Publications des scientifiques de l'IRD

Fayad I., Baghdadi N., Gond V., Bailly J. S., Barbier Nicolas, El Hajj M., Fabre F. (2014). Coupling potential of ICESat/GLAS and SRTM for the discrimination of forest landscape types in French Guiana. International Journal of Applied Earth Observation and Geoinformation, 33, p. 21-31. ISSN 0303-2434.

Titre du document
Coupling potential of ICESat/GLAS and SRTM for the discrimination of forest landscape types in French Guiana
Année de publication
2014
Type de document
Article référencé dans le Web of Science WOS:000340979300003
Auteurs
Fayad I., Baghdadi N., Gond V., Bailly J. S., Barbier Nicolas, El Hajj M., Fabre F.
Source
International Journal of Applied Earth Observation and Geoinformation, 2014, 33, p. 21-31 ISSN 0303-2434
The Shuttle Radar Topography Mission (SRTM) has produced the most accurate nearly global elevation dataset to date. Over vegetated areas, the measured SRTM elevations are the result of a complex interaction between radar waves and tree crowns. In this study, waveforms acquired by the Geoscience Laser Altimeter System (GLAS) were combined with SRTM elevations to discriminate the five forest landscape types (LTs) in French Guiana. Two differences were calculated: (1) penetration depth, defined as the GLAS highest elevations minus the SRTM elevations and (2) the GLAS centroid elevations minus the SRTM elevations. The results show that these differences were similar for the five LTs, and they increased as a function of the GLAS canopy height and of the SRTM roughness index. Next, a Random Forest (RF) classifier was used to analyze the coupling potential of GLAS and SRTM in the discrimination of forest landscape types in French Guiana. The parameters used in the RF classification were the GLAS canopy height, the SRTM roughness index, the difference between the GLAS highest elevations and the SRTM elevations and the difference between the GLAS centroid elevations and the SRTM elevations. Discrimination of the five forest landscape types in French Guiana was possible, with an overall classification accuracy of 81.3% and a kappa coefficient of 0.75. All forest LTs were well classified with an accuracy varying from 78.4% to 97.5%. Finally, differences of near coincident GLAS waveforms, one from the wet season and one from the dry season, were analyzed. The results showed that the open forest LT (LT12), in some locations, contains trees that lose leaves during the dry season. These trees allow LT12 to be easily discriminated from the other LTs that retain their leaves using the following three criteria: (1) difference between the GLAS centroid elevations and the SRTM elevations, (2) ratio of top energy in the wet season to top energy in the dry season, or (3) ratio of ground energy in the wet season to ground energy in the dry season.
Plan de classement
Etudes, transformation, conservation du milieu naturel [082] ; Télédétection [126]
Description Géographique
GUYANE FRANCAISE
Localisation
Fonds IRD [F B010062524]
Identifiant IRD
fdi:010062524
Contact