| Contents |
|
|
|
|
|
An analysis of influence of non-photosynthetic vegetation of deciduous broad-leaved forest on canopy FPAR: A method based on layered simulation |
| LIANG Shouzhen1, 2, 3, SUI Xueyan1, YAO Huimin1, WANG Meng1, HOU Xuehui1, CHEN Jinsong3, MA Wandong4 |
1. Shandong Institute of Agricultural Sustainable Development, Ji’nan 250100, China;
2. Key Laboratory of East China Urban Agriculture, Ministry of Agriculture, Ji’nan 250100, China;
3. Shenzhen Institutes of Advanced Technology, Shenzhen 518055,China;
4. Satellite Environment Center, Ministry of Environmental Protection, Beijing 100094, China |
|
|
|
|
Abstract Fraction of absorbed photosynthetically active radiation(FPAR) of the canopy is an important biophysical variable widely used in satellite-based production efficiency models to estimate the gross primary productivity(GPP). Vegetation canopy is composed primarily of photosynthetically active vegetation(PAV)and non-photosynthetic vegetation(NPV). Only the PAR absorbed by PAV is used for photosynthesis. Therefore, the photosynthetically active radiation absorbed by NPV in the canopy should be estimated and removed from canopy PAR so as to estimate GPP more accurately. Scattering by arbitrary inclined leaves(SAIL)model assumes canopy as a turbid medium with a number of layers, each treated as an infinite, horizontal, homogeneous medium. This assumption and configuration of model makes it possible to calculate PAR absorbed of each layers. In this study, SAIL model was used to calculate spectral reflectance and the PAR absorbed by PAV and NPV of deciduous broadleaved forest, and at last FPAR of NPV (FPARNPV) was calculated and analyzed. The results show that FPARNPV is dominated by canopy architecture. The contribution of NPV to canopy FPAR is low in high-cover regions, and the result is opposite in low-cover regions. NPV in the canopy can reduce reflectance in near infrared band. A significant and negative correlation is found between enhanced vegetation index(EVI)and FPARNPV. Though the simulation condition is ideal, the study is a good attempt which provides a means for acquiring deciduous broadleaf forests FPARNPV.
|
| Keywords
urban heat island(UHI)
urban rain island(URI)
tropical rainfall measuring mission(TRMM)
moderate resolution imaging spectroradiometer(MODIS)
land surface temperature(LST)
|
|
Issue Date: 03 May 2017
|
|
|
[1] Cramer W,Kicklighter D W,Bondeau A,et al.Comparing global models of terrestrial net primary productivity(NPP):Overview and key results[J].Global Change Biology,1999,5(S1):1-15.
[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(3/4):490-507.
[3] Olofsson P,Eklundh L.Estimation of absorbed PAR across Scandinavia from satellite measurements.Part II:Modeling and evaluating the fractional absorption[J].Remote Sensing of Environment,2007,110(2):240-251.
[4] 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.
Wu B F,Zeng Y,Huang J L.Overview of LAI/PAR retrieval from remotely sensed data[J].Advance in Earth Sciences,2004,19(4):585-590.
[5] Schottker B,Phinn S,Schmidt M.How does the global Moderate Resolution Imaging Spectroradiometer(MODIS) Fraction of Photosynthetically Active Radiation(FPAR) product relate to regionally developed land cover and vegetation products in a semi-arid Australian savanna[J].Journal of Applied Remote Sensing,2010,4(1):043538.
[6] Xiao X M,Hollinger D,Aber J,et al.Satellite-based modeling of gross primary production in an evergreen needleleaf forest[J].Remote Sensing of Environment,2004,89(4):519-534.
[7] Zhang Q Y,Xiao X M,Braswell B,et al.Estimating light absorption by chlorophyll,leaf and canopy in a deciduous broadleaf forest using MODIS data and a radiative transfer model[J].Remote Sensing of Environment,2005,99(3):357-371.
[8] 王文杰,祖元刚,王慧梅.林木非同化器官树枝(干)光合功能研究进展[J].生态学报,2007,27(4):1583-1595.
Wang W J,Zu Y G,Wang H M.Review on the photosynthetic function of non-photosynthetic woody organs of stem and branches[J].Acta Ecologica Sinica,2007,27(4):1583-1595.
[9] Le Roux X,Gauthier H,Bégué A,et al.Radiation absorption and use by humid savanna grassland:Assessment using remote sensing and modelling[J].Agricultural and Forest Meteorology,1997,85(1/2):117-132.
[10] Asner G P,Wessman C A,Archer S.Scale dependence of absorption of photosynthetically active radiation in terrestrial ecosystems[J].Ecological Applications,1998,8(4):1003-1021.
[11] 高彦华,陈良富,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.
Gao Y H,Chen L F,Liu Q H,et al.Research on remote sensing model for FPAR absorbed by chlorophyll[J].Journal of Remote Sensing,2006,10(5):798-803.
[12] 李 刚.呼伦贝尔温带草地FPAR/LAI遥感估算方法研究[D].北京:中国农业科学院,2009.
LI G.Study on Remote Sensing Estimation Models for FPAR/LAI of Temperate Grassland in Hulunber[D].Beijing:Chinese Academy of Agricultural Sciences,2009.
[13] 赵英时.遥感应用分析原理与方法[M].北京:科学出版社,2003.
Zhao Y S.Principles and Methods of Remote Sensing Application[M].Beijing:Science Press,2003.
