کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10113981 | 1621183 | 2018 | 12 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Optimising NDWI supraglacial pond classification on Himalayan debris-covered glaciers
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
علوم زمین و سیارات
کامپیوتر در علوم زمین
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چکیده انگلیسی
The ability of medium-resolution (10-30â¯m) satellite imagery to delineate the size and persistence of ponds on debris-covered glaciers is a topic of recent interest as it has become apparent through the use of fine-resolution products that smaller ponds have often been neglected. In this study, we performed a quantitative analysis of pond detection using a normalised difference water index (NDWI) applied to several widely used satellite sensors, which offer multispectral information at high radiometric precision. These data include: RapidEye (5â¯m spatial resolution), Sentinel-2 Multispectral Instrument (MSI) (10-20â¯m), and Landsat 8 Operational Land Imager (OLI) multispectral imagery (30â¯m). We demonstrate a method to derive an optimum NDWI value for pond classification using a subset reference dataset of 285 ponds classified using fine-resolution (0.5â¯m) imagery. We then applied the optimised NDWI (NDWI-O) to the remaining images to assess pond classification accuracy against a broader reference dataset of 898 ponds. NDWI values calculated using Sentinel-2 imagery showed the best spectral contrast between water and surrounding debris cover, and the strongest relationship with pixel water content (R2â¯=â¯0.56), followed by the RapidEye NDWI (R2â¯=â¯0.45). We conclude that RapidEye and Sentinel-2 imagery is best suited for accurate pond classification using a multispectral classification approach, which is important for quantifying their role in glacier ablation, meltwater regulation, and lake development. By comparison, the impact of using coarse-resolution Landsat 8 imagery to characterise surface water dynamics is minimised when applied to large glacier lakes, where the area-to-perimeter ratio is greater.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Remote Sensing of Environment - Volume 217, November 2018, Pages 414-425
Journal: Remote Sensing of Environment - Volume 217, November 2018, Pages 414-425
نویسندگان
C. Scott Watson, Owen King, Evan S. Miles, Duncan J. Quincey,