ZHAO Bin , WU Qianhong , GUO Haiqiang , YAN Yaner . On the Coupling between Eddy Covariance and Remote Sensing Techniques in Ecosystem Carbon Flux Estimation[J]. Advances in Earth Science, 2008 , 23(8) : 884 -894 . DOI: 10.11867/j.issn.1001-8166.2008.08.0884

[1] Thomas C D，Williams S E，Cameron A，et al. Biodiversity conservation: Uncertainty in predictions of extinction risk/Effects of changes in climate and land use/Climate change and extinction risk（Reply）[J]. Nature，2004，430:6995.

[2] Thomas C D，Cameron A，Green R E，et al. Extinction risk from climate change [J]. Nature，2004，427（6 970）:145-148. 

[3] Schimel D S，House J I，Hibbard K A，et al. Recent patterns and mechanisms of carbon exchange by terrestrial ecosystems [J]. Nature，2001，414（6 860）: 169-172. 

[4] Hoffert M I，Caldeira K，Benford G，et al. Advanced technology paths to global climate stability: Energy for a greenhouse planet [J]. Science，2002，298（5 595）: 981-987. 

[5] Yu Guirui. Global Change Carbon Cycle and Storage in Terrestrial Ecosystem [M]. Beijing：China Meteorological Press，2003.[于贵瑞.全球变化与陆地生态系统碳循环和碳蓄积[M]. 北京：气象出版社，2003.]

[6] Kang S，Running S W，Lim J H，et al. A regional phenology model for detecting onset of greenness in temperate mixed forests，Korea: An application of MODIS leaf area index [J]. Remote Sensing of Environment，2003，86: 232-242. 

[7] Baldocchi D，Falge E，Gu L H，et al. FLUXNET: A new tool to study the temporal and spatial variability of ecosystem-scale carbon dioxide，water vapor，and energy flux densities [J]. Bulletin of the American Meteorological Society，2001，82（11）: 2 415-2 434.

[8] Baldocchi D D. Assessing the eddy covariance technique for evaluating carbon dioxide exchange rates of ecosystems: Past，present and future [J]. Global Change Biology，2003，9（4）: 479-492. 

[9] Running S W，Baldocchi D D，Turner D P，et al. A global terrestrial monitoring network integrating tower fluxes，flask sampling，ecosystem modeling and EOS satellite data [J]. Remote Sensing of Environment，1999，70（1）: 108-127. 

[10] Yu Guirui，Sun Xiaoming. Principles of Flux Measurement in Terrestrial Ecosystems [M]. Beijing: Higher Education Press，2006.[于贵瑞，孙晓明. 陆地生态系统通量观测的原理与方法[M]. 北京：高等教育出版社，2006.]

[11] Nagler P L，Cleverly J，Glenn E，et al. Predicting riparian evapotranspiration from MODIS vegetation indices and meteorological data [J]. Remote Sensing of Environment，2005，94（1）: 17-30. 

[12] Yu G R，Zhang L M，Sun X M，et al. Advances in carbon flux observation and research in Asia [J]. Science in China（Series D），2005，48: 1-16. 

[13] Veroustraete F，Sabbe H，Rasse D P，et al. Carbon mass fluxes of forests in Belgium determined with low resolution optical sensors [J]. International Journal of Remote Sensing，2004，25（4）: 769-792. 

[14] Amthor J S，Chen J M，Clein J S，et al. Boreal forest CO₂ exchange and evapotranspiration predicted by nine ecosystem process models: Intermodel comparisons and relationships to field measurements [J]. Journal of Geophysical Research Atmospheres，2001，106（D24）: 33 623-33 648.

[15] Wilson K，Goldstein A，Falge E，et al. Energy balance closure at FLUXNET sites[J]. Agricultural and Forest Meteorology，2002，113（1/4）: 223-243. 

