Land-use/cover classification in a heterogeneous coastal landscape using RapidEye imagery: evaluating the performance of random forest and support vector machines classifiers

Author：        

Publisher： Taylor & Francis Ltd

ISSN： 1366-5901

Source： International Journal of Remote Sensing, Vol.35, Iss.10, 2014-05, pp. : 3440-3458

Disclaimer: Any content in publications that violate the sovereignty, the constitution or regulations of the PRC is not accepted or approved by CNPIEC.

Previous Menu Next

Related content

An assessment of support vector machines for land cover classification

By Huang C.   Davis L. S.   Townshend J. R. G.  

International Journal of Remote Sensing, Vol. 23, Iss. 4, 2002-02 ,pp. : 725-749

Taylor & Francis Ltd

Access to resources Recommend Favorite

Ensemble of support vector machines for land cover classification

By Pal M.  

International Journal of Remote Sensing, Vol. 29, Iss. 10, 2008-01 ,pp. : 3043-3049

Taylor & Francis Ltd

Access to resources Recommend Favorite

Multitemporal land-cover classification of Mexico using Landsat MSS imagery

By ALVAREZ R.   BONIFAZ R.   LUNETTA R. S.   GARCÍA C.   GÓMEZ G.   CASTRO R.   BERNAL A.   CABRERA A. L.  

International Journal of Remote Sensing, Vol. 24, Iss. 12, 2003-01 ,pp. : 2501-2514

Taylor & Francis Ltd

Access to resources Recommend Favorite

Crop and land cover classification in Iran using Landsat 7 imagery

By Akbari M.   Mamanpoush A. r.   Gieske A.   Miranzadeh M.   Torabi M.   Salemi H. R.  

International Journal of Remote Sensing, Vol. 27, Iss. 19, 2006-10 ,pp. : 4117-4135

Taylor & Francis Ltd

Access to resources Recommend Favorite

Multi-temporal RADARSAT-2 polarimetric SAR data for urban land-cover classification using an object-based support vector machine and a rule-based approach

By Niu Xin   Ban Yifang  

International Journal of Remote Sensing, Vol. 34, Iss. 1, 2013-01 ,pp. : 1-26

Taylor & Francis Ltd

Access to resources Recommend Favorite