Establishment of land cover map using object-oriented classification method for VNREDSat-1 data

  • Affiliations:

    1 Faculty of Geomatics and Land Administration, Hanoi University of Mining and Geology, Vietnam 2 Vietnam Institute of Geodesy and Cartography, Vietnam 3 Photography office, Geodesic Enterprise, Survey and Aerial Mapping One Member Limited Liability Company (SAMCOM Co.Ltd) , Vietnam 4 Center for Technical Resources and Environment of Dong Nai Province, Vietnam 5 Office land registration of Bac Tan Uyen district, Binh Duong provice, Vietnam 6 Resources and Environmental office of Di An town, Binh Duong province, Vietnam 7 Faculty of Surveying, Mapping and Geographic Information, Ho Chi Minh University of Natural Resources and Environment, Vietnam

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  • Received: 19th-Jan-2020
  • Revised: 6th-Mar-2020
  • Accepted: 29th-Apr-2020
  • Online: 28th-Apr-2020
Pages: 135 - 145
Views: 2198
Downloads: 1205
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Abstract:

Land cover/land use classification using high resolution remote sensing data has the biggest challenge is how to distinguish object classes from different spectral values, structures, shapes, and spatial elements. This paper reveals the object-oriented classification method to establish the land cover map using VNREDSat-1 data, with a spatial resolution of 10 m. Land cover/land use system is classified according to CORINE with level 3 with 14 types of land cover/land use. Extraction of 14 types of land cover/land use using object-oriented classification method based on reflectance spectral characteristics, shape index, location of objects, brightness, NDVI plant index, and density objects. The overall accuracy of classification result is about 0.71%.

How to Cite
Pham, L.Thi, , ., Nguyen, S.Phi, Nguyen, N.Viet, Dao, H.Van, Doan, L.Duc, Vo, N.Hong Thi, Nguyen, T.Thu Thi, Tran, H.Van and Le, N.Thanh 2020. Establishment of land cover map using object-oriented classification method for VNREDSat-1 data (in Vietnamese). Journal of Mining and Earth Sciences. 61, 2 (Apr, 2020), 135-145. DOI:https://doi.org/10.46326/JMES.2020.61(2).15.
References

Antonio, D. G. and Jansen, L. M., (1998). Land cover classification System (LCCS): Classification Concepts and User Manual. Food and Agriculture Organization of the United Nations, Rome.

Benz, U. C., Peter, H., Gregor, W., Iris L., Markus, H., (2004). Multi-resolution, object-oriented fuzzy analysis of remote sensing data for GIS-ready information. ISPRS Journal of Photogrammetry and Remote Sensing 58(3-4), 239-258.

Bolstad, P. V., Gessler, P., Lillesand, T. M., (1990). Positional uncertainty in manually digitized map data. International Journal of Geographical Information Systems 4. 399-412.

Choodarathnakara, Ashok Kumar Dr. T., Shivaprakash Koliwad Dr., Patil Dr. C. G., (2012). Soft Classification Techniques for RS Data. IJCSET 2 (11). 1468 - 1471.

Congalton, R. G. and Green, K., (2008). Assessing the accuracy of remotely sensed data: Principies and practices. New York. Taylorand Francis Group.

Jitendra Malik, S. B., Thomas Leung and Jianbi Shi (2001). Contour and Texture Analysis for Image Segmentation. International Journal of Computer Vision 43(1). 7 -27.

Mario, C., (2009). ESA advanced training course on land remote sensing: image classification. ESA.

Nedeljkovic, I., (2004). Image classification base on fuzzy logic. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences 34(XXX).

Nguyễn Ngọc Thạch, (2005). Cơ sở Viễn Thám. Hà Nội, Đại học Khoa học Tự nhiên.

Roostaei, A. S. A., Nikjoo.M. R. and Valizadeh K.,