[16] Potter C，Klooster S，Hiatt S，et al. Methane emissions from natural wetlands in the United States: Satellite-derived estimation based on ecosystem carbon cycling [J]. Earth Interactions，2006，10:1-12. 

[17] Potter C S，Randerson J T，Field C B，et al. Terrestrial ecosystem production: A process model based on global satellute and surface data [J]. Global Biogeochemical Cycles，1993，7（4）: 811-842. 

[18] Chen J M，Liu J，Cihlar J，et al. Daily canopy photosynthesis model through temporal and spatial scaling for remote sensing applications [J]. Ecological Modelling，1999，124（2/3）: 99-119. 

[19] Adiku S G K，Reichstein M，Lohila A，et al. PIXGRO: A model for simulating the ecosystem CO₂ exchange and growth of spring barley [J]. Ecological Modelling，2006，190（3/4）: 260-276. 

[20] Kimball J S，Running S W，Saatchi S S. Sensitivity of boreal forest regional water flux and net primary production simulations to sub-grid-scale land cover complexity [J]. Journal of Geophysical Research-Atmospheres，1999，104（D22）: 27 789-27 801.

[21] Kimball J S，White M A，Running S W. BIOME-BGC simulations of stand hydrologic processes for BOREAS [J]. Journal of Geophysical Research，1997，102（24）: 29 043-29 052. 

[22] Zhang R H，Sun X M，Zhu Z L，et al. A remote sensing model of CO₂ flux for wheat and studying of regional distribution [J]. Science in China（Series D），1999，42（3）: 325-332. 

[23] Houborg R M，Soegaard H. Regional simulation of ecosystem CO₂ and water vapor exchange for agricultural land using NOAA AVHRR and Terra MODIS satellite data，application to Zealand，Denmark [J]. Remote Sensing of Environment，2004，93（1/2）: 150-167.

[24] Boegh E，Soegaard H. Remote sensing based estimation of evapotranspiration rates [J]. International Journal of Remote Sensing，2004，25（13）: 2 535-2 551. 

[25] Reich P B，Turner D P，Bolstad P. An approach to spatially distributed modeling of net primary production（NPP） at the landscape scale and its application in validation of EOS NPP products [J]. Remote Sensing of Environment，1999，70（1）: 69-81.

[26] Chiesi M，Maselli F，Bindi M，et al. Modelling carbon budget of Mediterranean forests using ground and remote sensing measurements [J]. Agricultural and Forest Meteorology，2005，135（1/4）: 22-34. 

[27] Fuentes D A，Gamon J A，Cheng Y F，et al. Mapping carbon and water vapor fluxes in a chaparral ecosystem using vegetation indices derived from AVIRIS [J]. Remote Sensing of Environment，2006，103（3）: 312-323.

[28] Wythers K R，Reich P B，Turner D P. Predicting leaf area index from scaling principles: Corroboration and consequences [J]. Tree Physiology，2003，23（17）: 1 171-1 179. 

[29] Heinsch F A，Zhao M S，Running S W，et al. Evaluation of remote sensing based terrestrial productivity from MODIS using regional tower eddy flux network observations [J]. IEEE Transactions on Geoscience and Remote Sensing，2006，44（7）:1 908-1 925.

[30] Zhao M，Heinsch F A，Nemani R R，et al. Improvements of the MODIS terrestrial gross and net primary production global data set [J]. Remote Sensing of Environment，2005，95（2）: 164-176. 

[31] Waring R H，Law B E，Goulden M L，et al. Scaling gross ecosystem production at harvard forest with remote-sensing-A comparison of estimates from a constrained quantum-use efficiency Model and eddy-correlation [J]. Plant Cell and Environment，1995，18（10）: 1 201-1 213.

[32] Turner D P，Urbanski S，Bremer D，et al. A cross-biome comparison of daily light use efficiency for gross primary production [J]. Global Change Biology，2003，9（3）:383-395. 

