Broad-scale spatial pattern of forest landscape types in the Guiana Shield, 2011

The dataset identifies, characterizes and maps distinct forest landscape types within the evergreen lowland rainforest at the subcontinental scale.

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GEMET - INSPIRE themes, version 1.0 INSPIRE themes

GEMET - Concepts, version 2.4

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Supplemental Information: Bibliography: Gond V., Freycon V., Molino J.F., Brunaux O., Ingrassia F., Joubert P., Pekel J.F., Prévost M.F., Thierron V., Trombe P.J., Sabatier D.. 2011. International journal of applied earth observation and geoinformation, 13 (3) : 357-367.

Reference system identifier: EPSG / WGS 84 / UTM zone 22N (EPSG:32622) / 7.9

Distribution format

OnLine resource: Gond V., Freycon V., Molino J.F., Brunaux O., Ingrassia F., Joubert P., Pekel J.F., Prévost M.F., Thierron V., Trombe P.J., Sabatier D.. 2011. International journal of applied earth observation and geoinformation, 13 (3) : 357-367. ( WWW:LINK-1.0-http--related )

Statement: This dataset is based on the analysis of a 1 year daily data set (from January 1st to December 31st. 2000) from the VEGETATION sensor onboard the SPOT4 satellite (1 km spatial resolution). We interpreted remotely sensed landscape classes (RSLC) from field and high resolution remote sensing data of 21 sites in French Guiana. We crossanalyzed remote sensing data, field observations and environmental data using multivariate analysis. We obtained 33 remotely sensed landscape classes (RSLC) among which five forestRSLC representing 78 % of the forested area. The latter were classified as different broad forest landscape types according to a gradient of canopy openness. Their mapping revealed a new and meaningful broadscale spatial pattern of forest landscape types. At the scale of the Guiana Shield. we observed a spatial patterns similarity between climatic and forest landscape types. The two most open forestRSLCs were observed mainly within the northwest to southeast dry belt. The three other forest RSLCs were observed in wetter and less anthropized areas, particularly in the newly recognized “Guianan dense forest arch”. Better management and conservation policies as well as improvement of biological and ecological knowledge require accurate and stable representations of the geographical components of ecosystems.