A lake detection algorithm (LDA) using Landsat 8 data: A comparative approach in glacial environment

Anshuman Bhardwaj, Mritunjay Kumar Singh, P. K. Joshi*, Snehmani, Shaktiman Singh, Lydia Sam, R. D. Gupta, Rajesh Kumar

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

60 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)150-163
Number of pages14
JournalInternational Journal of Applied Earth Observation and Geoinformation
Publication statusPublished - Jun 2015


  • GIS
  • Glacial lakes
  • Landsat-8
  • NDWI
  • Remote sensing


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