{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,16]],"date-time":"2026-03-16T21:04:23Z","timestamp":1773695063717,"version":"3.50.1"},"reference-count":44,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2019,3,22]],"date-time":"2019-03-22T00:00:00Z","timestamp":1553212800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001775","name":"University of Technology Sydney","doi-asserted-by":"publisher","award":["321740.2232335 and 321740.2232357"],"award-info":[{"award-number":["321740.2232335 and 321740.2232357"]}],"id":[{"id":"10.13039\/501100001775","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Orthorectification is an important step in generating accurate land use\/land cover (LULC) from satellite imagery, particularly in urban areas with high-rise buildings. Such buildings generally appear as oblique shapes on very-high-resolution (VHR) satellite images, which reflect a bigger area of coverage than the real built-up area on LULC mapping. This drawback can cause not only uncertainties in urban mapping and LULC classification, but can also result in inaccurate urban change detection. Overestimating volume or area of high-rise buildings has a negative impact on computing the exact amount of environmental heat and emission. Hence, in this study, we propose a method of orthorectfiying VHR WorldView-3 images by integrating light detection and ranging (LiDAR) data to overcome the aforementioned problems. A 3D rational polynomial coefficient (RPC) model was proposed with respect to high-accuracy ground control points collected from the LiDAR data derived from the digital surface model. Multiple probabilities for generating an orthrorectified image from WV-3 were assessed using 3D RCP model to achieve the optimal combination technique, with low vertical and horizontal errors. Ground control point (GCPs) collection is sensitive to variation in number and data collection pattern. These steps are important in orthorectification because they can cause the morbidity of a standard equation, thereby interrupting the stability of 3D RCP model by reducing the accuracy of the orthorectified image. Hence, we assessed the maximum possible scenarios of resampling and ground control point collection techniques to bridge the gap. Results show that the 3D RCP model accurately orthorectifies the VHR satellite image if 20 to 100 GCPs were collected by convenience pattern. In addition, cubic conventional resampling algorithm improved the precision and smoothness of the orthorectified image. According to the root mean square error, the proposed combination technique enhanced the vertical and horizontal accuracies of the geo-positioning process to up to 0.8 and 1.8 m, respectively. Such accuracy is considered very high in orthorectification. The proposed technique is easy to use and can be replicated for other VHR satellite and aerial photos.<\/jats:p>","DOI":"10.3390\/rs11060692","type":"journal-article","created":{"date-parts":[[2019,3,25]],"date-time":"2019-03-25T06:56:52Z","timestamp":1553497012000},"page":"692","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Urban Mapping Accuracy Enhancement in High-Rise Built-Up Areas Deployed by 3D-Orthorectification Correction from WorldView-3 and LiDAR Imageries"],"prefix":"10.3390","volume":"11","author":[{"given":"Hossein Mojaddadi","family":"Rizeei","sequence":"first","affiliation":[{"name":"Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS), Faculty of Engineering and IT, University of Technology Sydney, Sydney, NSW 2007, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9863-2054","authenticated-orcid":false,"given":"Biswajeet","family":"Pradhan","sequence":"additional","affiliation":[{"name":"Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS), Faculty of Engineering and IT, University of Technology Sydney, Sydney, NSW 2007, Australia"},{"name":"Department of Energy and Mineral Resources Engineering, Choongmu-gwan, Sejong University, 209 Neungdong-ro, Gwangjin-gu, Seoul 05006, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,3,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Zhang, H., Pu, R., and Liu, X. (2016). A new image processing procedure integrating PCI-RPC and ArcGIS-Spline tools to improve the orthorectification accuracy of high-resolution satellite imagery. Remote Sens., 8.","DOI":"10.3390\/rs8100827"},{"key":"ref_2","first-page":"30","article-title":"Orthorectification of high resolution satellite images","volume":"35","author":"Piero","year":"2004","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1092","DOI":"10.1080\/01431161.2018.1524173","article-title":"Urban object extraction using Dempster Shafer feature-based image analysis from worldview-3 satellite imagery","volume":"40","author":"Pradhan","year":"2019","journal-title":"Int. J. Remote Sens."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Rizeei, H.M., Shafri, H.Z., Mohamoud, M.A., Pradhan, B., and Kalantar, B. (2018). Oil palm counting and age estimation from WorldView-3 imagery and LiDAR data using an integrated OBIA height model and regression analysis. J. Sens., 2018.","DOI":"10.1155\/2018\/2536327"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Aal-shamkhi, A.D.S., Mojaddadi, H., Pradhan, B., and Abdullahi, S. (2017). Extraction and modeling of urban sprawl development in Karbala City using VHR satellite imagery. Spatial Modeling and Assessment of Urban Form, Springer.","DOI":"10.1007\/978-3-319-54217-1_12"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1080\/10630732.2017.1390299","article-title":"City compactness: Assessing the influence of the growth of residential land use","volume":"25","author":"Abdullahi","year":"2018","journal-title":"J. Urban Technol."