Evaluating the effects of spatial resolution on land use and land cover classification accuracy

被引：0

作者：

Mishra, Varun Narayan ^{[1
]}

Prasad, Rajendra ^{[1
]}

Kumar, Pradeep ^{[1
]}

Gupta, Dileep Kumar ^{[1
]}

Dikshit, Prabhat Kumar Singh ^{[2
]}

Dwivedi, Shyam Bihari ^{[2
]}

Ohri, Anurag ^{[2
]}

机构：

[1] Indian Inst Technol BHU, Dept Phys, Varanasi, Uttar Pradesh, India

[2] Indian Inst Technol BHU, Dept Civil Engn, Varanasi, Uttar Pradesh, India

来源：

2015 INTERNATIONAL CONFERENCE ON MICROWAVE, OPTICAL AND COMMUNICATION ENGINEERING (ICMOCE) | 2015年

关键词：

LULC; LISS IV; Landsat; 8-OLI; MLC; accuracy; ARTIFICIAL NEURAL-NETWORK; MAXIMUM-LIKELIHOOD; ALGORITHMS; SELECTION;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

The choice of appropriate spatial resolution is a key factor to extract desired information from remotely sensed images. Optical data collected by two different sensors (LISS IV with 5.8 m and Landsat 8-OLI with 30 m spatial resolution respectively) were investigated against the capability to classify accurately into distinct land use and land cover (LULC) classes. To evaluate the quality of training samples class separability analysis using transformed divergence (TD) method was performed. Furthermore, supervised maximum likelihood classifier (MLC) was used to carry out LULC classification. The results indicated that the overall accuracy 83.28% and Kappa coefficient 0.805 for LISS IV image was found higher in comparison to Landsat 8-OLI image having overall accuracy 77.93% and Kappa coefficient 0.742 respectively.

引用

页码：208 / 211

页数：4

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