干旱区生态环境知识资源中心(Arid): BP神经网络的沙漠化土地信息提取研究

Arid

	BP神经网络的沙漠化土地信息提取研究
其他题名	Study on Extracting the Information about Desertified Lands Based on Principal Component Fusion and BP Neural Network
	买买提·沙吾提; 塔西甫拉提·特依拜; 丁建丽; 何祺胜
ISSN	1001-4675
出版年	2008
卷号	25 期号:5 页码:647-652
中文摘要	以塔克拉玛干沙漠南缘策勒绿洲为例，探讨了基于主成分融合的沙漠化信息的提取方法。由于Landsat-7 ETM＋的全色波段与多光谱波段有相同成像条件，影像获取时间一致，两种不同分辨率的数据可以不经配准而实现高精度融合。首先，对Landsat-7 ETM＋的全色图像与多光谱图像进行主成分融合处理，再利用BP神经网络模型，以相同的训练样本分别对融合前后的影像进行分类，在此基础上进行沙漠化信息的提取。结果表明：主成分变换融合图像的光谱信息保持性、信息量以及空间分解力都较高，且分类精度比Landsat-7 ETM＋多光谱图像有较大提高，是监测沙漠化土地变化的有效手段。
英文摘要	Sandy desertification is a severe environmental problem in arid areas, which threatens certainly the stability and sustainable development of oases, so it is very important to timely wxtraet the information and spatial distribution of sandy desertifieation by applying remote sensing means. In this paper, the PCA data fusion methods and BP network classification for deriving the information of desertified lands in Qira Oasis located in the central southern marginal zone of the Taklimakan are researched. Because the Landsat-7 ETM ＋ Panchromatic band and the muhispectral bands can be simultaneously obtained from the same sensor system under the same imaging conditions, it is available to get best data fusion results without registration. Firstly, Principal Component Analysis （PCA） is used to fuse the panchromatic and muhispectral images of Landsat-7 ETM ＋ Satellite. And then, the BP Neural Network classification method is applied to classify the Landsat-7 ETM ＋ muhispectral bands and the fusion images with the same training samples. The results reveal that PCA fusion image has more information and higher spatial resolution while maintaining the basic spectral characteristics of the original image, and also has a higher classification accuracy of the results than the Landsat-7 ETM ＋ muhispectral image. It is useful to detect and monitor sandy desertification change in arid areas.
中文关键词	沙漠化 ; 遥感 ; 数据融合 ; PCA变换 ; BP神经网络 ; 塔克拉玛干沙漠 ; 策勒绿洲
英文关键词	sandy desertification remote sensing data fusion PCA BP Neural Network.
语种	中文
国家	中国
收录类别	CSCD
WOS类目	REMOTE SENSING
WOS研究方向	Remote Sensing
CSCD记录号	CSCD:3387771
来源机构	新疆大学
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/222344
作者单位	新疆大学资源与环境科学学院, 乌鲁木齐, 新疆 830046, 中国
推荐引用方式 GB/T 7714	买买提·沙吾提,塔西甫拉提·特依拜,丁建丽,等. BP神经网络的沙漠化土地信息提取研究[J]. 新疆大学,2008,25(5):647-652.
APA	买买提·沙吾提,塔西甫拉提·特依拜,丁建丽,&何祺胜.(2008).BP神经网络的沙漠化土地信息提取研究.,25(5),647-652.
MLA	买买提·沙吾提,et al."BP神经网络的沙漠化土地信息提取研究".25.5(2008):647-652.