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1080","DOI":"10.1080\/19475705.2017.1294113","article-title":"Ensemble machine-learning-based geospatial approach for flood risk assessment using multi-sensor remote-sensing data and GIS","volume":"8","author":"Mojaddadi","year":"2017","journal-title":"Geomat. Nat. Hazards Risk"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"3440","DOI":"10.1002\/ldr.3112","article-title":"Assessment of land cover and land use change impact on soil loss in a tropical catchment by using multitemporal SPOT-5 satellite images and R evised U niversal Soil L oss E quation model","volume":"29","author":"Nampak","year":"2018","journal-title":"Land Degrad. Dev."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1007\/s12517-018-3397-6","article-title":"Surface runoff prediction regarding LULC and climate dynamics using coupled LTM, optimized ARIMA, and GIS-based SCS-CN models in tropical region","volume":"11","author":"Rizeei","year":"2018","journal-title":"Arab. J. Geosci."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1158","DOI":"10.1080\/10106049.2015.1120354","article-title":"Soil erosion prediction based on land cover dynamics at the Semenyih watershed in Malaysia using LTM and USLE models","volume":"31","author":"Rizeei","year":"2016","journal-title":"Geocarto Int."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1529","DOI":"10.1109\/TGRS.2006.888937","article-title":"Automatic and precise orthorectification, coregistration, and subpixel correlation of satellite images, application to ground deformation measurements","volume":"45","author":"Leprince","year":"2007","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_12","unstructured":"Chmiel, J., Kay, S., and Spruyt, P. (2004, January 12\u201323). Orthorectification and geometric quality assessment of very high spatial resolution satellite imagery for Common Agricultural Policy purposes. Proceedings of the XXth ISPRS Congress, Istanbul, Turkey."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Mezaal, M., Pradhan, B., and Rizeei, H. (2018). Improving Landslide Detection from Airborne Laser Scanning Data Using Optimized Dempster\u2013Shafer. Remote Sens., 10.","DOI":"10.3390\/rs10071029"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"633","DOI":"10.1007\/s10661-018-7013-8","article-title":"Assessment of groundwater nitrate contamination hazard in a semi-arid region by using integrated parametric IPNOA and data-driven logistic regression models","volume":"190","author":"Rizeei","year":"2018","journal-title":"Environ. Monit. Assess."},{"key":"ref_15","unstructured":"Dowman, I., and Dare, P. (1999, January 3\u20134). Automated procedures for multisensor registration and orthorectification of satellite images. Proceedings of the International Archives of Photogrammetry and Remote Sensing, Valladolid, Spain."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"6035","DOI":"10.1109\/TGRS.2015.2431434","article-title":"Automatic orthorectification of high-resolution optical satellite images using vector roads","volume":"53","author":"Fras","year":"2015","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_17","first-page":"586","article-title":"Optimized patch backprojection in orthorectification for high resolution satellite images","volume":"35","author":"Chen","year":"2004","journal-title":"Int. Arch. Photogramm. Remote Sens"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"182","DOI":"10.1016\/j.isprsjprs.2005.11.001","article-title":"Sensor orientation via RPCs","volume":"60","author":"Fraser","year":"2006","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_19","first-page":"427","article-title":"Assessing geometric accuracy of the orthorectification process from GeoEye-1 and WorldView-2 panchromatic images","volume":"21","author":"Aguilar","year":"2013","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1893","DOI":"10.1080\/0143116031000101611","article-title":"Geometric processing of remote sensing images: Models, algorithms and methods","volume":"25","author":"Toutin","year":"2004","journal-title":"Int. J. Remote Sens."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"909","DOI":"10.14358\/PERS.71.8.909","article-title":"Bias-compensated RPCs for sensor orientation of high-resolution satellite imagery","volume":"71","author":"Fraser","year":"2005","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Crespi, M., Fratarcangeli, F., Giannone, F., and Pieralice, F. (2010). High resolution satellite image orientation models. Geospatial Technology for Earth Observation, Springer.","DOI":"10.1007\/978-1-4419-0050-0_4"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"647","DOI":"10.1080\/10106049.2015.1073367","article-title":"The georeferencing of RASAT satellite imagery and some practical approaches to increase the georeferencing accuracy","volume":"31","author":"Erdogan","year":"2016","journal-title":"Geocarto Int."