森林地上生物量多模式遥感信息动态分析及建模框架

doi:10.13466/j.cnki.lyzygl.2015.02.022

摘要/Abstract

摘要： 森林控制着全球碳循环的动态,而森林地上生物量是固碳能力的重要标志,是评估森林碳收支的重要参数,是系统发挥其它生态功能的物质基础。基于任何单一的方法,如森林资源清查资料方法、遥感模型反演方法、通量观测法以及生态模型方法等均无法高效地刻画森林地上生物量及其动态变化信息。基于此,提出改进森林地上生物量估测精度的时空连续性的新思路和新方法,即基于已有的多模式遥感数据及产品、森林生态过程时空动态知识和各种地面连续观测数据提取的时空动态特征,采用同化算法进行遥感信息动态建模,生成高精度、时空连续、物理量一致的森林地上生物量及其动态变化产品。

关键词: 多模式遥感, 森林地上生物量, 动态分析及建模, 数据同化

Abstract: Forest dominates the global carbon cycle and forest above-ground biomas(ACB) has been the critica index for carbon seuestratio capaciy,the main parameler of cabhon budgel, he maleria basis for oher ecogical functions. However,any individual mehod such as fores-inventory -based mehod remooesensing-baned melhlod, lrobsovaron-baind method and clogicl-mooe mehod, canmon describ the forest AGB and its dynamic information eficienl.l In orler lo geneat uhe hih-prcision time-space-se-ries,physielcuanli sy nery forest AGB and is dynamic produces , this study proposes the new idea and methodology for improving the space-time series modeling forest AGB , that is , the framework of the remote sensing dynamic information model will be established by use of new -prototype and multi-mode remote sensing data and their products , by the knowledge of dynamic information of forest ecological process and the characteristics from various observation data ,and by data assimilation algorithm.

Key words: multi-mode remote sensing, forest above- ground biomass, dynamic analysis and modelling, data assimilation

中图分类号:

师君, 田昕, 闫敏. 森林地上生物量多模式遥感信息动态分析及建模框架[J]. 林业资源管理, 2015, 0(2): 125-132.

SHI Jun, TIANXin, YAN Min. Framework of dynamic analysis and modelling forest above-ground biomass by multi-mode remote sensing information[J]. FOREST RESOURCES WANAGEMENT, 2015, 0(2): 125-132.

