{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,8]],"date-time":"2026-07-08T22:26:25Z","timestamp":1783549585216,"version":"3.55.0"},"reference-count":70,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2016,1,5]],"date-time":"2016-01-05T00:00:00Z","timestamp":1451952000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation project of China","award":["41271433"],"award-info":[{"award-number":["41271433"]}]},{"name":"National Natural Science Foundation project of China","award":["41571373"],"award-info":[{"award-number":["41571373"]}]},{"name":"International Cooperation Key Project of CAS","award":["GJHZ201320"],"award-info":[{"award-number":["GJHZ201320"]}]},{"name":"International Cooperation Partner Program of Innovative Team, CAS","award":["KZZD-EW-TZ-06"],"award-info":[{"award-number":["KZZD-EW-TZ-06"]}]},{"name":"\u201cHundred Talents\u201d Project of Chinese Academy of Sciences"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>It is highly desirable to accurately detect the clouds in satellite images before any kind of applications. However, clouds and snow discrimination in remote sensing images is a challenging task because of their similar spectral signature. The shortwave infrared (SWIR, e.g., Landsat TM 1.55\u20131.75 \u00b5m band) band is widely used for the separation of cloud and snow. However, for some sensors such as the CBERS-2 (China-Brazil Earth Resources Satellite), CBERS-4 and HJ-1A\/B (HuanJing (HJ), which means environment in Chinese) that are designed without SWIR band, such methods are no longer practical. In this paper, a new practical method was proposed to discriminate clouds from snow through combining the spectral reflectance with the spatio-temporal contextual information. Taking the Mt. Gongga region, where there is frequent clouds and snow cover, in China as a case area, the detailed methodology was introduced on how to use the 181 scenes of HJ-1A\/B CCD images in the year 2011 to discriminate clouds and snow in these images. Visual inspection revealed that clouds and snow pixels can be accurately separated by the proposed method. The pixel-level quantitative accuracy validation was conducted by comparing the detection results with the reference cloud masks generated by a random-tile validation scheme. The pixel-level validation results showed that the coefficient of determination (R2) between the reference cloud masks and the detection results was 0.95, and the average overall accuracy, precision and recall for clouds were 91.32%, 85.33% and 81.82%, respectively. The experimental results confirmed that the proposed method was effective at providing reasonable cloud mask for the SWIR-lacking HJ-1A\/B CCD images. Since HJ-1A\/B have been in orbit for over seven years and these satellites still run well, the proposed method is helpful for the cloud mask generation of the historical archive HJ-1A\/B images and even similar sensors.<\/jats:p>","DOI":"10.3390\/rs8010031","type":"journal-article","created":{"date-parts":[[2016,1,6]],"date-time":"2016-01-06T02:18:12Z","timestamp":1452046692000},"page":"31","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":31,"title":["Cloud and Snow Discrimination for CCD Images of HJ-1A\/B Constellation Based on Spectral Signature and Spatio-Temporal Context"],"prefix":"10.3390","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1472-5259","authenticated-orcid":false,"given":"Jinhu","family":"Bian","sequence":"first","affiliation":[{"name":"Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ainong","family":"Li","sequence":"additional","affiliation":[{"name":"Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiannan","family":"Liu","sequence":"additional","affiliation":[{"name":"Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chengquan","family":"Huang","sequence":"additional","affiliation":[{"name":"Department of Geography, University of Maryland, College Park, MD 20742, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2016,1,5]]},"reference":[{"key":"ref_1","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":"Remote Sens. Environ."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1016\/j.isprsjprs.2011.10.008","article-title":"Combining the matter element model with the associated function of probability transformation for multi-source remote sensing data classification in mountainous regions","volume":"67","author":"Li","year":"2012","journal-title":"ISPRS J. Photogramm."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1016\/j.rse.2009.08.017","article-title":"An automated approach for reconstructing recent forest disturbance history using dense Landsat time series stacks","volume":"114","author":"Huang","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"192","DOI":"10.1080\/07038992.2014.945827","article-title":"Pixel-based image compositing for large-area dense time series applications and science","volume":"40","author":"White","year":"2014","journal-title":"Can. J. Remote Sens."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1016\/j.rse.2009.08.011","article-title":"Web-Enabled Landsat Data (WELD): Landsat ETM plus composited mosaics of the conterminous United States","volume":"114","author":"Roy","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1016\/j.rse.2007.02.018","article-title":"Lai, fapar and fcover cyclopes global products derived from vegetation: Part 1: Principles of the algorithm","volume":"110","author":"Baret","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1837","DOI":"10.1016\/j.rse.2011.03.001","article-title":"Modeling the height of young forests regenerating from recent disturbances in Mississippi using Landsat and ICEsat data","volume":"115","author":"Li","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Lyapustin, A., Wang, Y., and Frey, R. (2008). An automatic cloud mask algorithm based on time series of MODIS measurements. J. Geophys. Res.