[33] Turner D P，Ritts W D，Cohen W B，et al. Site-level evaluation of satellite-based global terrestrial gross primary production and net primary production monitoring [J]. Global Change Biology，2005，11（4）: 666-684.

[34] Turner D P，Ollinger S，Smith M L，et al. Scaling net primary production to a MODIS footprint in support of Earth observing system product validation [J]. International Journal of Remote Sensing，2004，25（10）:1 961-1 979.

[35] Cohen W B，Maiersperger T K，Turner D P，et al. MODIS land cover and LAI collection 4 product quality across nine sites in the western hemisphere [J]. IEEE Transactions on Geoscience and Remote Sensing，2006，44（7）: 1 843-1 857. 

[36] Leuning R，Cleugh H A，Zegelin S J，et al. Carbon and water fluxes over a temperate Eucalyptus forest and a tropical wet/dry savanna in Australia: Measurements and comparison with MODIS remote sensing estimates [J]. Agricultural and Forest Meteorology，2005，129（3/4）: 151-173.

[37] Coops N C，Jassal R S，Leuning R，et al. Incorporation of a soil water modifier into MODIS predictions of temperate Douglas-fir gross primary productivity: Initial model development [J]. Agricultural and Forest Meteorology，2007，147（3/4）: 99-109.

[38] Walsh S J，Butler D R，Malanson G P. An overview of scale，pattern，process relationships in geomorphology: A remote sensing and GIS perspective [J]. Geomorphology，1998，21（3/4）: 183-205. 

[39] Igarashi T，Shimada M，Rosenqvist A，et al. Preliminary study on data sets of ADEOS-II and ALOS dedicated to terrestrial carbon observation [C]∥Calibration，Characterization of Satellite Sensors，Physical Parameters Derived from Satellite Data. Kidlington: Pergamon Elsevier Science Ltd，2003:2 147-2 152.

[40] Gao Q，Yu M，Yang X S，et al. Scaling simulation models for spatially heterogeneous ecosystems with diffusive transportation [J]. Landscape Ecology，2001，16（4）: 289-300. 

[41] Lakshmi V，Zehrfuhs D. Normalization and comparison of surface temperatures across a range of scales [J]. IEEE Transactions on Geoscience and Remote Sensing，2002，40（12）: 2 636-2 646. 

[42] Cheng Y，Gamon J A，Fuentes D A，et al. A multi-scale analysis of dynamic optical signals in a Southern California chaparral ecosystem: A comparison of field，AVIRIS and MODIS data [J]. Remote Sensing of Environment，2006，103: 369-378. 

[43] Anderson M C，Kustas W P，Norman J M. Upscaling and downscaling—A regional view of the soil-plant-atmosphere continuum [J]. Agronomy Journal，2003，95（6）: 1 408-1 423. 

[44] Anderson M C，Neale C M U，Li F，et al. Upscaling ground observations of vegetation water content，canopy height，and leaf area index during SMEX02 using aircraft and Landsat imagery [J]. Remote Sensing of Environment，2004，92（4）: 447-464.

[45] Gamon J A，Cheng Y，Claudio H，et al. A mobile tram system for systematic sampling of ecosystem optical properties [J]. Remote Sensing of Environment，2006，103: 246-254. 

[46] Anderson M C，Kustas W P，Norman J M. Upscaling flux observations from local to continental scales using thermal remote sensing [J]. Agronomy Journal，2007，99（1）: 240-254.

[47] Gioli B，Miglietta F，De Martino B，et al. Comparison between tower and aircraft-based eddy covariance fluxes in five European regions [J]. Agricultural and Forest Meteorology，2004，127（1/2）: 1-16. 

[48] Brunsell N A，Gillies R R. Length scale analysis of surface energy fluxes derived from remote sensing [J]. Journal of Hydrometeorology，2003，4（6）: 1 212-1 219. 