参考文献 40

[1]	Melil JM, Premnice 1 C. Faquhar G D,e al. Trrertal bioice response to ewiomomnn chne and febake to dimetl M]//Clime Chmer1995 :The siene of Cimte dune. Cmbidge university pres,196 ,449-481.
[2]	李银鹏,季劲钧.全球陆地生态系统与大气之间碳交换的模拟研究[J].地理学报2001 ,56(4) :379-389.
[3]	Metsarana J M, Lidfer v J. Using dedochroo to obain annual data for modeing stand development: a supplement to permanent sample plous[J]. Foretry .2009 ,82(2):163-173.
[4]	Chiesi M, Maseli F, Moriondo M,et al.Application of BIOME BCC to simulale Mcitermnen farest procses[J] Ecological Modeling .2007 .206(1):179-190.
[5]	K]jun N, Black T A, Gris T J,et al. Response of net ecosystenm producivity of three boreal forst stands to drough[J]. Eosystems,2006 ,9(7):1128-1144.
[6]	王雪军,黄国胜,孙玉军,等.近20年辽宁省森林碳储量及其动态变化[J].生态学报2008 ,28(10) :4757-4764.
[7]	Fang Jinguyu, Chen Anping, Peng Changhui,et al.Changes in For est Biomass Carbon Storage in China Between 1949 and 1998[J]. Science. 2001 ,292(5525) :2320-2322.
[8]	王斌,刘某承,张彪.基于森林资源清查资料的森林植被净生产量及其动态变化研究[J].林业资源管理,2009(1):35-43.
[9]	Hansen M.Volume and biomass estimatio in FIA: national consisteney w. rgional acurey[C]//Pocedin of the third annual forest inventory and alylis symposum.20219-120.
[10]	Fehrmann L, Lehtonen A, Kleim C,et al.Comparison of Linear and Mixed-efiet Regresion Modelsnd a K - neares Neihbor Apprach for Extimation of Sinle - tree Bioas[J]. Can. J. Fr.Res.2008 .38(1):1-9.
[11]	Naver J.Alomeric Equations for Tree Speie and Cathon Slocks for Fores of Northen Mexico[J]. Forel Ecooy and Mamagement ,2009 ,257(2) :427-434.
[12]	Dong J R, Kaufmann R K,Myneni R B,et al.Remote sensing eaimates of boreal and temperate forest woody biomass :Carbon pools,sources ,and sins[J]. Remate Sensing of Environment,2003 ,84(3) :393-410.
[13]	陈尔学,李增元,武红敢,等.基于k- NN和Landsat数据的小面积统计单元森林蓄积估测方法.林业科学研究,2008 ,21(6):745-750.
[14]	Carus 0. Santoro M,Kelndorer J. Mapping forest aboveground biomas in the Northestem United States with ALOS PAISAR dualpolarization L-band[J]. Remote Sensing of Enviroment, 2012,124 :466-478.
[15]	Baler H.,Rowlanl c S,Saich P. Forest! cmopy heignt amnd curbon estimat ion at Monks Wood National Naure Reseve ,UK ,using dualwavelengh SAR iereromernt J]. Remoe Sensin of Envirorment ,2007 ,108(3):224-239.
[16]	陈尔学,李增元,庞勇,等.基于极化合成孔径雷达干涉测量的平均树高提取技:术[J].林业科学,2007 ,43(4) :66-71.
[17]	Treuhaft R N, Asner G P,Law B E.Structure - based forest biomass frum fusion of rader and hyersperer oeatiom[] Georphyial Reserch Leters ,2003.30(9):1472-1475.
[18]	Cartus 0, Santoro M,Schmllils C,et al. Large area forest stem volume mapping in the boreal zone using synery of ERS - 1/2 tandem coherence and MODIS vegetation cont inuous fileds[J]. Remote Sensing of Enwironment,201115(3):931-943.
[19]	庞勇,孙国清,李增元.林木空间格局对大光斑激光雷达波形影响模拟[J].遥感学报2006. 10(1):97-104.
[20]	Amini J,SumantyoJ T s. Employing a Method on SAR and Optical Images for Forest Biomass Estimaion[J]. IEEE Transacions on Ceosdine and Remole Sensin 209.47(12):4020-4026.
[21]	Quaie T, Levis P, Kauwe M DE, et al.Asimilating Canopy Refectance daa ino an Ecosystem Model with an Ensemble Kalman Filter[J]. Remote Sensin of Eavioment, 2008,112(4):1347-1364.
[22]	Lich H. Moleli the primy produdvui of the word[J]. Naureand rsource,1972.8(2)5-10.
[23]	Uchijin z, Seim H. Acolimimai ealation of net primary porductvrity of nat ure vetato((1)Chiugo modlel for evaluating pimary puivi[J]. Joumal of Agriculul Mateomoy 1985,40(4):342-352.
[24]	Running,S w,and Hunt E. R. Generalization of a forest ecosystem process model for other biomes,BIOME-BGC, and an apliation for gobal-cale models[M]//Scaling Pysologca Poces aff to Globe . San Diego: Academnice Pess,1993:141-158.
[25 ]	Parton w J,Scurlock J M ,0jima D s,et al. Observation and modeling of biomass and soil orgnic mater dynamics for the gassland biome wordvide[J]. Global Biogeochemical Cydes, 193,7(4):25 785-809.
[26]	Sich S,Smith B, Prentice I C.Evaluation of ecystem dynamie,plant geography and tresrial carbon eyling in the IPJ dynamic gobal vegetation mode[J]. Global Change Biology .20003 ,9(2):161- 185.
[27]	Veroustraete F,Sabbe H, Eerens H.Estimation of carbon mass fluxes over Europe using the C-Fix mode and Euolux da[J]. Remote Sensing Envronment ,2002 ,83(3):376-399.
[28]	Running s w,Thormton P E, Nemani R, et al. Global trrestrial gross and net primary proucti from the earth obevatin system[M]//Methods in Ecasystem Science. New York: SpringerVerla, 200:44-57.
[29]	Pine s D. Gownd s N. Global primary producion :a remle sensing ppch[J]. Joumal of Biogogaphy, 1995,. 22(4/5):815-835.
[30]	Potter C,Kloster s, Genovese v. Carbon Emisins from Deforesation in the Brarilian Amanon Regon[J]. Bigeocicnces 2009.6:2369-2381.
[31]	Swinbank w C. The measurement of verical transfer for heat and waler wupor by edies in the lower amope J]. Jumal of Mee orolgey ,1951 ,8(3):15-145.
[32]	Falge E,ebuen Bldochi D.at al. Phase and ampliudue ofecoystem cabhon relese and uptake potenias as derived fom FLUXNET measurements[J]. Agriculual and Forest Meorology. 202.11314):75-95.
[33]	Yu Guinui, Wen Xuefa, Sun Xiaomin et al. Overview of China FLUX and evaluatin of its eddy covriance measurement[J]. Ag rulou and Forst Meoon 2001313 -4):125-137.
[34]	Friend A D,Stevens A K, Knox R G,et al.FLUXNET and modelling the global carhon ecyde[J]. Clobal Change Bioloy 2007,13(3):610-633.
[35]	Brswel B H,Sacks w J,linder,.et al. Estima ing diumal to anwal ecosytem paraneters by synhesis of a cabhon fux model wih edy cowarine net cosgemn exchange oeretaon J]. Global Change Biology ,2005 11(2) :335-355.
[36]	Prevev L Baret F, Chary A, ea al. Asimilai of Multi - Sensorand Muti - Temporal Remote Sensing Data to Monior Vegtation and Sol-he Alplll -ReseDA prie[C]//IEEEE Inerataoina Geosciene and Remole Sensing Sympsium.nd Muti - Temporal Remote Sensing Data to Monior Vegtation and Sol-he Alplll -ReseDA prie[C]//IEEEE Inerataoina Geosciene and Remole Sensing Sympsium.1998 ,2399-2401.
[37]	Favard J c, Boiszeon D,Bare F ,er al. ADAM:a rerece dabase lo inestile asisilation of remate sensing obevation ino erp growh mlesclc//Pw. vm-th. Eur. Soe. Agrumomy Comgress. Denmak ,Coperhagn 204:213-214.
[38]	Koistn L, Wamelink w.,Schaepman-Strub G.et al. Assesing and prelicin hodiveniv in a foli cosen:e Asilaion of net pimury poucton dered frm imeg petooe due into a dymamic vegtation model[J]. Remole Sensing of Envirormemt,208,12(5):211-2130.
[39]	Dematy J.Chenalie F, et al.Friend A D.Asimlaion of gobal MODIS lef are index rieras within rerirt hnphehe mol(lJ Ccpyeiee Rere Lutes .2007 34(15) :402-422
[40]	Mo Xngo,Chen JngmingJu Weimin.et al. Opimizain of eco. system mdel parameters through asisilain edy covarince flux data wih an ensemble Kalman flue[J]. Eeologieal Modelin, 2008 ,217(1):157-173.