{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T15:27:53Z","timestamp":1760369273773,"version":"build-2065373602"},"reference-count":64,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2016,3,26]],"date-time":"2016-03-26T00:00:00Z","timestamp":1458950400000},"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>Disaster change mapping, which can provide accurate and timely changed information (e.g., damaged buildings, accessibility of road and the shelter sites) for decision makers to guide and support a plan for coordinating emergency rescue, is critical for early disaster rescue. In this paper, we focus on optical remote sensing data to propose an automatic procedure to reduce the impacts of optical data limitations and provide the emergency information in the early phases of a disaster. The procedure utilizes a series of new methods, such as an Optimizable Variational Model (OptVM) for image fusion and a scale-invariant feature transform (SIFT) constraint optical flow method (SIFT-OFM) for image registration, to produce product maps including cloudless backdrop maps and change-detection maps for catastrophic event regions, helping people to be aware of the whole scope of the disaster and assess the distribution and magnitude of damage. These product maps have a rather high accuracy as they are based on high precision preprocessing results in spectral consistency and geometric, which compared with traditional fused and registration methods by visual qualitative or quantitative analysis. The procedure is fully automated without any manual intervention to save response time. It also can be applied to many situations.<\/jats:p>","DOI":"10.3390\/rs8040272","type":"journal-article","created":{"date-parts":[[2016,3,29]],"date-time":"2016-03-29T16:00:28Z","timestamp":1459267228000},"page":"272","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":31,"title":["An Automatic Procedure for Early Disaster Change Mapping Based on Optical Remote Sensing"],"prefix":"10.3390","volume":"8","author":[{"given":"Yong","family":"Ma","sequence":"first","affiliation":[{"name":"Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fu","family":"Chen","sequence":"additional","affiliation":[{"name":"Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6301-0466","authenticated-orcid":false,"given":"Jianbo","family":"Liu","sequence":"additional","affiliation":[{"name":"Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yang","family":"He","sequence":"additional","affiliation":[{"name":"Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianbo","family":"Duan","sequence":"additional","affiliation":[{"name":"Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xinpeng","family":"Li","sequence":"additional","affiliation":[{"name":"Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2016,3,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"367","DOI":"10.1016\/j.future.2013.12.018","article-title":"Modeling and simulation for natural disaster contingency planning driven by high-resolution remote sensing images","volume":"37","author":"Dou","year":"2014","journal-title":"Future Gener. Comput. Syst."},{"key":"ref_2","unstructured":"Huyck, C., Verrucci, E., and Bevington, J. (2014). Earthquake Hazard, Risk, and Disasters, Academic Press."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1177\/0309133309339563","article-title":"A review of the status of satellite remote sensing and image processing techniques for mapping natural hazards and disasters","volume":"33","author":"Joyce","year":"2009","journal-title":"Prog. Phys. Geogr."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1520","DOI":"10.1109\/TGRS.2007.895830","article-title":"Satellite image analysis for disaster and crisis-management support","volume":"45","author":"Voigt","year":"2007","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1007\/978-3-319-09048-1_3","article-title":"Remote Sensing Role in Emergency Mapping for Disaster Response","volume":"Volume 5","author":"Boccardo","year":"2015","journal-title":"Engineering Geology for Society and Territory"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1571","DOI":"10.1109\/TGRS.2006.883149","article-title":"Coherence- and amplitude-based analysis of seismogenic damage in Bam, Iran, using ENVISAT ASAR data","volume":"45","author":"Arciniegas","year":"2007","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"923","DOI":"10.14358\/PERS.77.9.923","article-title":"Rapid damage assessment and situation mapping: Learning from the 2010 Haiti earthquake","volume":"77","author":"Voigt","year":"2011","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"153","DOI":"10.5721\/ItJRS201244112","article-title":"Rapid building damage assessment using EROS B data: The case study of L\u2019Aquila earthquake","volume":"44","author":"Baiocchi","year":"2012","journal-title":"Ital. J. Remote Sens."