Please wait a minute...
img img
高级检索
地球科学进展  2009, Vol. 24 Issue (7): 741-747    DOI: 10.11867/j.issn.1001-8166.2009.07.0741
遥感反演与估算     
植被FAPAR的遥感模型与反演研究
陶欣1,范闻捷1*,王大成2,闫彬彦1,徐希孺1
1.北京大学遥感与地理信息系统研究所,北京  100871;
2.浙江大学农业遥感与信息工程研究所,浙江  杭州  310029
Remote Sensing Retrieval of FAPAR: Model and Analysis
Tao Xin1,Fan Wenjie1,Wang Dacheng2,Yan Binyan1,Xu Xiru1
1. Institute of Remote Sensing and GIS, Peking University, Beijing  100871, China;
2. Institute of Agricultural Remote Sensing and Information Technology Application, Zhejiang University, Hangzhou  310029, China
 全文: PDF(8959 KB)  
摘要:

FAPAR是遥感估算陆地生态系统植被净第一性生产力(NPP)的重要参数。FAPAR模型是否能真实反映植被冠层吸收光合有效辐射状况,将直接影响遥感估算植被NPP和碳循环的准确性。从FAPAR机理出发,考虑土壤反射率、冠层结构、太阳入射角等多种因素,构建了全新的定量FAPAR反演模型,并分析了太阳天顶角、LAI、土壤背景等因素与FAPAR的关系。与蒙特卡罗模拟结果的对比和用地面实测数据的验证表明该模型拥有较高的精度。选择甘肃张掖盈科灌区为研究区,利用PROBA-CHRIS高光谱多角度数据反演得到了LAI和FAPAR,并用同步观测数据验证了反演结果。
 

关键词: FAPAR定量模型遥感反演    
Abstract:

FAPAR (Fraction of Absorbed Photosynthetically Active Radiation) is an important parameter for remote sensing monitoring plants net primary productivity (NPP) of land ecosystem. It is crucial that the calculated value approximates the actual value of canopy absorbed photosynthetically active radiation. The calculation accuracy directly influences the estimation of NPP and carbon cycle. The model in this paper is derived by analyzing the interaction processes between the photons and the canopy. It considers parameters like soil reflectance, canopy structure and solar zenith angle, etc. The relationship between these parameters and FAPAR is analyzed. The comparison results with Monte Carlo simulations and the validation results using field measurements prove the model to be accurate. We further choose Yingke, Zhangye City, Gansu province as study area, and retrieve LAI and FAPAR from hyperspectral and multi-angle PROBA-CHIRIS. Field data is also used to validate the retrieval result.



Key words: FAPAR    Quantitative model    Remote sensing retrieval
收稿日期: 2009-05-18 出版日期: 2009-07-10
:  TP79  
基金资助:

国家重点基础研究发展计划项目“地表时空变化特征参数的遥感定量描述与尺度转换”(编号:2007CB714402);国家自然基金项目“基于尺度纠正的作物插种面积和叶面积指数同步反演”(编号:40871186);中国科学院西部行动计划(二期)项目“黑河流域遥感—地面观测同步试验与综合模拟平台建设”(编号:KZCX2-XB2-09)资助.

通讯作者: 范闻捷(1972-),女,山西祁县人,副教授,主要从事定量遥感研究.     E-mail: fanwj @pku.edu.cn
作者简介: 陶欣(1985-),男,江西抚州人,硕士研究生,主要从事定量遥感模型与反演研究. E-mail:taoxin@pku.edu.cn
服务  
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章  
范闻捷

引用本文:

陶欣,范闻捷,王大成,闫彬彦,徐希孺. 植被FAPAR的遥感模型与反演研究[J]. 地球科学进展, 2009, 24(7): 741-747.

Tao Xin,Fan Wenjie,Wang Dacheng,Yan Binyan,Xu Xiru. Remote Sensing Retrieval of FAPAR: Model and Analysis. Advances in Earth Science, 2009, 24(7): 741-747.

链接本文:

http://www.adearth.ac.cn/CN/10.11867/j.issn.1001-8166.2009.07.0741        http://www.adearth.ac.cn/CN/Y2009/V24/I7/741