[49] Running S W，Nemani R R，Heinsch F A，et al. A continuous satellite-derived measure of global terrestrial primary production [J]. Bioscience，2004，54（6）: 547-560. 

[50] Gamon J A，Rahman A F，Dungan J L，et al. Spectral Network（SpecNet）-What is it and why do we need it? [J]. Remote Sensing of Environment，2006，103（3）: 227-235. 

[51] Wang Q，Tenhunen J，Falge E，et al. Simulation and scaling of temporal variation in gross primary production for coniferous and deciduous temperate forests [J]. Global Change Biology，2004，10（1）: 37-51. 

[52] Hagen S C，Braswell B H，Linder E，et al. Statistical uncertainty of eddy flux-based estimates of gross ecosystem carbon exchange at Howland Forest，Maine [J]. Journal of Geophysical Research Atmospheres，2006，111: D08S03. 

[53] Gilmanov T G，Johnson D A，Saliendra N Z. Growing season CO₂ fluxes in a sagebrush-steppe ecosystem in Idaho: Bowen ratio/energy balance measurements and modeling [J]. Basic and Applied Ecology，2003，4（2）: 167-183.

[54] Falge E，Reth S，Bruggemann N，et al. Comparison of surface energy exchange models with eddy flux data in forest and grassland ecosystems of Germany [J]. Ecological Modelling，2005，188（2/4）: 174-216. 

[55] 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. 

[56] Papale D，Reichstein M，Aubinet M，et al. Towards a standardized processing of Net Ecosystem Exchange measured with eddy covariance technique: Algorithms and uncertainty estimation [J]. Biogeosciences，2006，3（4）: 571-583. 

[57] Jiang H L，Feingold G. Effect of aerosol on warm convective clouds: Aerosol-cloud-surface flux feedbacks in a new coupled large eddy model [J]. Journal of Geophysical Research-Atmospheres，2006，111:D01202. 

[58] Lu L X，Shuttleworth W J. Incorporating NDVI-derived LAI into the climate version of RAMS and its impact on regional climate [J]. Journal of Hydrometeorology，2002，3（3）: 347-362. 

[59] Zhang L，Wylie B，Loveland T，et al. Evaluation and comparison of gross primary production estimates for the Northern Great Plains grasslands [J]. Remote Sensing of Environment，2007，106（2）: 173-189. 

[60] Boegh E，Soegaard H，Christensen J H，et al. Combining weather prediction and remote sensing data for the calculation of evapotranspiration rates: Application to Denmark [J]. International Journal of Remote Sensing，2004，25（13）: 2 553-2 574.

[61] Turner W，Spector S，Gardiner N，et al. Remote sensing for biodiversity science and conservation [J]. Trends in Ecology & Evolution，2003，18（6）: 306-315. 

[62] Turner D P，Ritts W D，Zhao M S，et al. Assessing interannual variation in MODIS-based estimates of gross primary production [J]. IEEE Transactions on Geoscience and Remote Sensing，2006，44（7）: 1 899-1 907. 

[63] Turner D P，Ritts W D，Cohen W B，et al. Evaluation of MODIS NPP and GPP products across multiple biomes [J]. Remote Sensing of Environment，2006，102（3/4）: 282-292. 

[64] Sims D A，Luo H Y，Hastings S，et al. Parallel adjustments in vegetation greenness and ecosystem CO₂ exchange in response to drought in a Southern California chaparral ecosystem [J]. Remote Sensing of Environment，2006，103（3）: 289-303. 

[65] Schwalm C R，Black T A，Amiro B D，et al. Photosynthetic light use efficiency of three biomes across an east-west continental-scale transect in Canada [J]. Agricultural and Forest Meteorology，2006，140（1/4）: 269-286.

[66] Xiao X M. Light absorption by leaf chlorophyll and maximum light use efficiency [J]. IEEE Transactions on Geoscience and Remote Sensing，2006，44（7）:1 933-1 935. 

