Land Use/ Land Cover Classification of Google Earth Imagery

Google Earth is a source of high spatial resolution images. The freely available Google Earth (GE) images are utilized to generate Land use/Land cover thematic map of the highly heterogeneous landscape of typical urban scene. In this paper, we have presented Euclidean Distance and Average Pixel Inte...

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Bibliographic Details
Published in2017 IEEE International WIE Conference on Electrical and Computer Engineering (WIECON ECE) pp. 10 - 13
Main Authors Sowmya, D R, Hegde, Vishwas S, Suhas, J, Hegdekatte, Raghavendra V, Shenoy, P Deepa, Venugopal, K R
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2017
Subjects
Buildings
Classification Accuracy
Classification algorithms
Earth
Google
Google Earth Imagery
Image color analysis
Image resolution
K-Nearest Neighbour
Land Use/Land Cover
User's accuracy
Vegetation mapping
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DOI10.1109/WIECON-ECE.2017.8468898

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Summary:Google Earth is a source of high spatial resolution images. The freely available Google Earth (GE) images are utilized to generate Land use/Land cover thematic map of the highly heterogeneous landscape of typical urban scene. In this paper, we have presented Euclidean Distance and Average Pixel Intensity based K-NN classification to classify five different land objects. The classification accuracy of the proposed method is compared against generic K-NN. The overall classification accuracy and the kappa value of generic K-NN are found to be 75.04% and 0.74 respectively. Whereas, proposed method results with 76.38% and 0.78. Both the methods exhibits classification error because of poor spectral reflectance properties of google earth imagery.
DOI:10.1109/WIECON-ECE.2017.8468898