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"59","DOI":"10.14358\/PERS.69.1.59","article-title":"Block adjustment of high-resolution satellite images described by rational polynomials","volume":"69","author":"Grodecki","year":"2003","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_25","first-page":"403","article-title":"Rational function optimization using genetic algorithms","volume":"9","author":"Zoej","year":"2007","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_26","unstructured":"Toutin, T. (2011). Three-Dimensional Geometric Correction of Earth Observation Satellite Data. Advances in Environmental Remote Sensing, CRC Press."},{"key":"ref_27","first-page":"672","article-title":"Digital mapping using high resolution satellite imagery based on 2D affine projection model","volume":"33","author":"Ono","year":"2000","journal-title":"Int. Arch. Photogramm. Remote Sens."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"506","DOI":"10.1080\/10106049.2015.1059900","article-title":"Effect of sensor modelling methods on computation of 3-D coordinates from Cartosat-1 stereo data","volume":"31","author":"Singh","year":"2016","journal-title":"Geocarto Int."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"58","DOI":"10.1111\/j.1477-9730.2011.00665.x","article-title":"Review of developments in geometric modelling for high resolution satellite pushbroom sensors","volume":"27","author":"Poli","year":"2012","journal-title":"Photogramm. Rec."},{"key":"ref_30","unstructured":"Cheng, P., and Toutin, T. (2001, January 5\u20139). Ortho Rectification and DEM generation from high resolution satellite data. Proceedings of the 22nd Asian Conference on Remote Sensing, Singapore."},{"key":"ref_31","unstructured":"Qin, Z., Li, W., Li, M., Chen, Z., and Zhou, G. (2003, January 21\u201325). A methodology for true orthorectification of large-scale urban aerial images and automatic detection of building occlusions using digital surface model. Proceedings of the Geoscience and Remote Sensing Symposium, Toulouse, France."},{"key":"ref_32","first-page":"12","article-title":"Assessment of geometric accuracy of VHR satellite images","volume":"35","author":"Wolniewicz","year":"2004","journal-title":"Proceeding Xxth Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_33","first-page":"17","article-title":"Accuracy Assessment of User-Derived RFCs for Ortho-Rectification of High-Resolution Satellite Imagery","volume":"4","author":"Afify","year":"2008","journal-title":"Int. J. Geoinform."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"12","DOI":"10.9790\/0990-0161217","article-title":"Using rational polynomial functions for rectification of GeoEye-1 imagery","volume":"1","author":"Maglione","year":"2013","journal-title":"IOSR J. Appl. Geol. Geophys."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"41","DOI":"10.5721\/ItJRS20124414","article-title":"DSM generation from high resolution imagery: Applications with WorldView-1 and Geoeye-1","volume":"44","author":"Capaldo","year":"2012","journal-title":"Ital. J. Remote Sens."},{"key":"ref_36","first-page":"1347","article-title":"A comprehensive study of the rational function model for photogrammetric processing","volume":"67","author":"Tao","year":"2001","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Pavlis, N.K., Holmes, S.A., Kenyon, S.C., and Factor, J.K. (2012). The development and evaluation of the Earth Gravitational Model 2008 (EGM2008). J. Geophys. Res. Solid Earth, 117.","DOI":"10.1029\/2011JB008916"},{"key":"ref_38","first-page":"634","article-title":"Georeferencing performance of GEOEYE-1","volume":"75","author":"Fraser","year":"2009","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Raabe, E.A., and Stumpf, R.P. (1997). Image Processing Methods; Procedures in Selection, Registration, Normalization and Enhancement of Satellite Imagery in Coastal Wetlands.","DOI":"10.3133\/ofr97287"},{"key":"ref_40","unstructured":"Errico, A., Guastaferro, F., Parente, C., and Santamaria, R. (2010, January 29\u201330). Applications on geometric correction of different resolution satellite images. Proceedings of the IEEE GOLD Conference 2010, Livorno, Italy."},{"key":"ref_41","unstructured":"Guastaferro, F., Maglione, P., and Parente, C. (2012, January 3\u20137). Rectification of spot 5 satellite imagery for marine geographic information systems. Proceedings of the Advanced Research in Scientific Areas Virtual International Conference, \u017dilina, Slovakia."},{"key":"ref_42","unstructured":"Authority, T.V. (1998). Geospatial Positionng Accuracy Standards Part 3: National Standard for Spatial Data Accuracy."},{"key":"ref_43","unstructured":"Kapnias, D., Milenov, P., and Kay, S. (2008). Guidelines for Best Practice and Quality Checking of Ortho Imagery, Joint Research Centre."},{"key":"ref_44","unstructured":"McGlone, J. (2004). Manual of Photogrammetry, The American Society for Photogrammetry and Remote Sensing. [5th ed.]."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/6\/692\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T12:40:01Z","timestamp":1760186401000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/6\/692"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,3,22]]},"references-count":44,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2019,3]]}},"alternative-id":["rs11060692"],"URL":"https:\/\/doi.org\/10.3390\/rs11060692","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,3,22]]}}}