[67] Sims D A，Rahman A F，Cordova V D，et al. On the use of MODIS EVI to assess gross primary productivity of North American ecosystems [J]. Journal of Geophysical Research-Biogeosciences，2006，111（G04015），doi:10.1029/2006JG000162.

[68] Gower S T，Kuckarik C J，Norman J M. Direct and indirect estimation of leaf area index，fAPAR and net primary production of terrestrial ecosystems [J]. Remote Sensing of Environment，1999，70: 29-51. 

[69] Turner D P，Gower S T，Cohen W B，et al. Effects of spatial variability in light use efficiency on satellite-based NPP monitoring [J]. Remote Sensing of Environment，2002，80（3）: 397-405. 

[70] Sims D A，Rahman A F，Cordova V D，et al. Midday values of gross CO₂ flux and light use efficiency during satellite overpasses can be used to directly estimate eightday mean flux [J]. Agricultural and Forest Meteorology，2005，131（1/2）: 1-12.

[71] Xiao X M，Zhang Q Y，Hollinger D，et al. Modeling gross primary production of an evergreen needleleaf forest using MODIS and climate data [J]. Ecological Applications，2005，15（3）: 954-969. 

[72] Ruimy A，Javis P，Saugier B，et al. CO₂ flux over plant canopies and solar radiation: A review [J]. Advances in Ecological Research，1995，26: 1-68. 

[73] Ruimy A，Dedieu G，Saugier B. TURC: A diagnostic model of continental gross primary productivity and net primary productivity [J]. Global Biogeochemical Cycles，1996，10（2）: 269-285. 

[74] Asner G P，Wessman C A，Schimel D S，et al. Variability in leaf and litter optical properties: Implications for BRDF model inversions using AVHRR，MODIS，and MISR [J]. Remote Sensing of Environment，1998，63（3）: 243-257. 

[75] Hanan N P. Enhanced two-layer radiative transfer scheme for a land surface model with a discontinuous upper canopy [J]. Agricultural and Forest Meteorology，2001，109（4）: 265-281. 

[76] Hanan N P，Burba G，Verma S B，et al. Inversion of net ecosystem CO₂ flux measurements for estimation of canopy PAR absorption [J]. Global Change Biology，2002，8（6）: 563-574. 

[77] Oliphant A，Susan C，Grimmond B，et al. Local-scale heterogeneity of photosynthetically active radiation （PAR），absorbed PAR and net radiation as a function of topography，sky conditions and leaf area index [J]. Remote Sensing of Environment，2006，103: 324-337.

[78] Kang S，Running S W，Zhao M，et al. Improving continuity of MODIS terrestrial photosynthesis products using an interpolation scheme for cloudy pixels [J]. International Journal of Remote Sensing，2005，26（8）: 1 659-1 676.

[79] Zhao Bin，Chen Shiping. The application of eddy covariance technology in ecology [C]∥Chen Jiquan，Li Bo，Ma Zhijun，et al，eds. Challenges Facing Ecologists: Question and Approaches. Beijing: Higher Education Press，2005:68-102.[赵斌，陈世苹. 涡度协方差技术在生态学中的应用[C]∥陈吉泉，李博，马志军，等编. 生态学家面临的挑战——问题与途径. 北京：高等教育出版社，2005:68-102.]

[80] Göckede M，Rebmann C，Foken T. A combination of quality assessment tools for eddy covariance measurements with footprint modelling for the characterisation of complex sites [J]. Agricultural and Forest Meteorology，2004，127（3/4）: 175-188.

[81] Schmid H P. Experimental design for flux measurements: Matching scales of observations and fluxes [J]. Agricultural and Forest Meteorology，1997，87（2/3）: 179-200. 

[82] Finnigan J. The footprint concept in complex terrain [J]. Agricultural and Forest Meteorology，2004，127（3/4）: 117-129. 

