A object-oriented glacier mapping method based on multi-temporal Landsat images

Li, Jun Li; Bao, Anming; Huang, Qi

doi:10.1117/12.2031083

Cited by 2 publications

(3 citation statements)

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“…Optical, Thermal and DEM derived parameters) while working on near homogeneous objects. Therefore, several studies could successfully demonstrate the delineation of debris cover glaciers within in an object-based environment (Rastner et al 2014;Bajracharya, Maharjan, and Shrestha 2014;Bajracharya and Shrestha 2011;Robson et al 2015;Li, Bao, and Huang 2013;Biddle 2015;Jawak, Jadhav, and Luis 2016). (Rastner et al 2014) presented a comparative study of PBIA and OBIA for debris cover classification in three test regions, namely: Coasta Mountains of Canada, Watkin range of Greenland, and Nepal Himalaya.…”

Section: Object-oriented Image Analysismentioning

confidence: 99%

“…However, the amount of manual correction required is not known and need further work on this (Robson et al 2015). Another study by Li, Bao, and Huang (2013) delineated full extent of debris cover glacier in the parts of eastern Tienshan Mountain using object image segmentation. This approach is also based on NDSI segmentation and terrain analysis in an object-based environment.…”

Section: Object-oriented Image Analysismentioning

confidence: 99%

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Development of glacier mapping in Indian Himalaya: a review of approaches

Kaushik

Joshi

Singh

2019

International Journal of Remote Sensing

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The paper reviews the status of glacier mapping with special reference to the Indian Himalaya. The review provides information on various satellite remote sensing data interpretation methods used with special emphasis laid on recent semi-automated algorithms used for glacier and debris-cover mapping, along with their limitations and challenges. Further, the pragmatic solutions on offer are discussed, and the emerging areas of glacier mapping research are highlighted. The review also touchescontribution of Survey of India (SOI) and Geological Survey of India (GSI) in the glacier mapping. Finally, it discusses the wider range of spatial and spectral domains in which remote sensing data helps to inventories glaciers. The review also identifies gaps in using the latest techniques like Unmanned Aerial Vehicles (UAVs) and machine learning algorithms to improvise on the ongoing efforts. At last, the review provides an exhaustive list of references on glacier mapping from the Indian Himalaya as benefit to readers.

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Section: Object-oriented Image Analysismentioning

confidence: 99%

Section: Object-oriented Image Analysismentioning

confidence: 99%

Development of glacier mapping in Indian Himalaya: a review of approaches

Kaushik

Joshi

Singh

2019

International Journal of Remote Sensing

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“…In the study area, virgin forest is typically found under the elevation value of 3800 m. Mountain rhododendron forest exists in the elevation value above 3800 m. Alpine meadow and brushwood are mainly distributed from 4000 to 4500 m. To determine the elevation value for the tree line or snow line accurately, we carry out two main steps. Surface radiance products of Landsat 5 TM data (Table 2) are employed to derive snow areas and no-snow areas as binary images using an object-oriented glacier mapping method [14]. Seven binary images have been derived.…”

Section: Establishment Of Local Tree Line and Snow Line As A Priori Kmentioning

confidence: 99%

Assessment of Snow Status Changes Using L-HH Temporal-Coherence Components at Mt. Dagu, China

Wang

et al. 2015

Remote Sensing

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Multitemporal Phased Array type L-band Synthetic Aperture Radar (PALSAR) horizontally transmitted and horizontally received (HH) coherence data was decomposed into temporal-coherence, spatial-coherence, and thermal noise components. The multitemporal data spanned between February and May of 2008, and consisted of two pairs of interferometric SAR (InSAR) images formed by consecutive repeat passes. With the analysis of ancillary data, a snow increase process and a snow decrease process were determined. Then, the multiple temporal-coherence components were used to study the variation of thawing and freezing statuses of snow because the components can mostly reflect the temporal change of the snow that occurred between two data acquisitions. Compared with snow mapping results derived from optical images, the outcomes from the snow increase process and the snow decrease process reached an overall accuracy of 71.3% and 79.5%, respectively. Being capable of delineating not only the areas with or without OPEN ACCESS Remote Sens. 2015, 7 11603 snow cover but also status changes among no-snow, wet snow, and dry snow, we have developed a critical means to assess the water resource in alpine areas.

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A object-oriented glacier mapping method based on multi-temporal Landsat images

Cited by 2 publications

References 0 publications

Development of glacier mapping in Indian Himalaya: a review of approaches

Development of glacier mapping in Indian Himalaya: a review of approaches

Assessment of Snow Status Changes Using L-HH Temporal-Coherence Components at Mt. Dagu, China

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