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结合 Sentinel-1B 和 Landsat8 数据的针叶林叶片含水量反演研究.

Authors :
王长青
邢艳秋
汪献义
邢万里
张蓉鑫
Source :
Forest Engineering. Jul2018, Vol. 34 Issue 4, p28-69. 10p.
Publication Year :
2018

Abstract

In order to study the feasibility of inverting leaf water content from SAR images combined with optical images, the paper takes the moon lake national forest park in Changchun City, Jilin Province as the study area, and uses Sentinel-1B and Landsat 8 OLI remote sensing images and the leaf water content obtained through field investigation as the data source. Through the correlation analysis, the band combinations and vegetation indices with large correlation with the leaf water content are selected and the principal components are extracted. The linear, quadratic polynomial, cubic polynomial and exponential models between the principal components and the leaf water content are established. Finally, the paper uses the model with the highest precision to reverse the leaf water content of the moon lake national forest park. The results show that: Sentinel-1B VV polarization, VH / VV polarization ratio and OLI sensor short wave infrared 1 band, short wave infrared 2 band, the normalized difference water index (NDWI), the ratio vegetation index (RVI) have large correlation with leaf water content. The principal components extracted from the combination of Sentinel-1B and Landsat8 OLI data are more correlated with leaf water content than Landsat8 OLI data alone. The cubic polynomial model in the inversion model established using the extracted principal components and leaf water content has the highest fitting accuracy (R2=0.6299, RMSE=0.0358). It shows that Sentinel-1B combined with Landsat8 OLI data can better reverse the leaf water content of coniferous forest. [ABSTRACT FROM AUTHOR]

Details

Language :
Chinese
ISSN :
10068023
Volume :
34
Issue :
4
Database :
Academic Search Index
Journal :
Forest Engineering
Publication Type :
Academic Journal
Accession number :
133040771