利用遥感技术实现作物模拟模型区域应用的研究进展

摘要/Abstract

摘要： 作物模拟模型从单点发展到区域应用时,模型中一些宏观资料的获取和参数的区域化方面出现困难,利用遥感技术将实现作物模拟模型的区域应用.文中综述了近年来遥感反演作物模型所需的地表生物物理参数的方法、利用遥感信息直接获取生物量的途径和遥感信息与作物模拟模型之间时空匹配问题等方面的研究概况,重点介绍了利用遥感技术实现作物模拟模型区域应用的3种解决方案(强迫型、调控型和验证型)及其研究进展,并讨论了目前存在的问题和今后研究的方向.

关键词: 作物模拟模型, 区域尺度应用, 遥感技术

Abstract: When applying crop simulation model developed from plot-scale level to regional scale,some challenges such as acquirement of some broader spatial data and regionalization of parameters will arise,while satellite can monitor crop growth status by remote sensing.Therefore,regional application of crop simulation model will be implement by remote sensing technique.In this paper,some research advances are reviewed,which include the methods of biophysical parameters retrieved from remote sensing data for crop model,the approach of biomass obtained by remote sensing data directly,and the means of matching temporal and spatial resolution between remote sensing data and crop model input.Three solutions (forcing,recalibration and validation) to the application of crop model in region scale by using remote sensing technique were emphasized,and the current problem and future research orientation in this filed were discussed in brief.

Key words: Crop simulation model, Application in regional scale, Remote sensing technique

中图分类号:

TP79

马玉平, 王石立. 利用遥感技术实现作物模拟模型区域应用的研究进展[J]. 应用生态学报, 2004, (9): 1655-1661.

MA Yuping, WANG Shili. A review on research of implement application for crop simulation model in regional scale by using remote sensing technology[J]. Chinese Journal of Applied Ecology, 2004, (9): 1655-1661.