[1] Gao Yanhua, Chen Liangfu, Liu Qinhuo, et al. Research on remote sensing model for FPAR absorbed by chlorophyll[J].Journal of Remote Sensing,2006, 10(5):798-803.[高彦华,陈良福,柳钦火,等.叶绿素吸收的光合有效辐射比率的遥感估算模型研究[J]. 遥感学报, 2006, 10(5): 798-803.]
[2] Fensholt R,Sandholt I, Rasmussen M S. Evaluation of MODIS LAI, fAPAR and the relation between fAPAR and NDVI in a semi-arid environment using in situ measurements[J].Remote Sensing of Environment, 2004, 91: 490-507.
[3] Wu Bingfang,Zeng Yuan, Huang Jinliang. Overview of  LAI/FPAR retrieval from remotely sensed data[J]. Advances in Earth Science,2004,19(4): 585-590.[吴炳方,曾源,黄进良.遥感提取植物生理参数LAI/ FPAR 的研究进展与应用[J]. 地球科学进展,2004,19(4):585-590.]
[4] Knyazikhin Y, Martonchik J V, Myneni R B,et al.Synergistic algorithm for estimating vegetation canopy leaf area index and fraction of absorbed photosynthetically active radiation from MODIS and MISR data[J].Journal of Geophysical Research,1998,103(24):32 257-32 276.
[5] Myneni R B, Nemani R R, Running S W. Estimation of global leaf area index and absorbed par using radiative transfer models[J].IEEE Transactions on Geoscience and Remote Sensing,1997,35(6):1 380-1 393.
[6] Myneni R B, Williams D L. On the relationship between FAPAR and NDVI[J].Remote Sensing of Environment, 1994,49:200-211.
[7] Goward S N, Huemmrich K F. Vegetation canopy PAR absorptance and the normalized difference vegetation index: An assessment using the SAIL model[J].Remote Sensing of Environment,1992,39:119-140.
[8] Sellers P J. Canopy reflectance, photosynthesis, and transpiration[J].International Journal of Remote Sensing, 1985, 6: 1 335-1 372.
[9] Asrar G, Fuchs M, Kanemasu E T, et al. Estimating absorbed photosynthetic radiation and leaf area index from spectral reflectance in wheat[J].Agronomy Journal,1984,76:300-306.
[10] Dawson T P,North P R J, Plummer S E, et al. Forest ecosystem chlorophyll content: Implications for remotely sensed estimates of net primary productivity[J].International Journal of Remote Sensing,2003,24(3):611-617.
[11] Wiegand C T, Maas S J, Aase J K, et al. Multisite analyses of spectral-biophysical data for wheat[J].Remote Sensing of Environment,1992,42:1-21.
[12] Casanova D, Epema G F, Goudriaan J. Monitoring rice reflectance at field level for estimating biomass and LAI[J].Field Crops Research,1998,55:83-92.
[13] Xu Xiru, Fan Wenjie, Tao Xin. The spatial scaling effect of continuous canopy leaves area index retrieved by remote sensing[J].Science in China(Series D),2009,39(1):79-87.[徐希孺,范闻捷,陶欣.遥感反演连续植被叶面积指数的空间尺度效应[J].中国科学:D辑,2009,39(1):79-87.]
[14] Jin Huiran, Tao Xin, Fan Wenjie, et al. Monitoring the spatial distribution of high-resolution leaf area index using DMC+4 image[J].Progress in Natural Science,2007, 17:1 229-1 234.[金慧然,陶欣,范闻捷,等.应用北京一号卫星数据监测高分辨率叶面积指数的空间分布[J].自然科学进展,2007,17:1 229-1 234.]
[15] Zhou Bin, Chen Liangfu, Shu Xiaobo. The Monte Carlo study on FPAR[J].Journal of Remote Sensing,2008, 12(3): 385-391.[周彬,陈良富,舒晓波.FPAR的Monte Carlo模拟研究[J]. 遥感学报,2008,12(3):385-391.]
[16] Huang Jianxi, Wu Bingfang, Zeng Yuan,et al.Forest canopy BRDF simulation using Monte Carlo method [J]. Journal of System Simulation,2006, 18(6): 1 671-1 676.[黄健熙,吴炳方,曾源,等. 基于蒙特卡罗方法的森林冠层BRDF模拟[J]. 系统仿真学报,2006,18(6): 1 671-1 676.]
[17] Chen Liangfu, Xu Xiru. The simulation using monte Carlo method in vegetation canopy remote sensing[J].Progress in Geography,2000, 19(1): 25-34.[陈良富,徐希孺. 植被遥感的Monte Carlo模拟研究[J]. 地理科学进展,2000,19(1): 25-34.]

[1] 贾立,M.Menenti. 利用MODIS fAPAR傅立叶时间序列分析研究植被光合作用活动对净辐射和降雨的响应:青藏高原个例研究[J]. 地球科学进展, 2006, 21(12): 1254-1259.
[2] 唐翔宇,杨浩,李仁英,赵其国. 7Be在土壤侵蚀示踪中的应用研究进展[J]. 地球科学进展, 2001, 16(4): 520-525.
[3] 唐翔宇,杨 浩,赵其国,李仁英,朱振华,濮励杰. 137Cs示踪技术在土壤侵蚀估算中的应用研究进展[J]. 地球科学进展, 2000, 15(5): 576-582.
[4] 赵振华. 微量元素地球化学[J]. 地球科学进展, 1992, 7(5): 65-.