{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,21]],"date-time":"2026-01-21T08:31:13Z","timestamp":1768984273488,"version":"3.49.0"},"reference-count":51,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2020,2,3]],"date-time":"2020-02-03T00:00:00Z","timestamp":1580688000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Surface ice\/snow is a vital resource and is sensitive to climate change in many parts of the world. The accurate and timely measurement of the spatial distribution of ice\/snow is critical for managing water resources. Object-oriented and pixel-oriented methods often have some limitations due to the image segmentation scale, the determination of the optimal threshold and background heterogeneity. Therefore, this study proposes a method for automatically extracting large-scale surface ice\/snow from Landsat series images, which takes advantage of the combination of image segmentation, the watershed algorithm and a series of ice\/snow indices. We tested our novel method in three different regions in the Karakoram Mountains, and the experimental results show that the produced ice\/snow map obtained a user\u2019s accuracy greater than 90%, a producer\u2019s accuracy greater than 97%, an overall accuracy greater than 98% and a kappa coefficient greater than 0.93. Comparing the extraction results under segmentation scales of 10, 15, 20 and 25, the user\u2019s accuracy and producer\u2019s accuracy from the proposed method are very similar, which indicates that the proposed method is more reliable and stable for extracting ice\/snow objects than the object-oriented method. Due to the different reflectivity values in the near-infrared band in the snow and water categories, the normalized difference forest snow index (NDFSI) is suitable for Landsat TM and ETM+ images. This study can serve as a reliable, scientific reference for rapidly and accurately extracting ice\/snow objects.<\/jats:p>","DOI":"10.3390\/rs12030485","type":"journal-article","created":{"date-parts":[[2020,2,5]],"date-time":"2020-02-05T03:18:48Z","timestamp":1580872728000},"page":"485","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["An Automated Method for Surface Ice\/Snow Mapping Based on Objects and Pixels from Landsat Imagery in a Mountainous Region"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0384-7341","authenticated-orcid":false,"given":"Xuecheng","family":"Wang","sequence":"first","affiliation":[{"name":"State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"given":"Xing","family":"Gao","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"}]},{"given":"Xiaoyan","family":"Zhang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3526-9160","authenticated-orcid":false,"given":"Wei","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"}]},{"given":"Fei","family":"Yang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"}]}],"member":"1968","published-online":{"date-parts":[[2020,2,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1016\/j.rse.2013.08.029","article-title":"Automated Water Extraction Index: A New Technique for Surface Water Mapping Using Landsat Imagery","volume":"140","author":"Feyisa","year":"2014","journal-title":"J. Remote Sens. Environ."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"607","DOI":"10.1017\/jog.2016.45","article-title":"Numerical reconstructions of the penultimate glacial maximum Northern Hemisphere ice sheets: Sensitivity to climate forcing and model parameters","volume":"62","author":"Wekerle","year":"2016","journal-title":"J. Glaciol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"568","DOI":"10.1017\/jog.2017.10","article-title":"Dependence of slope lapse rate over the Greenland ice sheet on background climate","volume":"63","author":"Erokhina","year":"2017","journal-title":"J. Glaciol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"395","DOI":"10.1017\/jog.2019.16","article-title":"The geodetic mass balance of Eyjafjallaj\u00f6kull ice cap for 1945\u20132014: Processing guidelines and relation to climate","volume":"65","author":"Belart","year":"2019","journal-title":"J. Glaciol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1016\/j.wem.2016.10.004","article-title":"Wilderness Medical Society practice guidelines for prevention and management of avalanche and nonavalanche snow burial accidents","volume":"28","author":"Tilburg","year":"2017","journal-title":"J. Wildern. Environ. Med."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"316","DOI":"10.1016\/j.scitotenv.2017.03.010","article-title":"Winter ecology of a subalpine grassland: Effects of snow removal on soil respiration, microbial structure and function","volume":"590","author":"Gavazov","year":"2017","journal-title":"J. Sci. Total Environ."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Moreno-Gen\u00e9, J., S\u00e1nchez-Pulido, L., Cristobal-Fransi, E., and Daries, N. (2018). The economic sustainability of snow tourism: The case of ski resorts in Austria, France, and Italy. J. Sustain., 10.","DOI":"10.3390\/su10093012"},{"key":"ref_8","first-page":"1","article-title":"The changing extent of the glaciers along the western Ross Sea, Antarctica","volume":"45","author":"Fountain","year":"2017","journal-title":"J. Geol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1016\/j.rse.2015.11.023","article-title":"Rapid large-area mapping of ice flow using Landsat 8","volume":"185","author":"Fahnestock","year":"2016","journal-title":"J. Remote Sens. Environ."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1900","DOI":"10.1038\/s41467-019-09863-x","article-title":"Climate policy implications of nonlinear decline of Arctic land permafrost and other cryosphere elements","volume":"10","author":"Yumashey","year":"2019","journal-title":"J. Nat. Commun."