},{"key":"ref_9","first-page":"466","article-title":"Satellite-based damage mapping following the 2006 Indonesia earthquake\u2014How accurate was it?","volume":"12","author":"Kerle","year":"2010","journal-title":"Int. J. Appl. Earth Obs."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1080\/17538940902767401","article-title":"Identifying damage caused by the 2008 Wenchuan earthquake from VHR remote sensing data","volume":"2","author":"Ehrlich","year":"2009","journal-title":"Int. J. Digit. Earth"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Chini, M. (2009). Earthquake Damage Mapping Techniques Using SAR and Optical Remote Sensing Satellite Data, INTECH Open Access Publisher.","DOI":"10.5772\/8290"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"935","DOI":"10.1109\/JSTARS.2011.2162721","article-title":"Earthquake damages rapid mapping by satellite remote sensing data: L\u2019Aquila 6 April 2009 event","volume":"4","author":"Bignami","year":"2011","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_13","first-page":"2280","article-title":"Earthquake damage detection using high-resolution satellite images","volume":"Volume 4","author":"Yamazaki","year":"2004","journal-title":"Proceedings of the IEEE International Geoscience and Remote Sensing Symposium"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1007\/s12210-015-0410-9","article-title":"Rapid Mapping: Geomatics role and research opportunities","volume":"26","author":"Ajmar","year":"2015","journal-title":"Rend. Lincei"},{"key":"ref_15","first-page":"657","article-title":"Understanding image fusion","volume":"70","author":"Zhang","year":"2004","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"629","DOI":"10.1109\/LGRS.2011.2177063","article-title":"A practical compressed sensing-based pan-sharpening method","volume":"9","author":"Jiang","year":"2012","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Shahdoosti, H.R., and Ghassemian, H. (2012, January 2\u20133). Spatial PCA as a new method for image fusion. Proceedings of the 16th CSI International Symposium on Artificial Intelligence and Signal Processing (AISP), Shiraz, Iran.","DOI":"10.1109\/AISP.2012.6313724"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1590","DOI":"10.1109\/TGRS.2010.2087029","article-title":"An IHS-based fusion for color distortion reduction and vegetation enhancement in IKONOS imagery","volume":"49","author":"Taleb","year":"2011","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_19","first-page":"587","article-title":"Problems in the Fusion of Commercial High-Resolution Satelitte as well as Landsat 7 Images and Initial Solutions","volume":"34","author":"Zhang","year":"2002","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"3674","DOI":"10.1109\/TGRS.2006.881758","article-title":"Estimation of the number of decomposition levels for a wavelet-based multiresolution multisensor image fusion","volume":"44","author":"Pradhan","year":"2006","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1693","DOI":"10.1109\/TSMCB.2012.2198810","article-title":"Adjustable model-based fusion method for multispectral and panchromatic images","volume":"42","author":"Zhang","year":"2012","journal-title":"IEEE Trans. Syst. Man Cybern. B Cybern."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"738","DOI":"10.1109\/TGRS.2010.2067219","article-title":"A new pan-sharpening method using a compressed sensing technique","volume":"49","author":"Li","year":"2011","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"502","DOI":"10.1109\/LGRS.2014.2347955","article-title":"Remote sensing image fusion using ripplet transform and compressed sensing","volume":"12","author":"Ghahremani","year":"2015","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1007\/s11263-006-6852-x","article-title":"A variational model for P+ XS image fusion","volume":"69","author":"Ballester","year":"2006","journal-title":"Int. J. Comput. Vis."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1145\/355984.355989","article-title":"LSQR: An algorithm for sparse linear equations and sparse least squares","volume":"8","author":"Paige","year":"1982","journal-title":"ACM Trans. Math. Softw. (TOMS)"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Le Moigne, J., Netanyahu, N.S., and Eastman, R.D. (2011). Image Registration for Remote Sensing, Cambridge University Press.","DOI":"10.1017\/CBO9780511777684"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1016\/j.media.2007.06.004","article-title":"Symmetric diffeomorphic image registration with cross-correlation: Evaluating automated labeling of elderly and neurodegenerative brain","volume":"12","author":"Avants","year":"2008","journal-title":"Med. Image Anal."