Exploration of Glacier Surface FaciesMapping Techniques Using Very High Resolution Worldview-2 Satellite Data

摘要

Glaciers exhibit a wide range of surface facies that can be analyzed as proxies for mass balance studies. Along with hydrological implications, these are in turn quintessential indicators of climate change. Moderate-to-high-resolution (MHR) data for mapping glacier facies have been used previously; however, the use of very high-resolution (VHR) data for this purpose has not yet been fully exploited. This study uses WorldView-2 (WV-2) VHR data to classify available glacier surface facies on the Samudra Tapu glacier, located in the Himalayas. Traditional methods of facies classification using conventional multispectral data involve band rationing and/or supervised classification. This study explores glacier surface facies classification by using the unique bands available in the multispectral range of WV-2 to develop customized spectral index ratios (SIRs) within an object-oriented domain. The results of this object-oriented classification (OOC) are then compared with five popular supervised classification algorithms using error matrices to determine the classification accuracies. The overall accuracy achieved by the object-based image analysis (OBIA) approach is 97.14% (?o = 0.96), and the highest overall accuracy among the pixel-based classification methods is 74.28% (?o = 0.70). The present results show that the object-based approach is far more accurate than the pixel-based classification techniques. Further studies should test the robustness of the object-oriented domain for the classification of glacier surface facies using customized sensor-specific as well as transferable indices, and the resultant accuracies.