参考文献

[1] Abuelgasim AA, Gopal S, Strahler AH. 1998. Forward and inverse modeling of canopy directional reflectance using a neural network.Int J Remote Sens, 19(3) :453～471
[2] Baret F, Guyot G. 1991. Potentials and limits of vegetation indices for LAI and APAR assessment. Remote Sens Environ, 35:161 ～173
[3] Boken VK, Shaykewich CF. 2002. Improving an operational wheat yield model using phenological phase-based Normalized Difference Vegetation Index. Int J Remote Sens, 23:4155～4168
[4] Bouman BAM, van Keulen H, van Laar HH, et al. 1996. The School-ofde-Wit crop growth simulation models: A pedigree and historical overview. Agric Syst, 52(2～3): 171 ～ 198
[5] Bouman BAM. 1991. The linking of crop growth models and multisensor remote sensing data. 5th Int. Colloq. on Physical Measurements and Signature in Remote Sensing. January 14 ～ 18,Courchevel, France. Esa SP-319: 583～ 588
[6] Clevers JGPW, van Leeuwen HJC. 1996. Combined use if optical and microwave remote sensing data for crop growth monitoring.Remot Sens Environ, 56: 42～ 51
[7] de Wit CT. 1965. Photosynthesis of leaf canopies. Agricultural research report 663. PUDOC, Wageningen, The Netherlands. 57P
[8] Delecolle R, Guerif M. 1988. Introducing spectral data into a plant process model for improving its prediction ability. Proc. 4th Int.Colloq. on Spectral Signatures of Objects in Remote Sensing. January 18～22, Aussois, France. Esa SP-287:125～ 127
[9] Doraiswamy PC, Hollinger S, Sinclair TR, et al. 2001. application of MODIS derived parameters for regional yield assessment. Proc.Remote Sensing for Agriculture, Ecosystems, and Hydrolory Ⅲ, 17～ 21 September 2001. Toulouse, France.
[10] Doraiswamy PC, Moulin S, Paul WC, et al. 2003. Crop yield assessment from remote sensing. Photogr Engin Remote Sens, 69: 665 ～674
[11] Duncan WG, Loomis RS, Williams WA, et al. 1967. A model for simulating photosynthesis in plant communities. Hilgardia, 38:181～ 205
[12] Faivre R, Fischer A. 1997. Predicting crop reflectance using satellite data observing mixed pixels. J Agric Biol Environ Statist, 2:1 ～ 21
[13] Feng L-P(冯利平),Gao L-Z(高亮之),Jin Z-Q(金之庆).1997.Studies on the simulation model for wheat phenology. Acta AgronSin(作物学报),23(4):418～424(in Chinese)
[14] Fischer A, Kergoat L, Dedieu G. 1997. Coupling satellite data with vegetation functional models: Review of different approaches and perspectives suggested by the assimilation strategy. Remot Sens Rev, 15: 283～ 303
[15] Fischer A. 1994. A model for the seasonal variation of vegetation indices in coarse resolution data and its inversion to extract crop parameter. Remot Sens Environ, 48: 220～ 230
[16] Gao F(高峰).1997.Inversion of Vegetation Canopies Using Multiangular Remote Sensing. Ph. D. Dissertation. Beijing: Beijing Normal University. (in Chinese)
[17] Gao L-Z(高亮之),Jin Z-Q(金之庆),Huang Y(黄耀),et al.1989. Rice clock model-A computer simulation model of rice development.Chin J Agrometeorol(中国农业气象),10(3):3～10(in Chinese)
[18] Gao L-Z(高亮之),Jin Z-Q(金之庆),Zheng G-Q(郑国清),et al.2000. Wheat cultivational simulation-optimization-decision making system(WCSODS).Jiangsu J Agron Sci(江苏农业学报),16(2):65 ～ 72 (in Chinese)
[19] Gao X(高翔),Wang F-T(王馥棠).1995.Research on the simulation model of double-harvest rice growth.In: Wang F-T(王馥棠)ed.Research on the Possible Effects of Climate Change on Agriculture in China. Beijing: Meteorology Press. 1～ 8(in Chinese)
[20] Gilabert MA, Gandia S, Mekia J. 1996. Analysis of spectral-biophysical relationships for a corn canopy. Remote Sens Environ, 55:50 ～ 58
[21] Guerif M, Duke CL. 2000. Adjustment procedure of a crop model to the site specific characteristics of soil and crop using remote sensing data assimilation. Agric Ecosyst Environ, 81: 57～69
[22] Guerif M, Duke C. 1998. Calibration of the SUCROS emergence and early growth module for sugarbeet using optical remote sensing data assimilation. Eur J Agron, 9:127～ 136
[23] Guriff M, DE Brisis S, Seguin B. 1993. Combined NOAA-AVHRR and SPOT-HRV data for assessing crop yields of semiarid environment. EARSeL Adv Remot Sens, 2:110～ 123
[24] Hatfield JK. 1983. Remote sensing estimators of potential and actual crop yield. Remot Sens Environ, 13: 301 ～ 311
[25] Hayes MJ, Decker WL. 1996. Using NOAA AVHRR data to estimate maize production in the US corn belt. Int J Remote Sens, 17:3189 ～ 3200
[26] Hoogenboom G, Wilkens PW, Tsuji GY, eds. 1999. DSSAT v3.Vol. 4. Honolulu, Hawaii: University of Hawaii. 286pp
[27] Karvonen T, Laurila H, Kleemola J. 1991. Estimation of agricultural crop production using satellite information. Helsinki, Fenland: University of Helsinki. 73P.