-Atmos.","DOI":"10.1029\/2007JD009641"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1016\/j.rse.2014.06.012","article-title":"Automated cloud, cloud shadow, and snow detection in multitemporal Landsat data: An algorithm designed specifically for monitoring land cover change","volume":"152","author":"Zhu","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"269","DOI":"10.1016\/j.rse.2014.12.014","article-title":"Improvement and expansion of the fmask algorithm: Cloud, cloud shadow, and snow detection for Landsats 4\u20137, 8, and Sentinel 2 images","volume":"159","author":"Zhu","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"459","DOI":"10.1109\/TGRS.2002.808301","article-title":"The MODIS cloud products: Algorithms and examples from terra","volume":"41","author":"Platnick","year":"2003","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"564","DOI":"10.3390\/rs70100564","article-title":"A one year Landsat 8 conterminous United States study of cirrus and non-cirrus clouds","volume":"7","author":"Kovalskyy","year":"2015","journal-title":"Remote Sens."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"224","DOI":"10.1016\/j.isprsjprs.2014.06.011","article-title":"An effective thin cloud removal procedure for visible remote sensing images","volume":"96","author":"Shen","year":"2014","journal-title":"ISPRS J. Photogramm."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"750","DOI":"10.1016\/j.rse.2007.06.004","article-title":"Statistical cloud detection from SEVIRI multispectral images","volume":"112","author":"Amato","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"2495","DOI":"10.1016\/j.rse.2007.11.012","article-title":"A method for integrating MODIS and Landsat data for systematic monitoring of forest cover and change in the Congo basin","volume":"112","author":"Hansen","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"5449","DOI":"10.1080\/01431160903369642","article-title":"Automated masking of cloud and cloud shadow for forest change analysis using Landsat images","volume":"31","author":"Huang","year":"2010","journal-title":"Int. J. Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1016\/j.rse.2011.10.030","article-title":"Continuous monitoring of forest disturbance using all available Landsat imagery","volume":"122","author":"Zhu","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1016\/0034-4257(89)90101-6","article-title":"Spectral signature of alpine snow cover from the Landsat Thematic Mapper","volume":"28","author":"Dozier","year":"1989","journal-title":"Remote Sens. Environ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1016\/0034-4257(95)00137-P","article-title":"Development of methods for mapping global snow cover using moderate resolution imaging spectroradiometer data","volume":"54","author":"Hall","year":"1995","journal-title":"Remote Sens. Environ."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1016\/j.rse.2004.03.007","article-title":"Cloud detection in Landsat imagery of ice sheets using shadow matching technique and automatic normalized difference snow index threshold value decision","volume":"91","author":"Choi","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_21","unstructured":"Vermote, E., and Saleous, N. (2007). Ledaps Surface Reflectance Product Description, Avaiable online: https:\/\/dwrgis.water.ca.gov\/documents\/269784\/4654504\/LEDAPS+Surface+Reflectance+Product+Description.pdf."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1109\/LGRS.2005.857030","article-title":"A land surface reflectance dataset for north America, 1990\u20132000","volume":"3","author":"Masek","year":"2006","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1747","DOI":"10.1016\/j.rse.2010.03.002","article-title":"A multi-temporal method for cloud detection, applied to Formosat-2, Venmus, Landsat and Sentinel-2 images","volume":"114","author":"Hagolle","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1016\/j.rse.2013.02.019","article-title":"Cloud and cloud shadow screening across queensland, australia: An automated method for Landsat TM\/ETM Plus time series","volume":"134","author":"Goodwin","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"584","DOI":"10.1016\/j.amc.2008.05.050","article-title":"Automatic cloud removal from multitemporal SPOT images","volume":"205","author":"Tseng","year":"2008","journal-title":"Appl. Math. Comput."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1016\/j.rse.2005.04.021","article-title":"A contextual classification scheme based on MRF model with improved parameter estimation and multiscale fuzzy line process","volume":"97","author":"Tso","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1016\/j.rse.2005.12.012","article-title":"A spatial-temporal approach to monitoring forest disease spread using multi-temporal high spatial resolution imagery","volume":"101","author":"Liu","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"784","DOI":"10.1109\/TGRS.2011.2162246","article-title":"A spatial\u2013contextual support vector machine for remotely sensed image classification","volume":"50","author":"Li","year":"2012","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1109\/TIT.1968.1054102","article-title":"On the mean accuracy of statistical pattern recognizers","volume":"14","author":"Hughes","year":"1968","journal-title":"IEEE