Cargando…
Research on Land Use Planning Based on Multisource Remote Sensing Data
Land use changes are analyzed correctly, a series of improvements according to the changes are carried out appropriately, the relationship between land use development and economic and human survival is handled correctly, and the healthy and orderly development of the entire society is promoted. Aim...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9259274/ https://www.ncbi.nlm.nih.gov/pubmed/35814598 http://dx.doi.org/10.1155/2022/5851768 |
_version_ | 1784741740554485760 |
---|---|
author | Jia, Wei Pei, Tingting Lei, Kai |
author_facet | Jia, Wei Pei, Tingting Lei, Kai |
author_sort | Jia, Wei |
collection | PubMed |
description | Land use changes are analyzed correctly, a series of improvements according to the changes are carried out appropriately, the relationship between land use development and economic and human survival is handled correctly, and the healthy and orderly development of the entire society is promoted. Aiming at the combination of multisource remote sensing data and monitoring changes in land planning, this study uses CBERS data and ASAR data as multisource remote sensing data sources to conduct in-depth research and discussion on the land use change in this area and uses the HPF pixel-level fusion method for data fusion to generate HPF. The data are integrated, and then, the CBERS data and HPF fusion data are used to extract the land use type information of Zhenning County, respectively, and a confusion matrix is built based on the field sample points to verify the accuracy, compare and analyze the relative error of the land use type information extraction before and after data fusion, and evaluate the CBERS data. Regarding the extraction effect of land use type information of fusion data with HPF, the results show that the two kinds of remote sensing data have good effects in extracting water body type information, and the accuracy has reached 100%. Using multisource remote sensing image processing can well summarize and analyze land use changes and make the changes in various indicators in the study area. Accurate statistics is obtained. |
format | Online Article Text |
id | pubmed-9259274 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-92592742022-07-07 Research on Land Use Planning Based on Multisource Remote Sensing Data Jia, Wei Pei, Tingting Lei, Kai Comput Intell Neurosci Research Article Land use changes are analyzed correctly, a series of improvements according to the changes are carried out appropriately, the relationship between land use development and economic and human survival is handled correctly, and the healthy and orderly development of the entire society is promoted. Aiming at the combination of multisource remote sensing data and monitoring changes in land planning, this study uses CBERS data and ASAR data as multisource remote sensing data sources to conduct in-depth research and discussion on the land use change in this area and uses the HPF pixel-level fusion method for data fusion to generate HPF. The data are integrated, and then, the CBERS data and HPF fusion data are used to extract the land use type information of Zhenning County, respectively, and a confusion matrix is built based on the field sample points to verify the accuracy, compare and analyze the relative error of the land use type information extraction before and after data fusion, and evaluate the CBERS data. Regarding the extraction effect of land use type information of fusion data with HPF, the results show that the two kinds of remote sensing data have good effects in extracting water body type information, and the accuracy has reached 100%. Using multisource remote sensing image processing can well summarize and analyze land use changes and make the changes in various indicators in the study area. Accurate statistics is obtained. Hindawi 2022-06-29 /pmc/articles/PMC9259274/ /pubmed/35814598 http://dx.doi.org/10.1155/2022/5851768 Text en Copyright © 2022 Wei Jia et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Jia, Wei Pei, Tingting Lei, Kai Research on Land Use Planning Based on Multisource Remote Sensing Data |
title | Research on Land Use Planning Based on Multisource Remote Sensing Data |
title_full | Research on Land Use Planning Based on Multisource Remote Sensing Data |
title_fullStr | Research on Land Use Planning Based on Multisource Remote Sensing Data |
title_full_unstemmed | Research on Land Use Planning Based on Multisource Remote Sensing Data |
title_short | Research on Land Use Planning Based on Multisource Remote Sensing Data |
title_sort | research on land use planning based on multisource remote sensing data |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9259274/ https://www.ncbi.nlm.nih.gov/pubmed/35814598 http://dx.doi.org/10.1155/2022/5851768 |
work_keys_str_mv | AT jiawei researchonlanduseplanningbasedonmultisourceremotesensingdata AT peitingting researchonlanduseplanningbasedonmultisourceremotesensingdata AT leikai researchonlanduseplanningbasedonmultisourceremotesensingdata |