Application of interferometric method and radar remote sensing images to estimate the depth of snow and water discharge, Case Study: (Yamchie Basin)

Document Type : Original Article

Authors

1 M.Sc. in Remote Sensing and GIS, Faculty of Planning and Environmental Sciences, Tabriz University, Tabriz, Iran.

2 Assistant Professor, Department of Remote Sensing and GIS, Faculty of Planning and Environmental Sciences, Tabriz University, Tabriz, Iran.

Abstract

Snow cover in mountainous basins is known as an important and reliable fresh water resource. Due to the physical conditions of the mountainous environments, it is believed that snow can measurement is still challenge based on traditional methods and techniques. In order to deal with this issue, remote sensing satellite images can be considered as efficient method for identifying snow covers and computing their depth and volume. Within the current research, the Landsat 8 satellite images were employed to detect snow cover surface for the Yamchi basin using NDSI indices and object based image analysis methods. The ground control points were applied to compute the accuracy of results while the overall accuracy was computed to be about 90%. In order to measure the snow cover depth and compute water discharge, the Sentinel A1 and D-InSAR satellite imagery were employed. In context of detection snow cover using Landsat 8 images, the satellite images for September indicated no snow cover for the study which accordingly employed as basic data for comparing against winter season satellite images and accordingly computing the snow cover and depth using the interferometry approaches. The results were verified by ground data.The correlation coefficients were computed to be about 85%. With confidence in the accuracy of the maps, the snow volume was also obtained through surface and snow depth maps. Accordingly, the correlation between snow depth of ground control points the obtained snows depth from differential radar interference were employed to compute water discharge of the study area.

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References

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Iran-Water Resources Research
Volume 15, Issue 1
February 2019
Pages 341-355

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History

  • Receive Date: 23 December 2017
  • Revise Date: 03 January 2019
  • Accept Date: 03 January 2019

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