Title: Dynamic prediction of urban landscape pattern based on remote sensing image fusion

Authors: Shi-yi Cao; Xi-jun Hu

Addresses: School of Landscape Architecture, Central South University of Forestry and Technology, Changsha 4140004, China; College of Civil Engineering and Architecture, Hunan Institute of Science and Technology, Yueyang 414006, China ' School of Landscape Architecture, Central South University of Forestry and Technology, Changsha 4140004, China

Abstract: In order to overcome the problems of large prediction error and slow prediction speed in dynamic prediction method of urban landscape, a new dynamic prediction method of urban landscape pattern based on remote sensing image fusion is proposed. The high-resolution remote sensing image is preprocessed by atmospheric correction and radiometric correction to obtain the fusion result of high-resolution remote sensing image. The urban landscape information is extracted from the fusion results, and the corresponding urban landscape pattern analysis model is built. The landscape pattern index is set up in the model, and the dynamic prediction of urban landscape pattern is completed by combining the characteristics of index change with the driving force and image factors of urban pattern change. The experimental results show that the average prediction error is 1.56, and the operation delay is reduced by 2 s-3 s.

Keywords: fusion; remote sensing image; urban landscape pattern; dynamic prediction.

DOI: 10.1504/IJETM.2021.115726

International Journal of Environmental Technology and Management, 2021 Vol.24 No.1/2, pp.18 - 32

Received: 24 Apr 2020
Accepted: 12 Nov 2020
Published online: 18 Jun 2021 *

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