Decadal Urban Growth Analysis of Prayagraj City During 2015-2024 Using Landsat-8 Multispectral Data

The present study analyzes the decadal urban growth of Prayagraj city using Landsat-8 multispectral images. For this purpose, the images during 2015 and 2024 are selected and processed for urban area extraction with the perspective of a smart city development. The images are classified using multiclass SVM into four major land covers focussing on urban class. The extracted urban area from the classified maps is measured into real units for the analysis of change in the land cover to investigate decadal changes. For change analysis, the images are used for direct differencing as well as classification based differencing which reflects the change maps before and after classification. The post classification change statistics is also measured and analyzed for urban growth. The classification accuracy using SVM varies between 90 % and 99 % with a kappa coefficient between 0.87 and 0.98 which can be considered significant. It is observed that the urban area has grown in a rapid manner in the last decade with a good amount of infrastructure developed including road and rail networks which are the backbone of a smart city. The novelty of the work is extraction and analysis of change statistics obtained after classification.

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Published
2024-11-29
DOI
https://doi.org/10.1109/upcon62832.2024.10983762
Primary Topic
Remote Sensing in Agriculture
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article
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article

Decadal Urban Growth Analysis of Prayagraj City During 2015-2024 Using Landsat-8 Multispectral Data

Triloki Pant, P. K. Srivastava, Chandrakant Kumar Singh
Remote Sensing in Agriculture
article

Decadal Urban Growth Analysis of Prayagraj City During 2015-2024 Using Landsat-8 Multispectral Data

Triloki Pant, P. K. Srivastava, Chandrakant Kumar Singh
article en

Abstract

The present study analyzes the decadal urban growth of Prayagraj city using Landsat-8 multispectral images. For this purpose, the images during 2015 and 2024 are selected and processed for urban area extraction with the perspective of a smart city development. The images are classified using multiclass SVM into four major land covers focussing on urban class. The extracted urban area from the classified maps is measured into real units for the analysis of change in the land cover to investigate decadal changes. For change analysis, the images are used for direct differencing as well as classification based differencing which reflects the change maps before and after classification. The post classification change statistics is also measured and analyzed for urban growth. The classification accuracy using SVM varies between 90 % and 99 % with a kappa coefficient between 0.87 and 0.98 which can be considered significant. It is observed that the urban area has grown in a rapid manner in the last decade with a good amount of infrastructure developed including road and rail networks which are the backbone of a smart city. The novelty of the work is extraction and analysis of change statistics obtained after classification.

Indian Institute of Information Technology Allahabad (IN)
Sustainable cities and communities
Openalex Percentile: Top 73%
Remote Sensing in Agriculture
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Decadal Urban Growth Analysis of Prayagraj City During 2015-2024 Using Landsat-8 Multispectral Data — Triloki Pant, P. K. Srivastava, et al. · (2024) | TGRS Research Map | TGRS