estimate of burned area for year 2010 at 66 368 km2, representing approximately 7.3% of the Mato Grosso area. This estimate is compared to estimates from two different approaches: 1) from a method developed by the Brazilian Institute for Space Research, applied to a wall-to-wall coverage of Landsat-5 TM imagery and 2) from a method using MODIS MCD64A1 products of the University of Maryland, resulting in 70 232 and 55 157 km2 of burned area, respectively (representing 7.8% or 6.1% of Mato Grosso area). Our method produces statistically valid estimates of burned areas for the Brazilian State of Mato Grosso in a more efficient manner than previous methods and enables the inclusion of small burn scars typically missed by coarse resolution satellites. This approach can be applied for regional and global assessments as well as for refining and evaluating burned area products based on coarse spatial resolution imagery like MODIS or SPOT-VEGETATION.

Combining Landsat TM/ETM+ and ALOS AVNIR-2 Satellite Data for Tropical Forest Cover Change Detection

The European Commission funded Tropical Ecosystem Environment Observation by Satellite (TREES) project aims to assess the forest cover and its changes within the pan- tropical belt. Statistics for the monitoring target periods 1990, 2000 and 2010 are derived from analyzing a systematic sample set of satellite imagery mainly from the Landsat TM and ETM+ sensors. To reach full coverage of all sample sites for the year 2010 epoch and to ensure data continuity for possible future epochs the usage of alternative satellite data is inevitable. In this study the replacement of Landsat data with ALOS AVNIR-2 data was tested. Adaptations of the existing processing chain are presented as well as the results of an accuracy assessment. The results show that AVNIR-2 data are generally suitable to substitute Landsat data in this context.

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.

Assessment of burned areas in Mato Grosso State, Brazil, from a systematic sample of medium resolution satellite imagery

This paper presents a method for mapping and assessing burned areas at a regional scale, using a systematic sample of medium spatial resolution satellite images (Landsat). The State of Mato Grosso, located in the Brazilian Amazon region, comprising an area of approximately 903,366 km2, was selected for this study. 77 sample sites (20km × 20km in size) located at each full degree confluence of latitude and longitude were analyzed. The results showed that 52,663 km2 or approximately 5.8% of the State land cover was burned in 2010. Our method produced results comparable with PanAmazonia Project data and useful for evaluating burned area products based on coarse spatial resolution imagery like MODIS or SPOT-VEGETATION.