Changes in tropical forest cover of Southeast Asia from 1990 to 2010

The study assesses the extent and trends of forest cover in Southeast Asia for the period 1990-2000-2010 and provides an overview on the main drivers of forest cover change. A systematic sample of 418 sites (10 km x 10 km size) located at the one-degree geographical confluence points and covered with satellite imagery at 30 m resolution is used for the assessment. For the analysis of satellite imagery techniques of image segmentation and automated classification were combined with visual interpretation and quality control, involving experts from Southeast Asian countries. Two forest cover classes, namely ‘Tree Cover’ and ‘Tree Cover Mosaic’, and three non-forest land cover classes were mapped. Area measures were derived for the individual sample sites and aggregated to regional statistical estimates, accounting for differences in sampling intensity due to geographical latitude, and extrapolating to uniform reference dates. For estimating the accuracy of our results an independent consistency assessment was performed from a subsample of 1572 mapping units, resulting in an overall agreement of > 85% for the general differentiation of forest cover versus non-forest cover. Forest cover in Southeast Asia is estimated at 268 Mha in 1990, dropping to 236 Mha in 2010, with annual change rates of 1.75 Mha (~0.67%) and 1.45 Mha (~0.59%) for the periods 1990-2000 and 2000-2010, respectively. The vast majority of forest cover loss (~ 2/3 for 2000-2010) occurred in insular Southeast Asia. Analysing the change patterns visible from satellite imagery and combining with the output of an expert consultation on drivers of forest change, the conversion of forest cover to cash crop plantations is ranked as the dominant driver of forest change in Southeast Asia, followed by selective logging and the establishment of tree plantations.JRC.H.3-Forest Resources and Climat

On the extent of fire-induced forest degradation in Mato Grosso, Brazilian Amazon, in 2000, 2005 and 2010

In this paper we analyse the extent of fire-induced forest degradation in Mato Grosso State, Brazil. We utilise 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 5 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 fire induced 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 in the 2000–2005 period to 190 000 ha year in the second half of the decade. The findings of this study advocate the inclusion of forest fire effects into carbon accounting initiatives.JRC.H.3-Forest Resources and Climat

Detection of forest degradation caused by fires in Amazonia from time series of MODIS fraction images

A new method is presented to detect and assess the extent of burned forests in a tropical ecosystem. Our study area is located in Mato Grosso state southern flank of the Brazilian Amazon region. MODIS images are used over the dry season of year 2010. The proposed method is based on (i) linear spectral mixing model applied to MODIS imagery to derive soil and shade fraction images and (ii) image segmentation and classification applied to a multi-temporal dataset of MODIS-derived images. In a first step, deforested areas are identified and mapped from the soil fraction images while burned areas are identified and mapped from the shade fraction images. Then, burned forest areas are mapped by combining a forest/non forest mask with the resulting burned area map. Our results show that 14,220 km2 of forests were degraded by fire in Mato Grosso during year 2010. Our approach can be potentially used operationally for detecting forest degradation due to fires. The proposed method can also be applied to time series of medium and high spatial resolution images for regional and local analysis.JRC.H.3-Forest Resources and Climat

Remote sensing of forest degradation in Southeast Asia - aiming for a regional view through 5-30 m satellite data

In this review paper we present geographical, ecological and historical aspects of Southeast Asia from the perspective of forest degradation monitoring and critically discuss available approaches for large area forest degradation monitoring with satellite remote sensing data at high to medium spatial resolution (5-30 m). Several authors have achieved promising results in geographically limited areas within Southeast Asia using automated detection algorithms. However, the application of automated methods to large area assessments remains a major challenge. To-date, nearly all large area assessments of forest degradation in the region have included a strong visual interpretation component. We conclude that due to the variety of forest types and forest disturbance levels, as well as the variable image acquisition conditions in Southeast Asia, it is unlikely that forest degradation monitoring can be conducted throughout the region using a single automated approach with currently available remote sensing data. The provision of regionally consistent information on forest degradation from satellite remote sensing data remains therefore challenging. However, the expected increase in observation frequency in the near future (due to Landsat 8 and Sentinel-2 satellites) may lead to the desired improvement in data availability and enable consistent and robust regional forest degradation monitoring in Southeast Asia.JRC.H.3-Forest Resources and Climat

First assessment on the potential of Sentinel-2 data for land area monitoring in Southeast Asian conditions

By 2016, two Sentinel-2 satellites developed by the European Space Agency (ESA) will start systematically delivering high temporal frequency (5-day revisit in the equator) coverage of all global land areas at 10-20 m spatial resolution. Before the decommissioning of the SPOT 4 satellite, the Centre National d’Etudes Spatiales (CNES) lowered the satellite to a 5-day revisit orbit to allow collection of Sentinel-2 type high temporal frequency data on 45 sites across the globe between February and June 2013. In this report we present the main findings of this “SPOT 4-Take 5” exercise for three sites located in Southeast Asia, including analysis of the cloud free observation frequency and possibilities enabled by the high frequency multi-temporal datasets. We conclude that the unprecedented acquisition frequency of high spatial resolution data holds great potential for Southeast Asian land area monitoring. In the seasonal continental part such frequency allows high spatial resolution time series analysis in an exceptional level of temporal detail, whereas in the humid insular part of the region it potentially enables accumulation of a full coverage dataset in as short as semi-annual intervals. Overall, the findings indicate that Sentinel-2 type future datasets will open new horizons for land cover monitoring in Southeast Asia and will further enforce the ongoing trend towards multi-temporal monitoring approaches.JRC.H.3-Forest Resources and Climat

Assessment of areas of selective logging and burned forests in Mato Grosso State, Brazil, from satellite imagery

This paper presents a semi-automated procedure for mapping degraded forest areas in Mato Grosso state, Brazil, from medium (30m) resolution satellite imagery. In the Brazilian Amazon region forest degradation in the context of UNFCCC REDD+ (i.e. considered as long term reduction of Carbon stocks in forests) is mainly driven by logging activities and forest fires. Medium to fine spatial resolution satellite data allow assessing the extent and distribution of deforestation, selective logging and burned forest areas with high reliability. However, it is difficult to obtain the full coverage of a region with cloud free satellite imagery for mapping logging tracks and burned areas. Such dynamic landscape features are detectable on satellite imagery only during a limited period of time in humid tropical regions (a few weeks / months). The proposed method consists in the further development of the approach used in the TREES-3 pan-tropical forest area survey conducted by the European Commission’s Joint Research Centre. It is applied to Mato Grosso State, Brazilian Amazon, using Landsat satellite imagery (Thematic Mapper sensor), acquired close to the year 2010. The approach is using a sample of sites systematically distributed at confluence geographical points (77 sample sites in Mato Grosso). The semi-automated procedure for analysis of satellite imagery extracted over the sample sites consists into: a) image pre-processing, b) production of ‘fraction images’: vegetation, soil and shade, and c) creation of spatially and spectrally homogeneous areas (‘objects’). In each of the 77 sample sites, spatial objects are then labelled as burned areas or logged forest areas through visual image interpretation. The resulting maps for the 77 sample sites are then combined with the forest cover maps of year 2010 from the TREES-3 survey. Statistical estimates of forest degradation by fires and selective logging are finally generated. The results show that 18,452 km2 and 9,435 km2 of forests appear as burned or affected by selective logging in year 2010, respectively, representing c. 4% and 2% of the total forest area of this state. The future availability of time series of finer spatial resolution data from the Sentinel-2 satellite (10m resolution) is expected to allow improving the assessment of forest degradation processes using such approach.JRC.H.3-Forest Resources and Climat