… on monitoring land cover changes … land use/land cover (LULC) estimation was done by a
unique hybrid classification approach consisting of unsupervised and support vector machine (…

… for modeling urban land use change that explicitly considers multiple land use classes and
… to predict a future land use class based on present spatial attributes and a land use class in …

… This paper presents a study that tests the support vector machines (SVM) as a method for
defining nonlinear transition rules for CA. SVM is a data mining technique whose performance …

<p>The support vector machine (SVM) is a group of theoretically superior machine learning …
, stability and training speed in deriving land cover classifications from satellite images. The …

… main problems that traditional support vector machine (SVM) … classification and aggregation
of land use data in urban industry. … The efficiency of land use real-time analysis is improved. …

… Land cover/use classification using remotely sensed images … Support vector machines
(SVMs) are a group of supervised … In this study, SVMs were used for land cover classification of …

… major land-cover categories … the support vector classification. These findings reported
here can help establish a practical guidance on the use of support vector machines for land-cover …

… (HSR) satellite imagery, urban land use/land cover (LULC) mapping has become one of the
… state-of-the art ensemble and/or Support Vector Machines (SVM) algorithms in the context of …

… This work focused on the land use classification of a subset image of South West Florida,
from Landsat TM 5 data. The study area is shown in figure 1 and the corresponding satellite …

… of land-usechange patterns. This paper presents a novel method to model urban land-use
change using support-vector machines (SVMs), a new generation of machine learning …