Paper Info
Title
Using Path Analysis To Study Correlation And Causation In Remote Sensing Inversion
Abstract
One problem in quantitative remote sensing inversion is the correlations between variables. Path analysis is a statistical technique that differentiates between correlation and causation, features multiple linear regressions, and generates path coefficients. In this paper, path analysis was applied to study the correlations and causations of two cases in remote sensing reversion. One is the retrieval of land surface temperature, and another is to explain the results of land surface moisture estimation. We found that path analysis can be used to study the direct effect and the indirect effects of a variable in remote sensing inversion, and gave a better explanation of the results of multiple linear regression analysis.
Year
DOI
Venue
2003
10.1109/IGARSS.2003.1295295
IGARSS 2003: IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS I - VII, PROCEEDINGS: LEARNING FROM EARTH'S SHAPES AND SIZES
Keywords
DocType
Volume
information retrieval,remote sensing,inverse problems,linear regression,moisture,geography,regression analysis,path analysis,parameter estimation,multiple linear regression
Conference
6
Issue
ISSN
Citations 
null
null
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Pengxin Wang142.67
Xiaowen Li2372112.54
Jindi Wang317353.39