{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:13:23Z","timestamp":1760242403181,"version":"build-2065373602"},"reference-count":27,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2017,8,5]],"date-time":"2017-08-05T00:00:00Z","timestamp":1501891200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>We present in this paper a polynomial fitting method applicable to segments of footprints measured by the Geoscience Laser Altimeter System (GLAS) to estimate glacier thickness change. Our modification makes the method applicable to complex topography, such as a large mountain glacier. After a full analysis of the planar fitting method to characterize errors of estimates due to complex topography, we developed an improved fitting method by adjusting a binary polynomial surface to local topography. The improved method and the planar fitting method were tested on the accumulation areas of the Naimona\u2019nyi glacier and Yanong glacier on along-track facets with lengths of 1000 m, 1500 m, 2000 m, and 2500 m, respectively. The results show that the improved method gives more reliable estimates of changes in elevation than planar fitting. The improved method was also tested on Guliya glacier with a large and relatively flat area and the Chasku Muba glacier with very complex topography. The results in these test sites demonstrate that the improved method can give estimates of glacier thickness change on glaciers with a large area and a complex topography. Additionally, the improved method based on GLAS Data and Shuttle Radar Topography Mission-Digital Elevation Model (SRTM-DEM) can give estimates of glacier thickness change from 2000 to 2008\/2009, since it takes the 2000 SRTM-DEM as a reference, which is a longer period than 2004 to 2008\/2009, when using the GLAS data only and the planar fitting method.<\/jats:p>","DOI":"10.3390\/s17081803","type":"journal-article","created":{"date-parts":[[2017,8,9]],"date-time":"2017-08-09T06:32:14Z","timestamp":1502260334000},"page":"1803","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["A New Method to Estimate Changes in Glacier Surface Elevation Based on Polynomial Fitting of Sparse ICESat\u2014GLAS Footprints"],"prefix":"10.3390","volume":"17","author":[{"given":"Tianjin","family":"Huang","sequence":"first","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"Joint Center for Global Change Studies, Beijing 100875, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"given":"Li","family":"Jia","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"Joint Center for Global Change Studies, Beijing 100875, China"}]},{"given":"Massimo","family":"Menenti","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"Department of Geoscience and Remote Sensing, Delft University of Technology, Delft 2600, The Netherlands"}]},{"given":"Jing","family":"Lu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"Joint Center for Global Change Studies, Beijing 100875, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1199-4261","authenticated-orcid":false,"given":"Jie","family":"Zhou","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"Joint Center for Global Change Studies, Beijing 100875, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2940-8336","authenticated-orcid":false,"given":"Guangcheng","family":"Hu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"Joint Center for Global Change Studies, Beijing 100875, China"}]}],"member":"1968","published-online":{"date-parts":[[2017,8,5]]},"reference":[{"key":"ref_1","unstructured":"IPCC (2013, January 20\u201321). 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