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"S25","DOI":"10.1016\/j.rse.2007.07.029","article-title":"Interpretation of snow properties from imaging spectrometry","volume":"113","author":"Dozier","year":"2009","journal-title":"J. Remote Sens. Environ."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"351","DOI":"10.1016\/j.rse.2003.10.016","article-title":"Estimating fractional snow cover from MODIS using the normalized difference snow index","volume":"89","author":"Salomonson","year":"2004","journal-title":"J. Remote Sens. Environ."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1016\/j.atmosres.2019.05.004","article-title":"Patterns in snow depth maximum and snow cover days during 1961\u20132015 period in the Tianshan Mountains, Central Asia","volume":"228","author":"Li","year":"2019","journal-title":"J. Atmos. Res."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Selkowitz, D., and Forster, R. (2016). An automated approach for mapping persistent ice and snow cover over high latitude regions. J. Remote Sens., 8.","DOI":"10.3390\/rs8010016"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"405","DOI":"10.1007\/s11769-019-1041-3","article-title":"Evaluation of Forest Damaged Area and Severity Caused by Ice-snow Frozen Disasters over Southern China with Remote Sensing","volume":"29","author":"Wang","year":"2019","journal-title":"J. Chin. Geogr. Sci."},{"key":"ref_16","first-page":"3355","article-title":"Fractional snow cover mapping through artificial neural network analysis of MODIS surface reflectance","volume":"12","author":"Iliyana","year":"2011","journal-title":"J. Remote Sens. Environ."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1029\/RG020i001p00067","article-title":"Optical properties of snow","volume":"20","author":"Warren","year":"1982","journal-title":"J. Rev. Geophys."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1016\/S0034-4257(02)00095-0","article-title":"MODIS snow-cover products","volume":"83","author":"Hall","year":"2002","journal-title":"J. Remote Sens. Environ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"17246","DOI":"10.3390\/rs71215882","article-title":"An effective method for snow-cover mapping of dense coniferous forests in the Upper Heihe River Basin using Landsat Operational Land Imager Data","volume":"7","author":"Wang","year":"2015","journal-title":"J. Remote Sens."},{"key":"ref_20","first-page":"273","article-title":"Glacier Mapping of the Illecillewaet Icefield, British Columbia, Canada, Using Landsat TM and Digital Elevation Data","volume":"2","author":"Sidjak","year":"1996","journal-title":"Int. J. Remote Sens."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"79","DOI":"10.3189\/172756406781812393","article-title":"Monitoring the Glacier Changes in the Muztag Ata and Konggur Mountains, East Pamirs, based on Chinese Glacier Inventory and Recent Satellite Imagery","volume":"43","author":"Shangguan","year":"2006","journal-title":"J. Ann. Glaciol."},{"key":"ref_22","first-page":"1","article-title":"Extraction Snow Cover in Mountain Areas Based on SAR and Optical Data","volume":"5","author":"He","year":"2015","journal-title":"J. IEEE Geosci. Remote Sens."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"403","DOI":"10.1016\/j.rse.2014.09.026","article-title":"Fractional snow cover estimation in complex alpine-forested envrionments using an artificial neural network","volume":"156","author":"Elzbieta","year":"2015","journal-title":"J. Remote Sens. Environ."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1145","DOI":"10.1016\/j.rse.2010.12.017","article-title":"Per-pixel vs. object-based classification of urban land cover extraction using high spatial resolution imagery","volume":"115","author":"Myint","year":"2011","journal-title":"J. Remote Sens. Environ."},{"key":"ref_25","first-page":"853","article-title":"A Comparison of Pixel- and Object-Based Glacier Classification with Optical Satellite Images","volume":"3","author":"Philipp","year":"2014","journal-title":"IEEE J.-Stars."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1016\/j.isprsjprs.2019.02.009","article-title":"Segmentation for Object-Based Image Analysis (OBIA): A review of algorithms and challenges from remote sensing perspective","volume":"150","author":"Hossain","year":"2019","journal-title":"ISPRS-J. Photogramm. Remote Sens."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1433","DOI":"10.1109\/JSTARS.2018.2810094","article-title":"Snow cover mapping for complex mountainous forested environments based on a multi-index technique","volume":"11","author":"Wang","year":"2018","journal-title":"IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"98","DOI":"10.1016\/j.isprsjprs.2014.08.010","article-title":"Applying object-based segmentation in the temporal domain to characterize snow seasonality","volume":"98","author":"Thompson","year":"2014","journal-title":"ISPRS J. Photogramm."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"6529","DOI":"10.1080\/01431161.2013.803631","article-title":"Comparison of automatic thresholding methods for snow-cover mapping using Landsat TM imagery","volume":"9","author":"Yin","year":"2013","journal-title":"Int. J. Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1111\/j.1751-8369.1993.tb00421.x","article-title":"Landsat TM derived and in situ summer reflectance of glaciers in Svalbard","volume":"12","author":"WINTHER","year":"1993","journal-title":"J. Polar Res."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"357","DOI":"10.3189\/2015JoG14J209","article-title":"The second Chinese glacier inventory: Data, methods and results","volume":"61","author":"Guo","year":"2015","journal-title":"J. Glaciol."