Baudouin Desclée

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.

State and evolution of the African rainforests between 1990 and 2010.

This paper presents a map of Africas rainforests for 2005. Derived from moderate resolution imaging spectroradiometer data at a spatial resolution of 250 m and with an overall accuracy of 84%, this map provides new levels of spatial and thematic detail. The map is accompanied by measurements of deforestation between 1990, 2000 and 2010 for West Africa, Central Africa and Madagascar derived from a systematic sample of Landsat images—imagery from equivalent platforms is used to fill gaps in the Landsat record. Net deforestation is estimated at 0.28% yr−1 for the period 1990–2000 and 0.14% yr−1 for the period 2000–2010. West Africa and Madagascar exhibit a much higher deforestation rate than the Congo Basin, for example, three times higher for West Africa and nine times higher for Madagascar. Analysis of variance over the Congo Basin is then used to show that expanding agriculture and increasing fuelwood demands are key drivers of deforestation in the region, whereas well-controlled timber exploitation programmes have little or no direct influence on forest-cover reduction at present. Rural and urban population concentrations and fluxes are also identified as strong underlying causes of deforestation in this study.

The Forests of the Congo Basin: State of the Forest 2010

Meat from wild terrestrial or semi-terrestrial animals, termed „bushmeat‟, is a significant source of animal protein in Central African countries, and a crucial component of food security and livelihoods in rural areas. Estimates of bushmeat consumption across the Congo Basin range between 1 million tonnes (Wilkie and Carpenter 1999) and 5 million tonnes (Fa et al. 2003) and harvest rates are estimated to range from 23 to 897 kg/km 2 /year (Nasi et al. 2008). Many sustainability assessments focusing on tropical forest wildlife in the region have warned about the increasing unsustainability of hunting and associated ecological impacts (e.g. examples within Bennett and Robinson, 2000).The term “value chain” is useful to understand the activities involved in bringing a product from the forest, through processing and production, to delivery to final consumers and ultimately disposal (Kaplinsky & morris, 2000). Value chain analysis is a conceptual framework for mapping and categorizing the economic, social and environmental processes. It helps to understand how and where enterprises and institutions are positioned in chains, and to identify opportunities and possible leverage points for upgrading. This analysis encompasses the organization, coordination, equity, power relationships, linkages and governance between organizations and actors. Photo 7.1: Kola nuts (Cola acuminata) for sale in a market in Kisangani, DRC

Land Cover Change Monitoring Using Landsat MSS/TM Satellite Image Data over West Africa between 1975 and 1990

Monitoring land cover changes from the 1970s in West Africa is important for assessing the dynamics between land cover types and understanding the anthropogenic impact during this period. Given the lack of historical land cover maps over such a large area, Landsat data is a reliable and consistent source of information on land cover dynamics from the 1970s. This study examines land cover changes occurring between 1975 and 1990 in West Africa using a systematic sample of satellite imagery. The primary data sources for the land cover classification were Landsat Multispectral Scanner (MSS) for 1975 and Landsat Thematic Mapper (TM) for the 1990 period. Dedicated selection of the appropriate image data for land cover change monitoring was performed for the year 1975. Based on this selected dataset, the land cover analysis is based on a systematic sample of 220 suitable Landsat image extracts (out of 246) of 20 km × 20 km at each one degree latitude/longitude intersection. Object-based classification, originally dedicated for Landsat TM land cover change monitoring and adapted for MSS, was used to produce land cover change information for four different land cover classes: dense tree cover, tree cover mosaic, other wooded land and other vegetation cover. Our results reveal that in 1975 about 6% of West Africa was covered by dense tree cover complemented with 12% of tree cover mosaic. Almost half of the area was covered by other wooded land and the remaining 32% was represented by other vegetation cover. Over the 1975–1990 period, the net annual change rate of dense tree cover was estimated at −0.95%, at −0.37% for the other wooded land and very low for tree cover mosaic (−0.05%). On the other side, other vegetation cover increased annually by 0.70%, most probably due to the expansion of agricultural areas. This study demonstrates the potential of Landsat MSS and TM data for large scale land cover change assessment in West Africa and highlights the importance of consistent and systematic data processing methods with targeted image acquisition procedures for long-term monitoring.

