林业科学Issue(9)：24-34,11.DOI:10.11707/j.1001-7488.20150904
不同方法提取的快鸟影像信息估算刺槐林有效叶面积指数的精度比较
A Comparison of Different Quickbird Image Information for Estimating the Effective Leaf Area Index of Robinia pseudoacacia Plantations
摘要
Abstract
[Objective]The spatial information of high resolution remote sensing image can improve the estimation accuracy of forestry parameters. This study precisely explored the combinational rule of spectral and spatial information with high resolution remote sensing in order to improve the effective leaf area index ( LAIe) based on the existing research. Obtained results can be provide evidence and data for estimation of forestry parameters and assessments of forestry health.[Method]The black locust ( Robinia pseudoacacia) plantations located in Weibei area of Loess Plateau were chosen as research objects. The LAIe values of 76 plots were measured. We also extracted seven textural parameters of panchromatic data including ASM,HOM,COR,CON,DIS,VAR,ENT and seven spectral parameters of multi-spectral image including b4,SAVI,MSAVI,NLI,EVI,DVI,NDVI from Quickbird imagey with high resolution. The combined spectral-textural indices of Quickbird imagery were obtained using method of raster operation. Four different techniques, including simple linear regression model, quadratic regression model, power model and exponential model, were developed to describe the relationship between image parameters and field measurements of LAIe. The predicted accuracy of combined spectral-textural index and sole texture parameter was compared to reveal the role of combined spectral index and texture parameters used for LAIe retrieval. [Result]The LAIe estimation accuracy was improved when ASM,COR and HOM were combined with SVIs. To a certain extent,the accuracy of SVIs to estimate LAIe was improved with the combination of CON,DIS,VAR and SVIs. The combination of HOM,ASM and COR with SVIs gained the higher r2 than those achieved using HOM,ASM or COR alone. The performances of CON,DIS and VAR were improved when combining with partly SVIs. The combination of Entropy data with SVIs invariably yielded adjusted r2 values that were lower than those achieved using ENT alone. Quadratic regression model and exponential model exhibited higher r2 values than power model and simple linear regression model slightly.[Conclusion]The combination of spectral and special information can improve the accuracy of LAIe estimation effectively when the high-resolution image was used to invert LAIe of black locust plantations. However,not all combined spectral and textural information can obtained higher accuracy comparing to the solely textural information. The model types influenced the accuracy of LAIe estimation slightly. Our results showed that comprehensive use of spatial and spectral information and appropriate selection of model was beneficial to accurate estimation and inversion of forestry parameters.关键词
有效叶面积指数/光谱 -纹理/纹理/高分辨率影像/刺槐林Key words
effective leaf area index ( LAIe )/spectral-textural information/texture/high resolution imagery/black locust plantation分类
农业科技引用本文复制引用
周靖靖,赵忠,刘金良,赵君,赵青侠,刘俊..不同方法提取的快鸟影像信息估算刺槐林有效叶面积指数的精度比较[J].林业科学,2015,(9):24-34,11.基金项目
国家“十二五”农村领域国家科技支撑计划项目(2012BAD22B0302) （2012BAD22B0302）
森林培育学教学团队项目(Z105021003) （Z105021003）
中央高校科研业务费专项资金资助项目(2662015QC048)。 （2662015QC048）
