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However, images acquired by sensors onboard various satellite platforms are affected by a systematic sensor and platform\u2010induced geometry errors, which introduce terrain distortions, especially when the sensor does not point directly at the nadir location of the sensor. To this extent, an automated processing chain of WorldView\u20103 image orthorectification is presented using rational polynomial coefficient (RPC) model and laser scanning data. The research is aimed at analyzing the effects of varying resolution of the digital surface model (DSM) derived from high\u2010resolution laser scanning data, with a novel orthorectification model. The proposed method is validated on actual data in an urban environment with complex structures. This research suggests that a DSM of 0.31\u2009m spatial resolution is optimum to achieve practical results (root\u2010mean\u2010square error = 0.69\u2009m) and decreasing the spatial resolution to 20\u2009m leads to poor results (root\u2010mean\u2010square error = 7.17). Moreover, orthorectifying WorldView\u20103 images with freely available digital elevation models from Shuttle Radar Topography Mission (SRTM) (30\u2009m) can result in an RMSE of 7.94\u2009m without correcting the distortions in the building. This research can improve the understanding of appropriate image processing and improve the classification for feature extraction in urban areas.<\/jats:p>","DOI":"10.1155\/2021\/5273549","type":"journal-article","created":{"date-parts":[[2021,10,16]],"date-time":"2021-10-16T18:12:10Z","timestamp":1634407930000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Orthorectification of WorldView\u20103 Satellite Image Using Airborne Laser Scanning Data"],"prefix":"10.1155","volume":"2021","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9863-2054","authenticated-orcid":false,"given":"Biswajeet","family":"Pradhan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ahmed A.","family":"Ahmed","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0102-5424","authenticated-orcid":false,"given":"Subrata","family":"Chakraborty","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Abdullah","family":"Alamri","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7235-3225","authenticated-orcid":false,"given":"Chang-Wook","family":"Lee","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2021,10,16]]},"reference":[{"key":"e_1_2_8_1_2","doi-asserted-by":"publisher","DOI":"10.3390\/rs8100827"},{"key":"e_1_2_8_2_2","doi-asserted-by":"publisher","DOI":"10.3390\/rs8010070"},{"key":"e_1_2_8_3_2","doi-asserted-by":"publisher","DOI":"10.1007\/s12061-015-9139-1"},{"key":"e_1_2_8_4_2","volume-title":"Remote Sensing of Multimodal Transportation Systems","author":"Bridgelall R.","year":"2016"},{"key":"e_1_2_8_5_2","doi-asserted-by":"publisher","DOI":"10.5194\/isprsarchives-XLI-B7-563-2016"},{"key":"e_1_2_8_6_2","doi-asserted-by":"publisher","DOI":"10.3390\/rs8121003"},{"key":"e_1_2_8_7_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.scitotenv.2016.05.146"},{"key":"e_1_2_8_8_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2016.01.008"},{"key":"e_1_2_8_9_2","article-title":"Object extraction and revision by image analysis using existing geospatial data and knowledge: state-of-the-art and steps towards operational systems","volume":"2","author":"Baltsavias E. 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