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Analysis of regional economic development based on land use and land cover change information derived from Landsat imagery
The monitoring of economic activities is of great significance for understanding regional economic development level and policymaking. As the carrier of economic activities, land resource is an indispensable production factor of economic development, and economic growth leads to increased demand for...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7391701/ https://www.ncbi.nlm.nih.gov/pubmed/32728061 http://dx.doi.org/10.1038/s41598-020-69716-2 |
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author | Chen, Chao He, Xinyue Liu, Zhisong Sun, Weiwei Dong, Heng Chu, Yanli |
author_facet | Chen, Chao He, Xinyue Liu, Zhisong Sun, Weiwei Dong, Heng Chu, Yanli |
author_sort | Chen, Chao |
collection | PubMed |
description | The monitoring of economic activities is of great significance for understanding regional economic development level and policymaking. As the carrier of economic activities, land resource is an indispensable production factor of economic development, and economic growth leads to increased demand for land as well as changes in land utilization form. As an important means of earth observation, remote-sensing technology can obtain the information of land use and land cover change (LUCC) related to economic activities. This study proposes a method for analysing regional economic situations based on remote-sensing technology, from which LUCC information extraction, sensitivity factor selection, model construction and accuracy evaluation were implemented. This approach was validated with experiments in Zhoushan City, China. The results show that the economic statistical index is most sensitive to the construction land area, and the average correlation coefficient between the actual data and the predicted data is 0.949, and the average of mean relative error is 14.21%. Therefore, this paper suggests that LUCC could be utilised as an explanatory indicator for estimating economic development at the regional level, and the potential applications of remotely-sensed image in economic activity monitoring are worth pursuing. |
format | Online Article Text |
id | pubmed-7391701 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-73917012020-07-31 Analysis of regional economic development based on land use and land cover change information derived from Landsat imagery Chen, Chao He, Xinyue Liu, Zhisong Sun, Weiwei Dong, Heng Chu, Yanli Sci Rep Article The monitoring of economic activities is of great significance for understanding regional economic development level and policymaking. As the carrier of economic activities, land resource is an indispensable production factor of economic development, and economic growth leads to increased demand for land as well as changes in land utilization form. As an important means of earth observation, remote-sensing technology can obtain the information of land use and land cover change (LUCC) related to economic activities. This study proposes a method for analysing regional economic situations based on remote-sensing technology, from which LUCC information extraction, sensitivity factor selection, model construction and accuracy evaluation were implemented. This approach was validated with experiments in Zhoushan City, China. The results show that the economic statistical index is most sensitive to the construction land area, and the average correlation coefficient between the actual data and the predicted data is 0.949, and the average of mean relative error is 14.21%. Therefore, this paper suggests that LUCC could be utilised as an explanatory indicator for estimating economic development at the regional level, and the potential applications of remotely-sensed image in economic activity monitoring are worth pursuing. Nature Publishing Group UK 2020-07-29 /pmc/articles/PMC7391701/ /pubmed/32728061 http://dx.doi.org/10.1038/s41598-020-69716-2 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Chen, Chao He, Xinyue Liu, Zhisong Sun, Weiwei Dong, Heng Chu, Yanli Analysis of regional economic development based on land use and land cover change information derived from Landsat imagery |
title | Analysis of regional economic development based on land use and land cover change information derived from Landsat imagery |
title_full | Analysis of regional economic development based on land use and land cover change information derived from Landsat imagery |
title_fullStr | Analysis of regional economic development based on land use and land cover change information derived from Landsat imagery |
title_full_unstemmed | Analysis of regional economic development based on land use and land cover change information derived from Landsat imagery |
title_short | Analysis of regional economic development based on land use and land cover change information derived from Landsat imagery |
title_sort | analysis of regional economic development based on land use and land cover change information derived from landsat imagery |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7391701/ https://www.ncbi.nlm.nih.gov/pubmed/32728061 http://dx.doi.org/10.1038/s41598-020-69716-2 |
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