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Classification is the most important method to determine type of crop contained in a region for agricultural planning. There are two types of the classification. First is pixel based and the other is ...
The evaluation of pavement conditions is an important part of pavement management. Traditionally, pavement condition data are gathered by human inspectors who walk or drive along the road to assess th...
It is still an open problem to extract road feature from high-resolution remote sensing image, although this topic had been intensively investigated and many methods had been put forwards. All works f...
Automatic image categorization using low-level features is a challenging research topic in remote sensing application. In this paper, we formulate the image categorization problem as an image texture ...
The remote sensing community has long been active in developing, evaluating, and comparing different classification algorithms using a variety of remotely sensed imagery. As an integral component of i...
We present a new object-oriented land cover classification method based on Support Vector Machine (SVM) by fusing spectral and textural information of High-Resolution (HR) aerial imagery and Digital...
This study focuses on the comparison between the classical and object-oriented image classifications of remote sensing imagery in the arid area. Due to its special geographic environment and socio-e...
Agricultural land use mapping and change detection are important for environmental assessment and crop yield estimation. An effective mapping and change detection of crop land use requires large ima...
Classification of remotely sensed images is often based on assigning classes on a ‘per-pixel’ basis and therefore ignoring spatial information captured by the image. In this paper a method is propose...

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