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|Title:||Global Monitoring of Tropical Forest Cover Changes by Means of a Sample Approach and Object-based Classification of Multi-scene Landsat Imagery: Pre-processing and First Results|
|Authors:||BODART Catherine; BEUCHLE Rene'; SIMONETTI Dario; EVA Hugh; RASI Rastislav; CARBONI S.; BRINK Andreas; STIBIG Hans-Jurgen; ACHARD Frederic; MAYAUX Philippe|
|Citation:||Proceedings of the 33rd International Symposium on Remote Sensing of Environment (ISRSE)|
|Type:||Articles in periodicals and books|
|Abstract:||At the JRC (TREES-3 and MONDE projects), a methodology is developed to monitor the tropical forest cover in Latin America, Southeast Asia and Africa. The results will provide quantitative measurements of changes for the year 1990 and 2000 and will be a major input for the FAO FRA 2010 remote sensing survey (Global Forest Resources Assessment). The project is based on object-based classification of a systematic sampling of Landsat imagery at each longitude and latitude intersect. The area covered at each sample site is a box of 20km x 20km for which Landsat data are used for both dates. Prior to the classification and the change detection, a robust approach applicable to a very large amount of data had to be developed to put the multi-temporal and multi-scene data on the same radiometric scale. The paper will present all the pre-processing steps applied to a total of 4000 image pairs. Starting with the conversion to TOA reflectance, the image normalization will be detailed as well as the haze correction process. A two-level segmentation is applied on the multi-date imagery. The results of these processing steps and the first tests of supervised classification based on a global database of spectral signatures will be presented.|
|JRC Institute:||Sustainable Resources|
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