DOI: 10.1016/j.jag.2014.04.005
Scopus记录号: 2-s2.0-84904742356
论文题名: Coupling potential of ICESat/GLAS and SRTM for the discrimination of forest landscape types in French Guiana
作者: Fayad I ; , Baghdadi N ; , Gond V ; , Bailly J ; S ; , Barbier N ; , El Hajj M ; , Fabre F
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2014
卷: 33, 期: 1 起始页码: 21
结束页码: 31
语种: 英语
英文关键词: French Guiana
; ICESat/GLAS
; SRTM DEM
; Tropical forest
Scopus关键词: accuracy assessment
; altimeter
; digital elevation model
; dry season
; elevation
; forest canopy
; ICESat
; penetration
; Shuttle Radar Topography Mission
; tropical forest
; waveform analysis
; wet season
; French Guiana
英文摘要: 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 LaserAltimeter 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, contain strees 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. © 2014 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79644
Appears in Collections: 气候变化事实与影响
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作者单位: IRSTEA, UMR TETIS, 500 rue François Breton, 34093 Montpellier cedex 5, France; CIRAD, UPR B and SEF, 34398 Montpellier, France; AgroParisTech, UMR LISAH-TETIS, 34090 Montpellier, France; IRD, UMP AMAP, 34000 Montpellier, France; NOVELTIS, 31670 Labège, France; EADS -Astrium, 31402 Toulouse, France
Recommended Citation:
Fayad I,, Baghdadi N,, Gond V,et al. Coupling potential of ICESat/GLAS and SRTM for the discrimination of forest landscape types in French Guiana[J]. International Journal of Applied Earth Observation and Geoinformation,2014-01-01,33(1)