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Hui, F., Li, X., Zhao, T., Shokr, M., Heil, P., Zhao, J., Liu, Y., Liang, S., and Cheng, X. (2016). Semi-automatic mapping of tidal cracks in the fast ice region near Zhongshan station in east Antarctica using landsat-8 OLI imagery. J. Remote Sens., 8.","DOI":"10.3390\/rs8030242"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1016\/j.jhydrol.2014.11.048","article-title":"Separating snow, clean and debris covered ice in the Upper Indus Basin, Hindukush-Karakoram-Himalayas, using Landsat images between 1998 and 2002","volume":"521","author":"Khan","year":"2015","journal-title":"J. Hydrol."},{"key":"ref_34","first-page":"537","article-title":"The Randolph glacier inventory: A globally complete inventory of glaciers","volume":"221","author":"Tad","year":"2014","journal-title":"J. Glaciol."},{"key":"ref_35","first-page":"135","article-title":"A new satellite-derived glacier inventory for western Alaska","volume":"59","author":"Paul","year":"2011","journal-title":"J. Ann. Glaciol."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Hua, T., Zhao, W., Liu, Y., Wang, S., and Yang, S. (2018). Spatial Consistency Assessments for Global Land-Cover Datasets: A Comparison among GLC2000, CCILC, MCD12, GLOBCOVER and GLCNMO. J. Remote Sens., 11.","DOI":"10.3390\/rs10111846"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1016\/j.rse.2011.10.028","article-title":"Object-based cloud and cloud shadow detection in Landsat imagery","volume":"118","author":"Zhu","year":"2012","journal-title":"J. Remote Sens. Environ."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1016\/j.rse.2018.06.043","article-title":"Multi-view object-based classification of wetland land covers using unmanned aircraft system images","volume":"216","author":"Liu","year":"2018","journal-title":"J. Remote Sens. Environ."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"239","DOI":"10.1016\/j.isprsjprs.2003.10.002","article-title":"Multi-resolution, object-oriented fuzzy analysis of remote sensing data for GIS-ready information","volume":"58","author":"Ursula","year":"2004","journal-title":"ISPRS J. Photogramm."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"317","DOI":"10.1006\/cviu.1999.0822","article-title":"Watershed-based segmentation and region merging","volume":"77","author":"Bleau","year":"2000","journal-title":"J. Comput. Vis. Image Underst."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"4429","DOI":"10.1080\/01431160601034910","article-title":"Multispectral image segmentation by a multichannel watershed-based approach","volume":"28","author":"Li","year":"2007","journal-title":"Int. J. Remote Sens."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1437","DOI":"10.1109\/TIP.2007.894239","article-title":"Classification-driven watershed segmentation","volume":"16","author":"Levner","year":"2007","journal-title":"J. IEEE Trans. Image Process."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"2053","DOI":"10.1007\/s11629-017-4357-4","article-title":"Watershed classification by remote sensing indices: A fuzzy c-means clustering approach","volume":"14","author":"Choubin","year":"2017","journal-title":"J. Mt. Sci."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1016\/0034-4257(91)90048-B","article-title":"A review of assessing the accuracy of classifications of remotely sensed data","volume":"37","author":"Congalton","year":"1991","journal-title":"J. Remote Sens. Environ."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"2788","DOI":"10.1109\/JSTARS.2018.2846551","article-title":"A Systematic Extraction Approach for Mapping Glacial Lakes in High Mountain Regions of Asia","volume":"11","author":"Zhao","year":"2018","journal-title":"IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens."},{"key":"ref_46","first-page":"298","article-title":"A comparison of selected classification algorithms for mapping bamboo patches in lower Gangetic plains using very high resolution WorldView 2 imagery","volume":"26","author":"Ghosh","year":"2014","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"1628","DOI":"10.1080\/01431161.2017.1410297","article-title":"Exponentially sampling scale parameters for the efficient segmentation of remote-sensing images","volume":"39","author":"Wang","year":"2018","journal-title":"Int. J. Remote Sens."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1016\/j.isprsjprs.2013.11.018","article-title":"Automated parameterisation for multi-scale image segmentation on multiple layers","volume":"88","author":"Csillik","year":"2014","journal-title":"ISPRS-J. Photogramm. Remote Sens."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1016\/j.isprsjprs.2010.11.001","article-title":"Support vector machines in remote sensing: A review","volume":"66","author":"Mountrakis","year":"2011","journal-title":"J. ISPRS-J. Photogramm. Remote Sens."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"146","DOI":"10.1117\/1.1631315","article-title":"Survey over image thresholding techniques and quantitative performance evaluation","volume":"13","author":"Sezgin","year":"2004","journal-title":"J. Electron. Imaging"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"126","DOI":"10.1016\/j.isprsjprs.2016.04.001","article-title":"Automated mapping of persistent ice and snow cover across the western US with Landsat","volume":"117","author":"Selkowitz","year":"2016","journal-title":"ISPRS-J. Photogramm. Remote Sens."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/3\/485\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T08:54:17Z","timestamp":1760172857000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/3\/485"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,2,3]]},"references-count":51,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2020,2]]}},"alternative-id":["rs12030485"],"URL":"https:\/\/doi.org\/10.3390\/rs12030485","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,2,3]]}}}