Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/43364
Title: Orthorectification of WorldView-3 Satellite Image Using Airborne Laser Scanning Data
Contributor(s): Pradhan, Biswajeet (author); Ahmed, Ahmed A (author); Chakraborty, Subrata  (author)orcid ; Alamri, Abdullah (author); Lee, Chang-Wook (author)
Publication Date: 2021-10-16
Open Access: Yes
DOI: 10.1155/2021/5273549
Handle Link: https://hdl.handle.net/1959.11/43364
Abstract: 

Satellite images have been widely used to produce land use and land cover maps and to generate other thematic layers through image processing. However, images acquired by sensors onboard various satellite platforms are affected by a systematic sensor and platform-induced 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-3 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-resolution 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 m spatial resolution is optimum to achieve practical results (root-mean-square error = 0:69 m) and decreasing the spatial resolution to 20 m leads to poor results (root-mean-square error = 7:17). Moreover, orthorectifying WorldView-3 images with freely available digital elevation models from Shuttle Radar Topography Mission (SRTM) (30 m) can result in an RMSE of 7.94 m 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.

Publication Type: Journal Article
Source of Publication: Journal of Sensors, v.2021, p. 1-12
Publisher: Hindawi Limited
Place of Publication: United Kingdom
ISSN: 1687-7268
1687-725X
Fields of Research (FoR) 2020: 460106 Spatial data and applications
460306 Image processing
461103 Deep learning
Socio-Economic Objective (SEO) 2020: 280115 Expanding knowledge in the information and computing sciences
Peer Reviewed: Yes
HERDC Category Description: C1 Refereed Article in a Scholarly Journal
Appears in Collections:Journal Article
School of Science and Technology

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