Assessment of Spatio-Temporal Changes in Land Use/Land Cover Over a Decade (2000–2014) Using Earth Observation Datasets: A Case Study of Varanasi District, India

A remote sensing aided multi-layer perceptron-Markov chain analysis for land use and land cover change prediction in Patna district (Bihar), India

(2016) Varun Narayan Mishra et al.   Arabian Journal of Geosciences

Comparison of support vector machine, artificial neural network, and spectral angle mapper algorithms for crop classification using LISS IV data

(2015) Pradeep Kumar et al.   INTERNATIONAL JOURNAL OF REMOTE SENSING

Continuous change detection and classification of land cover using all available Landsat data

(2014) Zhe Zhu et al.   REMOTE SENSING OF ENVIRONMENT

Assessment of the land use/land cover (LU/LC) and mangrove changes along the Mandovi–Zuari estuarine complex of Goa, India

(2013) Ankita Misra et al.   Arabian Journal of Geosciences

Appraisal of land use/land cover of mangrove forest ecosystem using support vector machine

(2013) Sudhir Kumar Singh et al.   Environmental Earth Sciences

Object-oriented mapping of urban trees using Random Forest classifiers

(2013) Anne Puissant et al.   International Journal of Applied Earth Observation and Geoinformation

Selection of classification techniques for land use/land cover change investigation

(2012) Prashant K. Srivastava et al.   ADVANCES IN SPACE RESEARCH

Finer resolution observation and monitoring of global land cover: first mapping results with Landsat TM and ETM+ data

(2012) Peng Gong et al.   INTERNATIONAL JOURNAL OF REMOTE SENSING

Feature Selection for Classification of Hyperspectral Data by SVM

(2010) Mahesh Pal et al.   IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING

Support vector machines in remote sensing: A review

(2010) Giorgos Mountrakis et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

Land cover change assessment using decision trees, support vector machines and maximum likelihood classification algorithms

(2009) J.R. Otukei et al.   International Journal of Applied Earth Observation and Geoinformation

Increasing the accuracy of neural network classification using refined training data

(2008) Taskin Kavzoglu   ENVIRONMENTAL MODELLING & SOFTWARE