Trans. Inform. Theory"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1016\/j.neucom.2014.09.102","article-title":"A cloud image detection method based on SVM vector machine","volume":"169","author":"Li","year":"2015","journal-title":"Neurocomputing"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Vasquez, R.E., and Manian, V.B. (2003). Texture-based cloud detection in MODIS images. Proc. SPIE.","DOI":"10.1117\/12.463042"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Zhu, L., Xiao, P., Feng, X., Zhang, X., Wang, Z., and Jiang, L. (2014). Support vector machine-based decision tree for snow cover extraction in mountain areas using high spatial resolution remote sensing image. J. Appl. Remote Sens., 8.","DOI":"10.1117\/1.JRS.8.084698"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"3078","DOI":"10.3390\/rs4103078","article-title":"Decision tree and texture analysis for mapping debris-covered glaciers in the Kangchenjunga area, eastern Himalaya","volume":"4","author":"Racoviteanu","year":"2012","journal-title":"Remote Sens."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1080\/01431168808954847","article-title":"Selecting the spatial-resolution of satellite sensors required for global monitoring of land transformations","volume":"9","author":"Townshend","year":"1988","journal-title":"Int. J. Remote Sens."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Luo, J., Chen, Y., Wu, Y., Shi, P., She, J., and Zhou, P. (2012). Temporal-spatial variation and controls of soil respiration in different primary succession stages on glacier forehead in Gongga Mountain, China. PLoS ONE, 7.","DOI":"10.1371\/journal.pone.0042354"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1007\/s11442-008-0115-4","article-title":"Source of major anions and cations of snowpacks in Hailuogou No. 1 glacier, Mt. Gongga and Baishui No. 1 glacier, Mt. Yulong","volume":"18","author":"Li","year":"2008","journal-title":"J. Geogr. Sci."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1007\/s11430-010-4139-0","article-title":"Chinese HJ-1A\/B satellites and data characteristics","volume":"53","author":"Wang","year":"2010","journal-title":"Sci. China Earth Sci."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.isprsjprs.2014.02.011","article-title":"A three-band semi-analytical model for deriving total suspended sediment concentration from HJ-1A\/CCD data in turbid coastal waters","volume":"93","author":"Chen","year":"2014","journal-title":"ISPRS J. Photogramm."},{"key":"ref_39","first-page":"428","article-title":"Water body mapping method with HJ-1A\/B satellite imagery","volume":"13","author":"Lu","year":"2011","journal-title":"Int. J. Appl. Earth Obs."},{"key":"ref_40","unstructured":"China Centre for Resources Satellite Data and Application. Avialable online: Http:\/\/www.Cresda.Com\/site2\/satellite\/7117.Shtml."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"754","DOI":"10.1007\/s11629-013-2545-4","article-title":"Auto-registration and orthorecification algorithm for the time series HJ-1A\/B CCD images","volume":"10","author":"Bian","year":"2013","journal-title":"J. Mt. Sci.-Engl."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1016\/j.rse.2013.02.026","article-title":"Assessment of the NASA-USGS Global Land Survey (GLS) datasets","volume":"134","author":"Gutman","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1016\/S0034-4257(02)00085-8","article-title":"Achieving sub-pixel geolocation accuracy in support of MODIS land science","volume":"83","author":"Wolfe","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"1829","DOI":"10.1364\/OE.23.001829","article-title":"Tracking radiometric responsivity of optical sensors without on-board calibration systems-case of the Chinese HJ-1A\/B CCD sensors","volume":"23","author":"Li","year":"2015","journal-title":"Opt. Express"},{"key":"ref_45","first-page":"1479","article-title":"An improved DDV method to retrieve AOT for HJ CCD image in typical mountainous areas","volume":"35","author":"Zhao","year":"2015","journal-title":"Spectrosc. Spect. Anal."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"16647","DOI":"10.3390\/rs71215846","article-title":"Development of dense time series 30-m image products from the Chinese HJ-1A\/B constellation: A case study in zoige plateau, china","volume":"7","author":"Bian","year":"2015","journal-title":"Remote Sens."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"4105","DOI":"10.1109\/TGRS.2007.905312","article-title":"Cloud-screening algorithm for ENVISAT\/MERIS multispectral images","volume":"45","author":"Guanter","year":"2007","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1016\/S0034-4257(02)00034-2","article-title":"An image transform to characterize and compensate for spatial variations in thin cloud contamination of Landsat images","volume":"82","author":"Zhang","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"3365","DOI":"10.1080\/01431169408954336","article-title":"The University-of-Maryland improved global vegetation index product","volume":"15","author":"Goward","year":"1994","journal-title":"Int. J. Remote Sens."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"1417","DOI":"10.1080\/01431168608948945","article-title":"Characteristics of maximum-value composite images from temporal AVHRR data","volume":"7","author":"Holben","year":"1986","journal-title":"Int. J. Remote Sens."