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

Autor:	Xi jun Hu, Shi yi Cao
Rok vydání:	2021
Předmět:	Set (abstract data type) Environmental Engineering Dynamic prediction Remote sensing (archaeology) Computer science Atmospheric correction Pattern analysis Management Monitoring Policy and Law Remote sensing image fusion Urban landscape Image (mathematics) Remote sensing
Zdroj:	International Journal of Environmental Technology and Management. 24:18
ISSN:	1741-511X 1466-2132
DOI:	10.1504/ijetm.2021.10038728
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::af962d793e6bfadabd92dbd8759c3cec https://doi.org/10.1504/ijetm.2021.10038728 Zobrazit plný text záznamu