Abstract
Mapping of surface glacier facies has been a part of several glaciological applications. The study of glacier facies in the Himalayas has gained momentum in the last decade owing to the implications imposed by these facies on the melt characteristics of the glaciers. Some of the most commonly reported surface facies in the Himalayas are snow, ice, ice mixed debris, and debris. The precision of the techniques used to extract glacier facies is of high importance, as the result of many cryospheric studies and economic reforms rely on it. An assessment of a customized semi-automated protocol against conventional and advanced mapping algorithms for mapping glacier surface facies is presented in this study. Customized spectral index ratios (SIRs) are developed for effective extraction of surface facies using thresholding in an object-based environment. This method was then tested on conventional and advanced classification algorithms for an evaluation of the mapping accuracy for five glaciers located in the Himalayas, using very high-resolution WorldView-2 imagery. The results indicate that the object-based image analysis (OBIA) based semi-automated SIR approach achieved a higher average overall accuracy of 87.33% (κ = 0.85) than the pixel-based image analysis (PBIA) approach. Among the conventional methods, the Maximum Likelihood performed the best, with an overall accuracy of 78.71% (κ = 0.75). The Constrained Energy Minimization, with an overall accuracy of 68.76% (κ = 0.63), was the best performer of the advanced algorithms. The advanced methods greatly underperformed in this study. The proposed SIRs show a promise in the mapping of minor features such as crevasses and in the discrimination between ice-mixed debris and debris. We have efficiently mapped surface glacier facies independently of short-wave infrared bands (SWIR). There is a scope for the transferability of the proposed SIRs and their performance in varying scenarios.
Highlights
Snow accumulated on a glacier will metamorphose into ice on exposure to meteorological and geological alterations
Following the similarity of the extracted scaled spectral reflectance curve to Shukla et al [90] and the criteria for differentiation between facies based on their reduced reflectance properties [40], this study identified the spectral properties of the observable facies across all five glaciers with relative ease
The object-based image analysis (OBIA) approach permitted the coupling of segmentation and band ratioing to deliver three customized spectral index ratios that have the potential to be transferable across glaciered regions
Summary
Snow accumulated on a glacier will metamorphose into ice on exposure to meteorological and geological alterations. This transformation leads to superficial expressions on the surface of the glacier and these expressions are as diverse in attributes as the processes that mold this transformation are intricate. Several facies on annexation categorically fall under two general zonations of a glacier, viz., the zone of accumulation and the zone of ablation. This study uses the term surface glacier facies
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