The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLIV-3/W1-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIV-3/W1-2020, 59–63, 2020
https://doi.org/10.5194/isprs-archives-XLIV-3-W1-2020-59-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIV-3/W1-2020, 59–63, 2020
https://doi.org/10.5194/isprs-archives-XLIV-3-W1-2020-59-2020

  18 Nov 2020

18 Nov 2020

INVESTIGATION OF CRYOSPHERE DYNAMICS VARIATIONS IN THE UPPER INDUS BASIN USING REMOTE SENSING AND GIS

J. Iqbal1, M. Ali2, A. Ali3, D. Raza2, F. Bashir4, F. Ali5, S. Hussain2, and Z. Afzal2 J. Iqbal et al.
  • 1Department of Environmental Engineering, China University of Geosciences, Wuhan, China
  • 2State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University 430079, China
  • 3Institu te of Geographical Information Systems, National University of Sciences and Technology, Islamabad, Pakistan
  • 4Department of Meteorology, COMSATS University Islamabad (CUI), Pakistan
  • 5Aerospace Information Research Institute, University of Chinese Academy of Science, China

Keywords: Snow Cover, Remote Sensing, GIS, Snow Mass Balance, Upper Indus Basin

Abstract. Glaciers are storehouses for freshwater. Glaciers Monitoring is one of the most important research areas especially when climate change has been accelerated snowmelt process. The major goal of research was to find snow cover trend for glaciated regions of Pakistan followed by estimation of snow mass balance. The area chosen for it was Upper Indus basin, which includes ranges of Hindukush, Karakoram and Himalayas extended in Pakistan, India and China. This region exhibits high topographic relief and climate change variability. Snow cover trend analysis was performed for eleven years ranging from 2004 to 2014 using Moderate Resolution Imaging Spectroradiometer (MODIS) data imagery product with daily temporal resolution. These results were combined with respective year’s average monthly temperature. Further quantitative analysis was performed to relate presence of greater vegetation as an indication of greater snowmelt using Landsat Imagery for these years. Snow mass balance curves reveal that glaciers are regaining their mass balance after losing mass balance in middle of last decade. In addition to that, only freely available data is used for this study. This purpose behind this approach is to prove RS and GIS has an effective and low-cost tool for snow cover monitoring, also mass balance calculations. Continuous monitoring of snow cover dynamics is effective for prediction and mitigation of hazards associated with areas in proximity of glaciated regions. One common hazard is glacial lake outburst phenomenon, which cause severe flash flooding in downstream areas. Year 2004 has the lowest mass snow balance and 2014 has the highest snow mass balance. These different parameters were analysed and results show that snow start melting in months of May and June and faster melting rate observed in months of July and August. With the advancement in computing technologies, it has been easier for computers to handle and manipulate massive datasets. Remote sensing has proved to be an excellent tool for extraction of data from glaciers, snow and oceans for remote areas. In particular, snow cover/snowmelt can tell us continuously changing melting patterns, which helps concerned authorities to take necessary measures for preserving these storehouses of water and to mitigate effect of global warming.