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  • 1.
    Bhardwaj, Anshuman
    et al.
    Snow and Avalanche Study Establishment, Defence Research and Development Organization (DRDO), Him Parisar, Sector-37A, Chandigarh.
    Joshi, Prakash C.
    Space Applications Centre, ISRO, Ahmedabad, Atmospheric and Oceanic Sciences Group, Space Applications Centre, Indian Space Research Organisation, Ahmedabad.
    Snehmani, Snehmani
    Snow and Avalanche Study Establishment, Defence Research and Development Organization (DRDO), Him Parisar, Sector-37A, Chandigarh.
    Sam, Lydia
    Department of Environmental Science, Sharda University.
    Singh, Mritunjay Kumar
    Snow and Avalanche Study Establishment, Defence Research and Development Organization (DRDO), Him Parisar, Sector-37A, Chandigarh.
    Singh, Shaktiman
    Department of Environmental Science, School of Basic Sciences and Research, Sharda University, Greater Noida.
    Kumar, Ramesh
    Department of Environmental Science, School of Basic Sciences and Research, Sharda University, Greater Noida.
    Applicability of Landsat 8 data for characterizing glacier facies and supraglacial debris2015In: International Journal of Applied Earth Observation and Geoinformation, ISSN 0303-2434, Vol. 38, p. 51-64Article in journal (Refereed)
    Abstract [en]

    present work evaluates the applicability of operational land imager (OLI) and thermal infrared sensor (TIRS) on-board Landsat 8 satellite. We demonstrate an algorithm for automated mapping of glacier facies and supraglacial debris using data collected in blue, near infrared (NIR), short wave infrared (SWIR) and thermal infrared (TIR) bands. The reflectance properties invisible and NIR regions of OLI for various glacier facies are in contrast with those in SWIR region. Based on the premise that different surface types (snow, ice and debris) of a glacier should show distinct thermal regimes, the 'at-satellite brightness temperature' obtained using TIRS was used as a base layer for developing the algorithm. This base layer was enhanced and modified using contrasting reflectance properties of OLI bands. In addition to fades and debris cover characterization, another interesting outcome of this algorithm was extraction of crevasses on the glacier surface which were distinctly visible in output and classified images. The validity of this algorithm was checked using field data along a transect of the glacier acquired during the satellite pass over the study area. With slight scene-dependent threshold adjustments, this work can be replicated for mapping glacier facies and supraglacial debris in any alpine valley glacier

  • 2.
    Bhardwaj, Anshuman
    et al.
    Snow and Avalanche Study Establishment, Defence Research and Development Organization (DRDO), Him Parisar, Sector-37A, Chandigarh.
    Singh, Mritunjay Kumar
    Snow and Avalanche Study Establishment, Defence Research and Development Organization (DRDO), Him Parisar, Sector-37A, Chandigarh.
    Joshi, Prakash C.
    Space Applications Centre, ISRO, Ahmedabad, Atmospheric and Oceanic Sciences Group, Space Applications Centre, Indian Space Research Organisation, Ahmedabad.
    Snehmani, Snehmani
    Snow and Avalanche Study Establishment, Defence Research and Development Organization (DRDO), Him Parisar, Sector-37A, Chandigarh.
    Singh, Shaktiman
    Department of Environmental Science, School of Basic Sciences and Research, Sharda University, Greater Noida.
    Sam, Lydia
    Department of Environmental Science, Sharda University.
    Gupta, R.D.
    Snow and Avalanche Study Establishment, Defence Research and Development Organization (DRDO), Him Parisar, Sector-37A, Chandigarh.
    Kumar, Rajesh
    Department of Environmental Science, School of Basic Sciences and Research, Sharda University, Greater Noida.
    A lake detection algorithm (LDA) using Landsat 8 data: A comparative approach in glacial environment2015In: International Journal of Applied Earth Observation and Geoinformation, ISSN 0303-2434, Vol. 38, p. 150-163Article in journal (Refereed)
    Abstract [en]

    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 (R-2) 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.

  • 3.
    Bhardwaj, Anshuman
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology. Department of Environmental Science, Sharda University.
    Singh, Shaktiman
    Department of Environmental Science, Sharda University,.
    Sam, Lydia
    Department of Environmental Science, Sharda University,.
    Joshi, PK
    School of Environmental Sciences, Jawaharlal Nehru University, New Delhi.
    Bhardwaj, Akanksha
    Banaras Hindu University.
    Martín-Torres, Javier F.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology. Instituto Andaluz de Ciencias de la Tierra (CSIC-UGR).
    Kumar, Rajesh
    Department of Environmental Science, Sharda University.
    A review on remotely sensed land surface temperature anomaly as an earthquake precursor2017In: International Journal of Applied Earth Observation and Geoinformation, ISSN 0303-2434, Vol. 63, p. 158-166Article in journal (Refereed)
    Abstract [en]

    The low predictability of earthquakes and the high uncertainty associated with their forecasts make earthquakes one of the worst natural calamities, capable of causing instant loss of life and property. Here, we discuss the studies reporting the observed anomalies in the satellite-derived Land Surface Temperature (LST) before an earthquake. We compile the conclusions of these studies and evaluate the use of remotely sensed LST anomalies as precursors of earthquakes. The arrival times and the amplitudes of the anomalies vary widely, thus making it difficult to consider them as universal markers to issue earthquake warnings. Based on the randomness in the observations of these precursors, we support employing a global-scale monitoring system to detect statistically robust anomalous geophysical signals prior to earthquakes before considering them as definite precursors.

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