Les Forêts du Bassin du Congo. Etat des Forêts 2013

Le rôLe de La faune dans Le cadre de La sécurité aLimentaire en afrique centraLe : une menace pour La biodiversité ?Au cours des vingt dernières années, les six pays forestiers du bassin du Congo ont conçu et adopté des politiques forestières dans le but, d’une part, de réduire la pauvreté notamment en milieu rural et, d’autre part, de contribuer à l’amélioration de leurs économies nationales et de promouvoir la gestion responsable de la diversité biologique. En effet, dans la région, la gestion des forêts intervient dans un contexte de pauvreté rurale généralisée : on estime que plus de 58 % de ces populations vivent en dessous du seuil de pauvreté (avec 2

Multi-Sensor Monitoring System for Forest Cover Change Assessment in Central Africa

/jour), la majorité d’entre elles habitant dans des zones où la forêt tient une place prédominante (World Bank, 2010). Au fil des années, les nouvelles lois ont permis d’améliorer considérablement les méthodes de gestion des forêts. On a constaté une forte augmentation du nombre de concessions forestières gérées au moyen de plans d’aménagement forestier et, surtout, un accroissement des impôts collectés par le Trésor public (Eba’a Atyi et al., 2009). Cependant, la grande majorité de ces réformes politiques se sont concentrées sur les activités forestières industrielles et orientées vers l’exportation, en négligeant la production par sciage artisanal, à plus petite échelle et vendue en grande partie sur les marchés intérieurs et régionaux. Les titres d’exploitation à petite échelle qui autorisent les citoyens à abattre un nombre limité d’arbres, généralement pour leurs besoins personnels et à des fins non commerciales, sont en effet inclus dans tous les cadres légaux de la région. Cependant, ils ne sont pas adaptés aux besoins actuels des scieurs artisanaux et, à ce titre, ils sont rarement sollicités. Par conséquent, le secteur domestique du bois reste en grande partie informel en dépit de son importance. Ses impacts économiques, écologiques et sociaux sont méconnus des ministères et ne sont pas pris en compte dans les statistiques nationales et internationales. Par exemple, pour l’année 2007, les statistiques officielles faisaient état d’une production de bois en Afrique centrale d’environ 8,4 millions de m3 (Eba’a Atyi et al., 2009), le Gabon et le Cameroun étant les plus gros producteurs et la République démocratique du Congo (RDC) le plus petit d’entre eux. Cependant, l’ensemble des données nationales et internationales, notamment celles de la FAOSTAT, de l’UN Comtrade22 ou de l’OIBT, ne concernaient que la production du secteur forestier industriel et orienté vers l’exportation.

Object-based method for automatic forest change detection

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 Commissions 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.

Identifying Forest Dynamics for Change Detection Using Multitemporal SPOT Imagery

A new method has been developed in order to automatically detect land cover changes in forested areas on a multitemporal dataset. From a multitemporal segmentation on the calibrated reflectance of all images, unchanged but especially the changed stands are accurately delineated. Stands are characterized by features extracted from the reflectance difference images. As these features for the changed objects will appear as outliers with respect to the ones for unchanged objects, they are identified through a multivariate iterative trimming procedure. The method, which was tested in eastern Belgian forest using three SPOT HRV images covering a decade, could detect accurately clearcuts and regenerations on both coniferous and hardwood. The performance of this method of change detection, measured by the detection accuracy, was proved to be higher (85 to 95 %) than a particular multidate classification, named RGB-NDVI (49 to 65%). The originality of this study is (i) the fact that an object-based approach is used instead of the classical pixel-based methods, and (ii) the automation of the process.

Forest change detection by statistical object-based method

Change detection based on satellite remote sensing relies on the comparison of multispectral reflectance acquired at different dates. A major problem in forest change detection is to separate the signal change related to forest conversion from other sources of noise such as the ever-changing state of a forest stand from the regrowth to the mature age. This research aims at characterizing spectral reflectance over the whole forest succession in order to quantify the reflectance dynamics and to identify the most appropriate spectral signal thanks to a robust object-based change detection approach. From a large sample of spruce stands, spectral trajectories of forest cycle were derived for green, red and NIR reflectances and the NDVI derived from SPOT-HRVIR images. These trajectories were found typical for spruce stands and consistent between satellite images. Based on the object-based change detection method using image differencing, the combination of all spectral bands was proved more efficient to detect changes and more discriminant to distinguish them than any single spectral band or NDVI. Two forest changes, namely the clearing and the regrowth, have been distinguished based on multivariate analysis for different temporal resolutions. Finally, tills study emphasized the need of a better characterization of changes of interest for defining appropriate forest monitoring systems.