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"2017","DOI":"10.1109\/36.851783","article-title":"The impact of misregistration upon composited wide field of view satellite data and implications for change detection","volume":"38","author":"Roy","year":"2000","journal-title":"IEEE Trans. Geosci. Remote"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"416","DOI":"10.1016\/j.rse.2006.05.016","article-title":"Improved estimation of aerosol optical depth from MODIS imagery over land surfaces","volume":"104","author":"Liang","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"4167","DOI":"10.1016\/j.rse.2008.06.010","article-title":"Developing clear-sky, cloud and cloud shadow mask for producing clear-sky composites at 250-meter spatial resolution for the seven MODIS land bands over canada and north America","volume":"112","author":"Luo","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"6481","DOI":"10.3390\/rs5126481","article-title":"Seasonal composite Landsat TM\/ETM+ images using the Medoid (a multi-dimensional median)","volume":"5","author":"Flood","year":"2013","journal-title":"Remote Sens."},{"key":"ref_55","first-page":"725","article-title":"Reconstructing ndvi time-series data set of modis based on the Savitzky-Golay filter","volume":"14","author":"Bian","year":"2010","journal-title":"J. Remote Sens."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"332","DOI":"10.1016\/j.rse.2004.03.014","article-title":"A simple method for reconstructing a high-quality NDVI time-series data set based on the Savitzky-Golay filter","volume":"91","author":"Chen","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"1627","DOI":"10.1021\/ac60214a047","article-title":"Smoothing and differentiation of data by simplified least squares procedure","volume":"36","author":"Savitzky","year":"1964","journal-title":"Anal. Chem."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"98","DOI":"10.1016\/j.patrec.2008.02.027","article-title":"Non-rigid object tracking in complex scenes","volume":"30","author":"Zhou","year":"2009","journal-title":"Pattern Recogn. Lett."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"1197","DOI":"10.1016\/j.robot.2010.08.002","article-title":"Target tracking for mobile robot platforms via object matching and background anti-matching","volume":"58","author":"Zhang","year":"2010","journal-title":"Robot. Auton. Syst."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"589","DOI":"10.1007\/11744047_45","article-title":"Region covariance: A fast descriptor for detection and classification","volume":"3952","author":"Tuzel","year":"2006","journal-title":"Lect. Notes Comput. Sci."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"4173","DOI":"10.1109\/TGRS.2012.2189011","article-title":"A hierarchical ship detection scheme for high-resolution SAR images","volume":"50","author":"Wang","year":"2012","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_62","doi-asserted-by":"crossref","unstructured":"Grafarend, W.E., Krumm, F.W., and Schwarze, V.S. (2003). Geodesy\u2014The Challenge of the 3rd Millennium, Springer-Verlag.","DOI":"10.1007\/978-3-662-05296-9"},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"610","DOI":"10.1109\/TSMC.1973.4309314","article-title":"Textural features for image classification","volume":"SMC-3","author":"Haralick","year":"1973","journal-title":"IEEE Trans. Syst. Man Cybern."},{"key":"ref_64","first-page":"37","article-title":"Evaluation: From precision, recall and f-measure to ROC, informedness, markedness and correlation","volume":"2","author":"Powers","year":"2011","journal-title":"J. Mach. Learn. Technol."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"1765","DOI":"10.1080\/01431160902926632","article-title":"Improvement of cloud detection near sunrise and sunset by temporal-differencing and region-growing techniques with real-time SEVIRI","volume":"31","author":"Derrien","year":"2010","journal-title":"Int. J. Remote Sens."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"2950","DOI":"10.1109\/TGRS.2006.876704","article-title":"A pixel shape index coupled with spectral information for classification of high spatial resolution remotely sensed imagery","volume":"44","author":"Zhang","year":"2006","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"3804","DOI":"10.1109\/TGRS.2008.922034","article-title":"Spectral and spatial classification of hyperspectral data using SVMS and morphological profiles","volume":"46","author":"Fauvel","year":"2008","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"5923","DOI":"10.1080\/01431160802139922","article-title":"A multiscale feature fusion approach for classification of very high resolution satellite imagery based on wavelet transform","volume":"29","author":"Huang","year":"2008","journal-title":"Int. J. Remote Sens."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"947","DOI":"10.14358\/PERS.78.9.947","article-title":"A variational gradient-based fusion method for visible and SWIR imagery","volume":"78","author":"Li","year":"2012","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1016\/j.rse.2011.11.026","article-title":"Sentinel-2: ESA\u2019s optical high-resolution mission for GMES operational services","volume":"120","author":"Drusch","year":"2012","journal-title":"Remote Sens. Environ."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/8\/1\/31\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T19:17:17Z","timestamp":1760210237000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/8\/1\/31"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,1,5]]},"references-count":70,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2016,1]]}},"alternative-id":["rs8010031"],"URL":"https:\/\/doi.org\/10.3390\/rs8010031","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,1,5]]}}}