| 1. |
- Bhardwaj, Anshuman, et al.
(författare)
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A lake detection algorithm (LDA) using Landsat 8 data : A comparative approach in glacial environment
- 2015
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Ingår i: International Journal of Applied Earth Observation and Geoinformation. - : Elsevier BV. - 1569-8432 .- 1872-826X. ; 38, s. 150-163
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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| 2. |
- Bhardwaj, Anshuman, et al.
(författare)
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Applicability of Landsat 8 data for characterizing glacier facies and supraglacial debris
- 2015
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Ingår i: International Journal of Applied Earth Observation and Geoinformation. - : Elsevier BV. - 1569-8432 .- 1872-826X. ; 38, s. 51-64
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Tidskriftsartikel (refereegranskat)abstract
- 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
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| 3. |
- Singh, Mritunjay Kumar, et al.
(författare)
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High resolution DEM generation for complex snow covered Indian Himalayan Region using ADS80 aerial push-broom camera : a first time attemp7
- 2015
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Ingår i: Arabian Journal of Geosciences. - : Springer Science and Business Media LLC. - 1866-7511 .- 1866-7538. ; 8:3, s. 1-12
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Tidskriftsartikel (refereegranskat)abstract
- Updated and Accurate Digital Elevation Model (DEM) of snow covered and glaciated mountainous area is essential for many applications such as avalanche hazard and numerical modelling of mass movements or mapping of terrain changes. The best high resolution terrain product available for Himalayan region is the DEM, with a spatial resolution of 10 m, generated using Cartosat-1 stereo ortho-kit data. Even this spatial resolution is insufficient for many applications like avalanche hazard mapping or forecasting in complex mountainous terrain. This study reports the process of high spatial resolution (1 m) DEM generation for Manali and nearby areas using digital aerial photogrammetric survey data of 40 cm Ground Sampling Distance (GSD), captured through airborne ADS80 push-broom camera for the first time in Indian Himalayas. This DEM was also evaluated with Differential Global Positioning System (DGPS) points for accuracy assessment. The ADS80 DEM gave Root Mean Square Error (RMSE) of ∼<1 m and Linear Error, at 90 % confidence interval (LE 90) of 1.36 m in comparison with the DGPS points.
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| 4. |
- Snehmani, Snehmani, et al.
(författare)
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Modelling the hypsometric seasonal snow cover using meteorological parameters
- 2015
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Ingår i: Journal of Spatial Science. - : Informa UK Limited. - 1449-8596 .- 1836-5655. ; 60:1, s. 51-64
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Tidskriftsartikel (refereegranskat)abstract
- This study established a decadal correlation between meteorological observations (temperature and snowfall) and satellite-derived seasonal snow cover for a glacier catchment. The study area was classified into 10 elevation zones. The time period for considering climatic variables was from the start of the significant fresh snowfall of the new season to the date of satellite image acquisition. The snowfall inputs from the five meteorological stations at different altitudes were interpolated for the entire catchment using a discretised thin-plate spline technique. A local temperature lapse rate for this specific time period was calculated. It was applied throughout the catchment for interpolating the temperature, which was further used to refine the interpolated snowfall. Such a hypsometric approach along with third-order polynomial curve fitting (R2=0.998) finally gave an equation for estimating percent snow-covered area for different elevation zones with a good accuracy and very low average RMSE (Root Mean Square Error) of 3.16 percent.
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| 5. |
- Snehmani, Snehmani, et al.
(författare)
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Remote sensing of mountain snow using active microwave sensors : a review
- 2015
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Ingår i: Geocarto International. - : Informa UK Limited. - 1010-6049 .- 1752-0762. ; 30:1, s. 1-27
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Tidskriftsartikel (refereegranskat)abstract
- This work provides an overview of various methods for estimating snow cover and properties in high mountains using remote sensing techniques involving microwaves. Satellite-based remote sensing with its characteristics such as synoptic view, repetitive coverage and uniformity over large areas has great potential for identifying the temporal snow cover. Many sensors have been used in the past with various algorithms and accuracies for this purpose. These methods have been improving with the use of Synthetic Aperture Radar sensors, working in different microwave frequencies, polarisation and acquisition modes. The limitations, advantages and drawbacks are illustrated while error sources and strategies on how to ease their impacts are also reviewed. An extensive list of references, with an emphasis on studies since 1990s, allows the reader to delve into specific topics
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