[14] Verhoef W.Light scattering by leaf layers with application to canopy reflectance modeling:The SAIL model[J].Remote Sensing of Environment,1984,16(2):125-141.
[15] Jacquemoud S,Verhoef W,Baret F,et al.PROSPECT+ SAIL models:A review of use for vegetation characterization[J].Remote Sensing of Environment,2009,113(s1):56-66.
[16] Huemmrich K F,Goward S N.Vegetation canopy PAR absorptance and NDVI:An assessment for ten tree species with the SAIL model[J].Remote Sensing of Environment,1997,61(2):254-269.
[17] Gobron N,Pinty B,Aussedat O,et al.Evaluation of fraction of absorbed photosynthetically active radiation products for different canopy radiation transfer regimes:Methodology and results using Joint Research Center products derived from SeaWiFS against ground-based estimations[J].Journal of Geophysical Research,2006,111(D13):13110.
[18] Widlowski J L,Pinty B,Lavergne T,et al.Using 1-D models to interpret the reflectance anisotropy of 3-D canopy targets:Issues and caveats[J].IEEE Transactions on Geoscience and Remote Sensing,2005,43(9):2008-2017.
[19] Bacour C,Baret F,Béal D,et al.Neural network estimation of LAI, f APAR , f Cover and LAI×Cab ,from top of canopy MERIS reflectance data:Principles and validation[J].Remote Sensing of Environment,2006,105(4):313-325.
[20] Weiss M,Baret F,Garrigues S,et al.LAI,fAPAR and fCover CYCLOPES global products derived from VEGETATION.Part 2:Validation and comparison with MODIS Collection 4 products[J].Remote Sensing of Environment,2007,110(3):317-331.
[21] 肖艳芳,周德民,赵文吉.辐射传输模型多尺度反演植被理化参数研究进展[J].生态学报,2013,33(11):3291-3297.
Xiao Y F,Zhou D M,Zhao W J.Review of inversing biophysical and biochemical vegetation parameters in various spatial scales using radiative transfer models[J].Acta Ecologica Sinica,2013,33(11):3291-3297.
[22] Laurent V C E,Verhoef W,Clevers J G P W,et al.Inversion of a coupled canopy-atmosphere model using multi-angular top-of-atmosphere radiance data:A forest case study[J].Remote Sensing of Environment,2011,115(10):2603-2612.
[23] Li W J,Fang H L.Estimation of direct,diffuse,and total FPARs from Landsat surface reflectance data and ground-based estimates over six FLUXNET sites[J].Journal of Geophysical Research,2015,120(1):96-112.
[24] Steinberg D C,Goetz S J,Hyer E J.Validation of MODIS FPAR products in boreal forests of Alaska[J].IEEE Transactions on Geoscience and Remote Sensing,2006,44(7):1818-1828.
[25] Friedl M A,Davis F W,Michaelsen J,et al.Scaling and uncertainty in the relationship between the NDVI and land surface biophysical variables:An analysis using a scene simulation model and data from FIFE[J].Remote Sensing of Environment,1995,54(3):233-246.
[26] Myneni R B,Williams D L.On the relationship between FAPAR and NDVI[J].Remote Sensing of Environment,1994,49(3):200-211.
[27] 陈雪洋,蒙继华,吴炳方,等.基于HJ-1CCD的夏玉米FPAR遥感监测模型[J].农业工程学报,2010,26(s1):241-245.
Chen X Y,Meng J H,Wu B F,et al.Monitoring corn FPAR based on HJ-1 CCD[J].Transactions of the CSAE,2010,26(s1):241-245.
[28] King D A,Turner D P,Ritts W D.Parameterization of a diagnostic carbon cycle model for continental scale application[J].Remote Sensing of Environment,2011,115(7):1653-1664.
[29] Nakaji T,Ide R,Oguma H,et al.Utility of spectral vegetation index for estimation of gross CO 2 flux under varied sky conditions[J].Remote Sensing of Environment,2007,109(3):274-284.
[30] Xiao X M.Light absorption by leaf chlorophyll and maximum light use efficiency[J].IEEE Transactions on Geoscience and Remote Sensing,2006,44(7):1933-1935.
[31] Roujean J L,Breon F M.Estimating PAR absorbed by vegetation from bidirectional reflectance measurements[J].Remote Sensing of Environment,1995,51(3):375-384.
[32] Gitelson A A,Kaufman Y J,Merzlyak M N.Use of a green channel in remote sensing of global vegetation from EOS-MODIS[J].Remote Sensing of Environment,1996,58(3):289-298.
[33] Huete A R,Liu H Q,Batchily K,et al.A comparison of vegetation indices over a global set of TM images for EOS-MODIS[J].Remote Sensing of Environment,1997,59(3):440-451.
[34] Running S W,Thornton P E,Nemani R,et al.Global terrestrial gross and net primary productivity from the earth observing system[M]//Sala O E,Jackson R B,Mooney H A,et al.Methods in Ecosystem Science.New York:Springer-Verlag,2000:44-57.
[35] 黄 玫,季劲钧.中国区域植被叶面积指数时空分布——机理模型模拟与遥感反演比较[J].生态学报,2010,30(11):3057-3064.
Huang M,Ji J J.The spatial-temporal distribution of leaf area index in China:A comparison between ecosystem modeling and remote sensing reversion[J].Acta Ecologica Sinica,2010,30(11):3057-3064. |
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
| |
Shared |
|
|
|
|
| |
Discussed |
|
|
|
|
2017,
Vol. 29
