Research and Driving Force Analysis of Remote Sensing Images based on ENVI in Urban Expansion in Xining Municipal District

With the deepening of reform and opening up and rapid economic development, the development of Xining City has been accelerating, and the urbanization level of the study area represented by the municipal district of Xining City has received more and more attention under this social background. Combined with the Landsat remote sensing images from 2008 to 2018 and ENVI processing software, the building information of Xining City was extracted by the methods of Normalized Building Index (NDBI), Improved Normalized Bare Index (MNDBI) and Urban Land Use Index (ULI), and the differences between the three were analyzed by confusion matrix and Kappa coefficient, and the results showed that the total accuracy of NDBI was 78.75%, The Kappa coefficient was 0.56, the total accuracy of MNDBI was 82.50%, the Kappa coefficient was 0.56, the total accuracy of ULI was 92.50%, and the Kappa coefficient was 0.81. On this basis, the results show that the development rate of Xining City was stable from 2008 to 2014, and the development rate increased suddenly from 2014 to 2018, and then the driving factors of the change of construction area were analyzed.

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Publication Details

Journal
International Journal of Social Sciences and Public Administration
Published
2025-03-11
DOI
https://doi.org/10.62051/ijsspa.v6n2.22
Primary Topic
Remote Sensing and Land Use
Type
article
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article

Research and Driving Force Analysis of Remote Sensing Images based on ENVI in Urban Expansion in Xining Municipal District

Kun Wang
International Journal of Social Sciences and Public Administration
Remote Sensing and Land Use
article

Research and Driving Force Analysis of Remote Sensing Images based on ENVI in Urban Expansion in Xining Municipal District

Kun Wang
article en

Abstract

With the deepening of reform and opening up and rapid economic development, the development of Xining City has been accelerating, and the urbanization level of the study area represented by the municipal district of Xining City has received more and more attention under this social background. Combined with the Landsat remote sensing images from 2008 to 2018 and ENVI processing software, the building information of Xining City was extracted by the methods of Normalized Building Index (NDBI), Improved Normalized Bare Index (MNDBI) and Urban Land Use Index (ULI), and the differences between the three were analyzed by confusion matrix and Kappa coefficient, and the results showed that the total accuracy of NDBI was 78.75%, The Kappa coefficient was 0.56, the total accuracy of MNDBI was 82.50%, the Kappa coefficient was 0.56, the total accuracy of ULI was 92.50%, and the Kappa coefficient was 0.81. On this basis, the results show that the development rate of Xining City was stable from 2008 to 2014, and the development rate increased suddenly from 2014 to 2018, and then the driving factors of the change of construction area were analyzed.

International Journal of Social Sciences and Public AdministrationVol. 6(2)
Openalex Percentile: Top 90%
Remote Sensing and Land Use
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Research and Driving Force Analysis of Remote Sensing Images based on ENVI in Urban Expansion in Xining Municipal District — Kun Wang · International Journal of Social Sciences and Public Administration (2025) | TGRS Research Map | TGRS