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"4190","DOI":"10.1109\/TIP.2012.2199124","article-title":"Second-order optimization of mutual information for real-time image registration","volume":"21","author":"Dame","year":"2012","journal-title":"IEEE Trans. Image Process."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"2031","DOI":"10.1016\/j.ijleo.2011.09.040","article-title":"Motion detection in moving background using a novel algorithm based on image features guiding self-adaptive Sequential Similarity Detection Algorithm","volume":"123","author":"Yu","year":"2012","journal-title":"Optik-Int. J. Light Electron Opt."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1023\/B:VISI.0000029664.99615.94","article-title":"Distinctive image features from scale-invariant keypoints","volume":"60","author":"Lowe","year":"2004","journal-title":"Int. J. Comput. Vis."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1023\/B:VISI.0000027790.02288.f2","article-title":"Scale & affine invariant interest point detectors","volume":"60","author":"Mikolajczyk","year":"2004","journal-title":"Int. J. Comput. Vis."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"2037","DOI":"10.3390\/rs5052037","article-title":"Optimizing SIFT for matching of short wave infrared and visible wavelength images","volume":"5","author":"Sima","year":"2013","journal-title":"Remote Sens."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/S0734-189X(89)80014-3","article-title":"Multiresolution elastic matching","volume":"46","author":"Bajcsy","year":"1989","journal-title":"Comput. Vis. Graph. Image Process."},{"key":"ref_34","first-page":"307","article-title":"Research of automated image registration technique for infrared images based on optical flow field analysis","volume":"22","author":"Zhang","year":"2003","journal-title":"J. Infrared Millim. Waves"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"5943","DOI":"10.1080\/01431160802144195","article-title":"Phase correlation pixel-to-pixel image co-registration based on optical flow and median shift propagation","volume":"29","author":"Liu","year":"2008","journal-title":"Int. J. Remote Sens."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1109\/LGRS.2011.2163491","article-title":"Multilevel SIFT matching for large-size VHR image registration","volume":"9","author":"Huo","year":"2012","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_37","unstructured":"Horn, B.K., and Schunck, B.G. (1981). 1981 Technical Symposium East, International Society for Optics and Photonics."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1016\/j.amc.2003.12.085","article-title":"Successive over relaxation iterative method for fuzzy system of linear equations","volume":"162","author":"Allahviranloo","year":"2005","journal-title":"Appl. Math. Comput."},{"key":"ref_39","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. Remote Sens."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"232","DOI":"10.1109\/TGRS.2012.2197682","article-title":"Cloud removal from multitemporal satellite images using information cloning","volume":"51","author":"Lin","year":"2013","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1053","DOI":"10.1016\/j.rse.2010.12.010","article-title":"A simple and effective method for filling gaps in Landsat ETM+ SLC-off images","volume":"115","author":"Chen","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_42","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_43","doi-asserted-by":"crossref","first-page":"2207","DOI":"10.1109\/TGRS.2006.872081","article-title":"On the blending of the Landsat and MODIS surface reflectance: Predicting daily Landsat surface reflectance","volume":"44","author":"Gao","year":"2006","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"1079","DOI":"10.14358\/PERS.71.9.1079","article-title":"Cloud-free satellite image mosaics with regression trees and histogram matching","volume":"71","author":"Helmer","year":"2005","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1016\/j.isprsjprs.2014.02.015","article-title":"Cloud removal for remotely sensed images by similar pixel replacement guided with a spatio-temporal MRF model","volume":"92","author":"Cheng","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1109\/ICEMI.2011.6037860","article-title":"Automatic cloud and cloud shadow removal method for landsat TM images","volume":"Volume 3","author":"Zhengke","year":"2011","journal-title":"Proceedings of the 10th International Conference on Electronic Measurement & Instruments (ICEMI)"},{"key":"ref_47","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_48","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1109\/TGRS.2008.2002695","article-title":"Exploiting SAR and VHR optical images to quantify damage caused by the 2003 Bam earthquake","volume":"47","author":"Chini","year":"2009","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"3073","DOI":"10.1080\/01431160701442096","article-title":"Building-based damage detection due to earthquake using the watershed segmentation of the post-event aerial images","volume":"29","author":"Turker","year":"2008","journal-title":"Int. J. Remote Sens."