DOI: 10.1016/j.jag.2015.01.004
Scopus记录号: 2-s2.0-84988910622
论文题名: A lake detection algorithm (LDA) using Landsat 8 data: A comparative approach in glacial environment
作者: Bhardwaj A ; , Singh M ; K ; , Joshi P ; K ; , Snehmani, Singh S ; , Sam L ; , Gupta R ; D ; , Kumar R
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2015
卷: 38 起始页码: 150
结束页码: 163
语种: 英语
英文关键词: GIS
; Glacial lakes
; Landsat-8
; NDWI
; Remote sensing
Scopus关键词: algorithm
; ASTER
; comparative study
; detection method
; digital elevation model
; GIS
; glacial environment
; glacial lake
; Landsat
; outburst
; pixel
; remote sensing
; satellite data
英文摘要: Glacial lakes show a wide range of turbidity. Owing to this, the normalized difference water indices (NDWIs) as proposed by many researchers, do not give appropriate results in case of glacial lakes. In addition, the sub-pixel proportion of water and use of different optical band combinations are also reported to produce varying results. In the wake of the changing climate and increasing GLOFs (glacial lake outburst floods), there is a need to utilize wide optical and thermal capabilities of Landsat 8 data for the automated detection of glacial lakes. In the present study, the optical and thermal bandwidths of Landsat 8 data were explored along with the terrain slope parameter derived from Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model Version2 (ASTER GDEM V2), for detecting and mapping glacial lakes. The validation of the algorithm was performed using manually digitized and subsequently field corrected lake boundaries. The pre-existing NDWIs were also evaluated to determine the supremacy and the stability of the proposed algorithm for glacial lake detection. Two new parameters, LDI (lake detection index) and LF (lake fraction) were proposed to comment on the performances of the indices. The lake detection algorithm (LDA) performed best in case of both, mixed lake pixels and pure lake pixels with no false detections (LDI = 0.98) and very less areal underestimation (LF = 0.73). The coefficient of determination (R2) between areal extents of lake pixels, extracted using the LDA and the actual lake area, was very high (0.99). With understanding of the terrain conditions and slight threshold adjustments, this work can be replicated for any mountainous region of the world. © 2015 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79458
Appears in Collections: 气候变化事实与影响
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作者单位: Snow and Avalanche Study Establishment, Sector 37A, Chandigarh, India; Department of Natural Resources, TERI University, New Delhi, India; Motilal Nehru National Institute of Technology, Allahabad, UP, India; Department of Environmental Sciences, Sharda University, Greater Noida, UP, India; Defence Research & Development Organisation, New Delhi, India
Recommended Citation:
Bhardwaj A,, Singh M,K,et al. A lake detection algorithm (LDA) using Landsat 8 data: A comparative approach in glacial environment[J]. International Journal of Applied Earth Observation and Geoinformation,2015-01-01,38