全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

玉米叶面积指数的CHRIS/PROBA数据反演分析

DOI: 10.3724/SP.J.1047.2015.01243, PP. 1243-1248

Keywords: 多角度,植被指数,高光谱数据,叶面积指数

Full-Text   Cite this paper   Add to My Lib

Abstract:

叶面积指数(LAI)是衡量植被生态状况和估算作物产量的一个重要指标。LAI的反演是定量遥感研究的重要内容。传统的经验统计反演方法基于单一观测角度的遥感数据进行,忽略了地物反射率的方向性。若在反演中加入多观测角度的信息,则有可能提升LAI反演的精度。以2008年甘肃省张掖市玉米实验区为研究区,利用欧空局的CHRIS/PROBA多角度高光谱数据对比分析了传统植被指数NDVI、RVI、EVI的变化规律及其反演玉米叶面积指数LAI的精度,并根据NDVI随观测角度的变化规律,构造出新型多角度归一化植被指数MNDVI,分别对实测叶面积指数进行线性回归并利用实测数据对估算LAI进行精度验证,结果表明新型MNDVI指数相比于传统NDVI、RVI、EVI对LAI的反演精度有了显著提升,估算模型决定系数R2达到0.716,精度验证均方根误差为0.127,平均减小了33.3%。

References

[1]  Stern W R, Donald C M. Relationship of radiation, leaf area index and crop growth-rate[J]. Nature, 1961,189(476):597.
[2]  Aber J D, Reich P B, Goulden M L. Extrapolating leaf CO 2 exchange to the canopy: A generalized model of forest photosynthesis compared with measurements by eddy correlation[J]. Oecologia, 1996,106:257-265.
[3]  Pocewicz A, Vierlizing L A, Lentile L B, et al . View angle effects on relationships between MISR vegetation indices and leaf area index in a recently burned ponderosa pine forest[J]. Remote Sensing of Environment, 2007,107:322-333.
[4]  方秀琴,张万昌.叶面积指数( LAI)的遥感定量方法综述[J].国土资源遥感,2003(57):58-62.
[5]  Chen J M, Cihlar J. Retrieving leaf area index of boreal conifer forests using landsat TM images[J]. Remote Sensing of Environment, 1996,55(2):153-162.
[6]  Haboudane D, Miller J R, Pattey E, et al . Hyper-spectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: Modeling and validation in the context of precision agriculture[J]. Remote Sensing of Environment, 2003,90(3):337-352.
[7]  Yang QY, Huang W J, Zhao J L, et al . Effect of canopy geometry on estimation of leaf area index in winter wheat using multi-angle spectrum[J]. International Journal of Agriculture and Biology, 2013,15(6):1187-1192.
[8]  ESA. CHRIS Mission[EB/OL].http://earth.esa.int/services/pg/pgproba-chris.xml.
[9]  Verelst J, Romijn E, Kooistra L. Mapping vegetation density in a heterogeneous river floodplain ecosystem using pointable CHRIS/PROBA data[J]. Remote Sensing, 2002,4(9):2866-2889.
[10]  Duan S B, Li Z L, Wu H, et al . Inversion of the PROSAIl model to estimate leaf area index of maize, potato, and sunflowers fields from unmanned aerial vehicle hyperspectral data[J]. International Journal of Applied Earth Observation and Geoinformation, 2014,26:12-20.
[11]  Cao J J, Gu Z J, Xu J H, et al .Sensitivity analysis for leaf area index(LAI) estimation from CHRIS/PROBA data[J]. Frontiers of Earth Science,2014,8(3):405-413.
[12]  Cernicharo J, Verger A, Camacho F. Empirical and physical estimation of canopy water content from CHRIS/PROBA data[J].Remote Sensing, 2013,5(10):5265-5284.
[13]  杨贵军,赵春江,邢著荣,等.基于PROBA/CHRIS遥感数据和PROSPECT模型的春小麦LAI反演[J].农业工程学报,2011,27(10):88-94.
[14]  李小文,王锦地,刘毅,等.不连续植被二向性反射的几何光学与辐射传输一体化综合模型初探[J].环境遥感,1993(3):161-172.
[15]  梁守真,施平,周迪.基于SAILH模型的植被冠层NDVI二向性分析[J].遥感信息,2011(1):22-26.
[16]  董广香,张继贤,刘正军.CHRIS/PROBA数据条带噪声去除方法比较[J].遥感信息,2006(6):36-39.
[17]  盖利亚,刘正军,张继贤. CHRIS/PROBA高光谱数据的预处理[J].测绘工程,2008(1):40-43.
[18]  王明常,王亚楠,陈圣波,等.多角度高光谱CHRIS/PROBA植被模式数据大气校正[J].吉林大学学报,2011(2):609-614.
[19]  Li XW, Gao F, Wang J D, et al . Bi-directional normalized difference vegetation index: Concept and application[J]. Progress of Natural Science, 2002,12(2):115-119.
[20]  李小文,闫广建,刘毅,等.BRDF物理模型反演中的不确定性与敏感性矩阵[J].遥感学报,1997,1(1):121-130.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133