[28] Kerdiles H, Grondona MO. 1995. NOAA-AVHRR NDVI decomposition and subpixel classification using liner missing in the Argentina Pampa. Int J Remot Sens, 16:1303～ 1325
[29] Kimes DS, Harrison PR, Ratcliffe PA. 1991. A knowledge-based espert system for inferring vegetation characteristics. Int J Remot Sens, 12(10) :1987～2020
[30] Kropff MJ, van Laar HH, Matthews R. 1994. ORAZA1, An Ecophysiological Model for Irrigation Rice Production. SARP Research Proceedings. DLO Research Institute for Agrobiology and Soil Fertility. Wageningen, the Netherlands. 110pp.
[31] Labus MP, Nielsen GA, Lawrence RL. 2002. Wheat yield estimates using multi-temporal NDVI satellite imagery. Int J Remot Sens,23:4169～4180
[32] Launay M, Guerif M. 2001. Remote sensing data assimilation in a sugar beet growth model sa a tool for spatial crop development variability forecast and diagnosis. 8th International Symposium "Physical Measurements and Signatures in Remote Sensing ". Aussois (France).
[33] Leblon B, Guerif M, Baret F. 1991. The use of remotely sensed data in estimation of PRA use efficiency and biomass production of flooded rice. Remot Sens Environ, 38:147～ 158
[34] Li X-W(李小文),Wang J-D(王锦地),Hu B-X(胡宝新),et al.1998. The use of prior knowledge in remote sensing inversion. Sci China(Series D)(中国科学·D辑),28(1):67～72(in Chines)
[35] Li X-W(李小文),Yan G-J(阎广建),Liu Y(刘毅),et al.1997. Uncertainty and sensitivity matrix of parameters in inversion of physical BRDF models.Chin J Remot Sens(遥感学报),1(supp.):113～122(in Chinese)
[36] Liu B-C(刘布春),Wang S-L(王石立),Ma Y-P(马玉平).2002.Research advances of regional application of crop simulation model out china.Meteorol Scu Tech(气象科技),30(4):193～203(in Chinese)
[37] LiuY-J(刘玉洁),Yang Z-D(杨忠东),eds.2001.Principium and Algorithm of Remote Sensing Information Process in MODIS. Beijing: Science Press. 232～260(in Chinese)
[38] Loudjani P, Delecolle R, Guerif M, et al. 1995. Combined use of NOAA-AVHRR and SPOT-HRV data for the estimation of European crop yields on a regional scale. International Colloquium Photosynthesis and Remote Sensing. Montpellier, France. 28 ～ 30 August 1995. EARSeL-ISPRS(Strasbourg: EARSeL).
[39] Manjunath KR, Potdar MB, Purohit NL. 2002. Large area operational wheat yield model development and validation based on spectral and meteorological data. Int J Remot Sens, 23: 3023～ 3038
[40] Mass SJ. 1988. Using satellite data to improve model estimates of crop yield. Agron J, 80: 655 ～ 662
[41] Monteith JL. 1977. Climate and the efficiency of crop production in Britain. Philosoph Trans Royal Soci London, B281: 277～ 294
[42] Moulin S, Bondesu A, Delecolle R. 1998. Combining agricultural crop models and satellite observations:From field to regional scales. Int J Remote Sens, 19(6): 1021～ 1036
[43] Moulin S, Fischer A, Dedieu G, et al. 1995. Temporal variations in satellite reflectances at field and regional scales compared with values simulated by linking crop growth ad SAIL models. Remot Sens Environ, 54: 261 ～ 272
[44] Moulin S, Launay M, Guerif M. 2001. The crop growth monitoring at a regional scale based on the combination of remote sensing and process-based models. International Symposium "Crop monitoring and Prediction at Regional Scales". February. Tsukuba(Japan).
[45] Ouaidrari H, Begue A, Imbernon J, et al. 1996. Extraction of the pure spectral response of the landscape components in NOAA/AVHRR mixed pixels: Application to the HAPEX-Sahel degree square. Int J Remot Sens, 17:2259～2280
[46] Pan X-B(潘学标),Han X-L(韩湘玲),Shi Y-C(石元春),et al.1996. COTDROW: Cotton growth and development simulation model.Acta Gossypii Sin(棉花学报),8(4):180～188(in Chinese)
[47] Penninning de Vries FWT,eds.1988.Trans.Wang F-T(王馥棠),et al. 1988. Simulation of Plant Growth and Crop Production. Beijing: Science Press. 10 ～ 45 (in Chinese)
[48] Penninning de Vries FWT, Jansen DM, ten Berge HFM, et al.1989. Simulation of ecophysiological processes of growth of several annual crops. Simulation Monographs. Wageningen: Centre for Agricultural Publishing and Documentation(Pudoc).
[49] Puyou-Lascassies PH, Flouzat G, Gay M, etal. 1994. Validation if the use of multiple liner regression as a tool for unmixing coarse spatial resolution image. Remot Sens Environ, 49:155～ 166
[50] Qiu G-W(裘国旺),Wang F-T(王馥棠).1998.Numerical simulation study on the potential impact of climate change on double cropping of rice in the south of Yangtze river valley of china. J Appl Meteorol Sci(应用气象学报),9(2):151～159(in Chinese)
