A Method of Detecting Land Use Change of Remote Sensing Images based on Texture Features and DEM

机译：基于纹理特征和DEM的遥感影像土地利用变化检测方法

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In this paper, a combination method, between the neural network and textures information, is proposed to remote sensing images classification. The methodology involves an extraction of texture features using the gray level co-occurrence matrix and image classification with BP artificial neural network. The combination of texture features and the digital elevation model (DEM) as classified bands to neural network were used to recognized different classes. This scheme shows high recognition accuracy in the classification of remote sensing images. In the experiments, the proposed method was successfully applied to remote sensing image classification and Land Use Change Detection, in the meanwhile, the effectiveness of the proposed method was verified.

机译：本文提出了一种将神经网络与纹理信息结合起来的方法，用于遥感图像的分类。该方法涉及使用灰度共生矩阵提取纹理特征，并使用BP人工神经网络对图像进行分类。纹理特征和数字高程模型（DEM）作为神经网络的分类带的组合用于识别不同的类别。该方案在遥感图像分类中显示出较高的识别精度。在实验中，将该方法成功应用于遥感图像分类和土地利用变化检测，同时验证了该方法的有效性。

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《International conference on intelligent earth observing and applications》|2015年|980822.1-980822.6|共6页
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Dong-ming Huang; Chun-tao WEI; Jun-chen Yu; Jian-lin Wang;
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关键词
Land use; change detection; remote sensing; BP artificial neural network; texture;

机译：土地利用;变更检测;遥感; BP人工神经网络;质地;

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4. A Method of Detecting Land Use Change of Remote Sensing Images based on Texture Features and DEM [C] . Dong-ming Huang, Chun-tao WEI, Jun-chen Yu, International conference on intelligent earth observing and applications . 2015

机译：一种检测基于纹理特征和DEM的遥感图像土地利用变化的方法
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8. Textural Features for Image Classification in Remote Sensing [R] . Haertel, V., Shimabukuro, Y. E. 1987

机译：遥感图像分类的纹理特征

A Method of Detecting Land Use Change of Remote Sensing Images based on Texture Features and DEM

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