Monitoring forest areas from continental to territorial levels using a sample of medium spatial resolution satellite imagery

Eva, Hugh; Carboni, Silvia; Achard, Frédéric; Stach, N.; Durieux, Laurent; Faure, Jean-François; Mollicone, Danilo

doi:10.1016/j.isprsjprs.2009.10.008

Cited by 57 publications

(41 citation statements)

References 29 publications

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“…The assessment will have about 13,500 samples over the whole land surface of the Earth, of which about 9,000 samples lie outside deserts for the three dates (1990, 2000 and 2005/2006) [27]. The geo-wiki tool could be used to build confidence of the results of the Remote Sensing Survey and to provide extended validation material for further development of the global survey (e.g., adding year 2010 to the survey) or for intensification at the national level [28].…”

Section: Discussionmentioning

confidence: 99%

Geo-Wiki.Org: The Use of Crowdsourcing to Improve Global Land Cover

et al. 2009

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Global land cover is one of the essential terrestrial baseline datasets available for ecosystem modeling, however uncertainty remains an issue. Tools such as Google Earth offer enormous potential for land cover validation. With an ever increasing amount of very fine spatial resolution images (up to 50 cm × 50 cm) available on Google Earth, it is becoming possible for every Internet user (including non remote sensing experts) to distinguish land cover features with a high degree of reliability. Such an approach is inexpensive and allows Internet users from any region of the world to get involved in this global validation exercise. The Geo-Wiki Project is a global network of volunteers who wish to help improve the quality of global land cover maps. Since large differences occur between existing global land cover maps, current ecosystem and land-use science lacks crucial accurate data (e.g., to determine the potential of additional agricultural land available to grow crops in Africa), volunteers are asked to review hotspot maps of global land cover disagreement and determine, based on what they actually see in Google Earth and their local knowledge, if the land cover maps are correct or incorrect. Their input is recorded in a OPEN ACCESS Remote Sens. 2009, 1 346 database, along with uploaded photos, to be used in the future for the creation of a new and improved hybrid global land cover map.

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Section: Discussionmentioning

confidence: 99%

Geo-Wiki.Org: The Use of Crowdsourcing to Improve Global Land Cover

et al. 2009

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“…The potential to intensify the sampling grid to obtain territorial estimates has already been demonstrated over French Guiana [18]. The sample grid provides 1,230 sample units each initially of 20 km by 20 km, uniformly distributed across the study area.…”

Section: Methodsmentioning

confidence: 99%

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

et al. 2012

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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.

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“…In the early 1990s, the Joint Research Centre (JRC) of the European Commission established forest and land cover monitoring systems based on Landsat sample sites over the tropics within the Tropical Ecosystem Environment Observation by Satellite (TREES) project [17,18]. A regular sampling of Landsat image extracts based on a rectangular grid has been developed and applied by the JRC in collaboration with the Food and Agriculture Organization's (FAO) Remote Sensing Survey (RSS) of the Forest Resources Assessment (FRA) [19,20].…”

Section: Introductionmentioning

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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Monitoring forest areas from continental to territorial levels using a sample of medium spatial resolution satellite imagery

Cited by 57 publications

References 29 publications

Geo-Wiki.Org: The Use of Crowdsourcing to Improve Global Land Cover

Geo-Wiki.Org: The Use of Crowdsourcing to Improve Global Land Cover

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

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

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