[51] Rahman H. 2001. Influence of atmospheric correction on the sstimation of biophysical parameters of crop canopy using satellite remote sensing. Int J Remot Sens, 22:1245～ 1268
[52] Rastogi A, Kalra N, Agarwal PK, et al. 2000. Estimation of wheat leaf area index From IRS LISS-Ⅲ data using Price model. Int J Remot Sens, 21 :2943～2949
[53] Schluesel G, Dickinson RE, Privette JL, et al. 1994. Modelling the bidirectional reflectance distribution function of mixed finite plant canopies and soil. J Geophy Res, 99:10577 ～ 10600
[54] Seguin B, Lagouarde JP, Aavane M. 1991. The sasessment if regional crop water conditions from meteorological satellite thermal infrared data. Remot Sens Environ, 35:141 ～ 148
[55] Shang Z-B(尚宗波),Yang J-W(杨继武),Yin H(殷红).2000.A physiological-ecological simulation model of maize growth. Acta Bot Sin(植物学报),42(2):184～194(in Chinese)
[56] Shen S-Y(沈思渊).1990.Simulation and modelling of crop production.Chin J Appl Ecol(应用生态学报),1(3):270～276(in Chinese)
[57] Stem AJ, Doraiswamy PC, Cook PW. 2001. Spring wheat classification in an AVHRR image by signature extension from a landsat TM classified image. Potogr Engin Remot Sens, 67: 207 ～ 211
[58] Stinmentz S, Guerif M, Delecolle R, et al. 1990. Spectral estimates of the absorbed photosynthetically active radiation and light-use efficiency of a win ter wheat crop subjected to nitrogen and water deficiencies. Int J Remot Sens, 11:1797～ 1808
[59] Stol W, Rouse DI, van Kraalingen DWG. 1992. FSEOPT a FORTRAN program for calibration and uncertainty analysis of simulation models. Simulation Report CABO-TT, No. 24, CABO-DLO and Agricultural University, Wageningen. 24 pp.
[60] Strahler AH. 1997. Vegetation canopy reflectance modeling-Recent developments and remote sensing perspectives. Remot Sens Rev, 15:179～ 194
[61] Supit I, Hoojier CA, et al. 1994. System description of the WOFOST 6.0 crop simulation model implemented in CGMS. The Winand Starting Centre for Intergratsd Land. Soil and Water Research(SC-DLO). Wageningen, The Netherlands. 144p
[62] Tang S-H(唐世浩).2001.Studies on Inverse Theories and Methods of Terrestrial Parameters in Remote Sensing. Ph. D. Dissertation. Beijing: Beijing Normal University. (in Chinese)
[63] Tian Q-J(田庆久),Min X-J(闵祥军).1998.Advances in study on vegetation indices.Adv Earth Sci(地球科学进展),13(4):327～333(in Chinese)
[64] Tucker CJ, Holben BN, Elgin JH, et al. 1981. Remote sensing of total dry-matter accumulation in winter wheat. Remot Sens Environ, 11 : 179 ～ 189
[65] Tucker CJ, Vanpreat CL, Sharman MJ, et al. 1985. Satellite remote sensing of total herbaceous production in the Senegalese Sahel 1980～ 1984. Remot Sens Environ, 17: 232～ 249
[66] Verhoef W. 1984. Light scattering by leaf layers with application to canopy reflectance modeling: The SAIL model. Remot Sens Environ, 16:125 ～ 141
[67] Verhoef W. 1996. Application of Harmonic Analysis of NDVI Time Series(HANTS). In: Azzali S, Menenti M, eds. Fourier Analysis of Temporal NDVI in the southern African and American Continents.DLO Winand Staring Center, Wagenmgen, The Nether Lands. Report, 108:19～24
[68] Wang F-T(王馥棠),Wang S-L(王石立),Li Y-W(李友文),et al. 1990. On the evolution of yellowed leaves of spring wheat and its simulative model.J Appl Meteorol Sci(应用气象学报),1(3):305～ 311(in Chinese)
[69] Wang S-L(王石立),Wang F-T(王馥棠),Li Y-W(李友文),et al. 1991. A study on simplified simulation model of the spring wheat growth. J Appl Meteorol Sci(应用气象学报),2(3):293～299(in Chinese)
[70] Wen G(温刚).1999.Inversion of a bidirectional reflectance distribution function model of vegetation.Chin J Remot Sens(遥感学报),3(3):176～182(in Chinese)
[71] Xiao X, He L, Li C, et al. 2002. Quantitative relationships between field-measured leaf area index and vegetation index derived from vegetation images for paddy rice fields. Int J Remot Sens, 23: 3595～ 3604
[72] Yan G-J(阎广建),Wu J(吴均),Wang J-D(王锦地).2002.Spectral prior knowledge and its use in the rmote sensing based inversion of vegetation structure.Chin J Remot Sens(遥感学报),6(1): 1～ 6(in Chinese)
[73] Yang J-P(杨京平),Wang Z-Q(王兆骞).1999.Crop growth simulation model and its application.Chin J Appl Ecol(应用生态学报),10(4):501～505(in Chinese)
[74] Zhang J-H(张佳华),Fu C-B(符淙斌).2002.Study response of ecological system on east Asian monsoon by LAI from remote sensing inversion.Adv Nat Sci(自然科学进展),12(10):1098～1100( in Chinese)
[75] Zhang R-H(张仁华).1996.Remote Sensing Model Based Ground Experiment. Beijing: Science Press. 106 ～ 119(in Chinese)
[76] Zhang Y(张宇),Wang S-L(王石立),Wang F-T(王馥棠),et al. 2000. Research on the possible effects of climate change on growth and yield of wheat in China.J Appl Meteorol Sci(应用气象学报),11(3):264～270(in Chinese)