Remote Sensing Image Extraction and Precision Analysis for Alpine Wetland Based on Coupling Analysis of Multispectral Factor PCA and Decision Tree

2009 ◽  
Author(s):  
Wenlong Li ◽  
Tiangang Liang ◽  
Xun Wang
Keyword(s):  
Remote Sensing ◽  
Decision Tree ◽  
Remote Sensing Image ◽  
Coupling Analysis ◽  
Precision Analysis ◽  
Alpine Wetland

Commonly Used Correction Model Comparison, Improvement and Precision Analysis of Radiation Remote Sensing Image

2014 ◽  
Vol 998-999 ◽  
pp. 1013-1017
Author(s):  
Xiao Li Liu
Keyword(s):  
Remote Sensing ◽  
Model Comparison ◽  
Remote Sensing Data ◽  
Remote Sensing Image ◽  
Surface Radiation ◽  
Precision Analysis ◽  
Mountain Area ◽  
Correction Model ◽  
Radiation Correction ◽  
Quantitative Remote Sensing

Remote sensing image radiation correction is a key technique for quantitative remote sensing data processing is essential, especially in the surface undulating mountains, surface radiation affected by topography, the radiation correction of remote sensing inversion error can reduce the surface information, so as to maximize the accuracy of remote sensing investigation of mountain area. In this paper, the ETM image in mountain area of Western Beijing as an example, application of cosine correction model and Sandmeier correction model of image are topographic radiation correction, and then proposed an improved Sandmeier correction model, and carries on the precision analysis from the visual effect and quantitative parameters. Experiments show that, the improved Sandmeier correction model eliminates the influence of topography, greatly improving the accuracy of remote sensing image Topographic Radiation correction.

Remote Sense Image Classification Based on CART Algorithm

2013 ◽  
Vol 864-867 ◽  
pp. 2782-2786
Author(s):  
Bao Hua Yang ◽  
Shuang Li
Keyword(s):  
Remote Sensing ◽  
Decision Tree ◽  
Regression Tree ◽  
Remote Sensing Image ◽  
Classification And Regression Tree ◽  
Classification Method ◽  
Remote Sense ◽  
Data Source ◽  
Cart Algorithm ◽  
Tree Method

This papers deals with the study of the algorithm of classification method based on decision tree for remote sensing image. The experimental area is located in the Xiangyang district, the data source for the 2010 satellite images of SPOT and TM fusion. Moreover, classification method based on decision tree is optimized with the help of the module of RuleGen and applied in regional remote sensing image of interest. The precision of Maximum likelihood ratio is 95.15 percent, and 94.82 percent for CRAT. Experimental results show that the classification method based on classification and regression tree method is as well as the traditional one.

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