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

Desclée, Baudouin; Simonetti, Dario; Mayaux, Philippe; Achard, Frédéric

doi:10.1109/jstars.2013.2240263

Cited by 14 publications

(8 citation statements)

References 23 publications

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“…Polygons smaller than 3 ha were merged with their neighbors (Raši et al ., ). An automatic process of object‐based change detection and classification was designed for Landsat images (Raši et al ., ) and the process adapted for alternative imagery (Desclée et al ., ).…”

Section: Methodsmentioning

confidence: 99%

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

Achard

Rene

Mayaux

et al. 2014

Global Change Biology

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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.

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Section: Methodsmentioning

confidence: 99%

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

Achard

Rene

Mayaux

et al. 2014

Global Change Biology

Self Cite

486

383

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show abstract

“…This includes different steps using multi-date Landsat imagery [25,26]: visual screening of best available images from the entire Landsat open archive, co-registration, calibration, cloud and shadow masking, segmentation, change detection and classification [25,27]. This processing chain was adapted for the DMC and SPOT samples used in the 2010 epoch [28]. The minimum mapping unit was 5 ha.…”

Section: Methodsmentioning

confidence: 99%

State and evolution of the African rainforests between 1990 and 2010

Mayaux

Pekel

Desclée

et al. 2013

Phil. Trans. R. Soc. B

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160

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This paper presents a map of Africa's 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.

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“…In order to exploit multi-sensor images (SPOT, DMC/Deimos and even MSS data), the processing chain has again been adapted to be more flexible to spectral content differences and by using the most appropriate object features for the supervised classification [34]. Derived from this last approach, our 1975-1990 processing chain is working in three steps: (1) multi-date segmentation; (2) change detection; and (3) 1975 land cover classification ( Figure 6).…”

Section: Land Cover Classification and Change Detection Proceduresmentioning

confidence: 99%

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

et al. 2014

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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 OPEN ACCESS Remote Sens. 2014, 6 659 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.

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

Cited by 14 publications

References 23 publications

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

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

State and evolution of the African rainforests between 1990 and 2010

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

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