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"453","DOI":"10.1193\/1.4000139","article-title":"Detection of building damage areas of the 2006 central Java, Indonesia, earthquake through digital analysis of optical satellite images","volume":"29","author":"Miura","year":"2013","journal-title":"Earthq. Spectra"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"1025","DOI":"10.1016\/j.rse.2007.07.013","article-title":"Automatic radiometric normalization of multitemporal satellite imagery with the iteratively re-weighted MAD transformation","volume":"112","author":"Canty","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"463","DOI":"10.1109\/TIP.2006.888195","article-title":"The regularized iteratively reweighted MAD method for change detection in multi-and hyperspectral data","volume":"16","author":"Nielsen","year":"2007","journal-title":"IEEE Trans. Image Process."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"799","DOI":"10.1109\/LGRS.2011.2109697","article-title":"Improving change detection results of IR-MAD by eliminating strong changes","volume":"8","author":"Marpu","year":"2011","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_54","unstructured":"Qiang, L., Yuan, G., and Ying, C. (2014, January 29\u201330). Study on disaster information management system compatible with VGI and crowdsourcing. Proceedings of the 2014 IEEE Workshop on Advanced Research and Technology in Industry Applications (WARTIA), Ottawa, ON, Canada."},{"key":"ref_55","unstructured":"Resor, E.E.L. (2013). The Neo-Humanitarians: Assessing the Credibility of Organized Volunteer Crisis Mappers. [Ph.D. Thesis, Massachusetts Institute of Technology]."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"571","DOI":"10.5721\/EuJRS20134633","article-title":"New perspectives in emergency mapping","volume":"46","author":"Boccardo","year":"2013","journal-title":"Eur. J. Remote Sens."},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Barrington, L., Ghosh, S., Greene, M., Har-Noy, S., Berger, J., Gill, S., Lin, A.Y.-M., and Huyck, C. (2012). Crowdsourcing earthquake damage assessment using remote sensing imagery. Ann. Geophys., 54.","DOI":"10.4401\/ag-5324"},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"313","DOI":"10.1109\/LGRS.2004.836784","article-title":"A global quality measurement of pan-sharpened multispectral imagery","volume":"1","author":"Alparone","year":"2004","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"3880","DOI":"10.1109\/TGRS.2009.2029094","article-title":"Pansharpening quality assessment using the modulation transfer functions of instruments","volume":"47","author":"Khan","year":"2009","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1155\/2009\/305479","article-title":"Precise image registration with structural similarity error measurement applied to superresolution","volume":"2009","author":"Amintoosi","year":"2009","journal-title":"EURASIP J. Adv. Signal Process."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"1087","DOI":"10.5194\/nhess-15-1087-2015","article-title":"UAV-based urban structural damage assessment using object-based image analysis and semantic reasoning","volume":"15","author":"Kerle","year":"2015","journal-title":"Nat. Hazards Earth Sys. Sci."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1016\/j.isprsjprs.2015.03.016","article-title":"Identification of damage in buildings based on gaps in 3D point clouds from very high resolution oblique airborne images","volume":"105","author":"Vetrivel","year":"2015","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"97","DOI":"10.5194\/nhess-13-97-2013","article-title":"Collaborative damage mapping for emergency response: The role of cognitive systems engineering","volume":"13","author":"Kerle","year":"2013","journal-title":"Nat. Hazards Earth Syst. Sci."},{"key":"ref_64","doi-asserted-by":"crossref","unstructured":"Eguchi, R.T., Huyck, C.K., Ghosh, S., Adams, B.J., and McMillan, A. (2010). Utilizing New Technologies in Managing Hazards and Disasters Geospatial Techniques in Urban Hazard and Disaster Analysis, Springer.","DOI":"10.1007\/978-90-481-2238-7_15"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/8\/4\/272\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T19:21:22Z","timestamp":1760210482000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/8\/4\/272"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,3,26]]},"references-count":64,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2016,4]]}},"alternative-id":["rs8040272"],"URL":"https:\/\/doi.org\/10.3390\/rs8040272","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2016,3,26]]}}}