An analysis of change detection in land use land cover area of remotely sensed data using supervised classifier

IF 0.5 Q4 ENGINEERING, ENVIRONMENTAL International Journal of Environmental Technology and Management Pub Date : 2023-01-01 DOI:10.1504/ijetm.2023.134322
H.N. Mahendra, S. Mallikarjunaswamy
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Abstract

In the present work, change detection in land use and land cover (LULC) area of Chikkamagaluru district were assessed using remote sensing data and supervised classifier. Chikkamagaluru district is known for the green cover; therefore an analysis of the land use land cover of the district is the main objective of this work. The change detection of an entire Chikkamagaluru district has been carried out for the period between 2017 and 2021 by using Sentinel-2 multispectral remote sensing data. Supervised classification-based support vector machines (SVM) have been applied to assess the LULC of the study area. An experimental result shows the positive changes in vegetation cover, water bodies, and negative changes observed in bare ground and rangeland. Overall classification accuracy of the SVM was estimated to be 86.30% for 2017 and 85.36% for 2021. The performance of SVM is also compared with the other supervised classifiers such as neural networks, maximum likelihood classifier (MLC), minimum-distance-to-means, and Mahalanobis distance. The comparison results show that SVMs provide better classification results as compared to other supervised classifiers.
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基于监督分类器的遥感土地利用土地覆盖面积变化检测分析
利用遥感数据和监督分类器对奇卡马加鲁鲁地区土地利用和土地覆盖(LULC)区域的变化检测进行了评估。Chikkamagaluru地区以绿色覆盖而闻名;因此,分析该区的土地利用和土地覆被是本工作的主要目的。2017年至2021年期间,利用Sentinel-2多光谱遥感数据对整个Chikkamagaluru地区进行了变化检测。应用基于监督分类的支持向量机(SVM)对研究区域的LULC进行评估。实验结果表明,植被覆盖度、水体呈正变化,裸地和牧场呈负变化。2017年SVM总体分类准确率为86.30%,2021年为85.36%。SVM的性能还与其他监督分类器如神经网络、最大似然分类器(MLC)、最小距离均值和马氏距离进行了比较。对比结果表明,与其他监督分类器相比,svm提供了更好的分类结果。
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来源期刊
CiteScore
1.00
自引率
0.00%
发文量
66
期刊介绍: IJETM is a refereed and authoritative source of information in the field of environmental technology and management. Together with its sister publications IJEP and IJGEnvI, it provides a comprehensive coverage of environmental issues. It deals with the shorter-term, covering both engineering/technical and management solutions.
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