[83] Foken T，Wichura B. Tools for quality assessment of surface-based flux measurements [J]. Agricultural and Forest Meteorology，1996，78（1/2）: 83-105. 

[84] Sogachev A，Rannik U，Vesala T. Flux footprints over complex terrain covered by heterogeneous forest [J]. Agricultural and Forest Meteorology，2004，127（3/4）: 143-158. 

[85] Kurbanmuradov O，Rannik U，Sabelfeld K，et al. Evaluation of mean concentration and fluxes in turbulent flows by Lagrangian stochastic models [J]. Mathematics and Computers in Simulation，2001，54（6）: 459-476.

[86] Schmid H P. Footprint modeling for vegetation atmosphere exchange studies: A review and perspective [J]. Agricultural and Forest Meteorology，2002，113: 159-183. 

[87] Vesala T，Rannik U，Leclerc M，et al. Flux and concentration footprints [J]. Agricultural and Forest Meteorology，2004，127（3/4）:111-116. 

[88] Foken T，Leclerc M Y. Methods and limitations in validation of footprint models [J]. Agricultural and Forest Meteorology，2004，127（3/4）:223-234.

[89] Gockede M，Markkanen T，Hasager C B，et al. Update of a footprint-based approach for the characterisation of complex measurement sites [J]. Boundary-Layer Meteorology，2006，118（3）:635-655. 

[90] Rannik U，Raittila J. Turbulence statistics inside an over forest: Influence on footprint prediction [J]. Boundary-layer Meteorology，2003，109:137-166. 

[91] Rebmann C，Gockede M，Foken T，et al. Quality analysis applied on eddy covariance measurements at complex forest sites using footprint modeling [J]. Theoretical and Applied Climatology，2005，80（2/4）: 121-141.

[92] Reithmaier L M，Gockede M，Markkanen T，et al. Use of remotely sensed land use classification for a better evaluation of micrometeorological flux measurement sites [J]. Theoretical and Applied Climatology，2006，84（4）: 219-233.

[93] Kim J，Guo Q，Baldocchi D D，et al. Upscaling fluxes from tower to landscape: Overlaying flux footprints on high-resolution（IKONOS） images of vegetation cover[J]. Agricultural and Forest Meteorology，2006，136（3/4）: 132-146. 

[94] House J I，Prentice I C，Ramankutty N，et al. Reconciling apparent inconsistencies in estimates of terrestrial CO₂ sources and sinks [J]. Tellus Series B-Chemical and Physical Meteorology，2003，55（2）: 345-363. 

[95] Xiao X M，Zhang Q Y，Braswell B，et al. Modeling gross primary production of temperate deciduous broadleaf forest using satellite images and climate data [J]. Remote Sensing of Environment，2004，91（2）: 256-270.

[96] Zhao M，Running S W，Nemani R R. Sensitivity of Moderate Resolution Imaging Spectroradiometer （MODIS） terrestrial primary production to the accuracy of meteorological reanalyses [J]. Journal of Geophysical Research-Biogeosciences，2006，111:G01002. 

[97] Li Z Q，Yu G R，Xiao X M，et al. Modeling gross primary production of alpine ecosystems in the Tibetan Plateau using MODIS images and climate data [J]. Remote Sensing of Environment，2007，107（3）: 510-519.

[98] Turner D P，Ritts W D，Cohen W B，et al. Scaling gross primary production（GPP） over boreal and deciduous forest landscapes in support of MODIS GPP product validation [J]. Remote Sensing of Environment，2003，88（3）: 256-270. 

[99] Xiao X M，Zhang Q Y，Saleska S，et al. Satellite-based modeling of gross primary production in a seasonally moist tropical evergreen forest [J]. Remote Sensing of Environment，2005，94（1）: 105-122. 

[100] Gebremichael M，Barros A P. Evaluation of MODIS gross primary productivity（GPP） in tropical monsoon regions [J]. Remote Sensing of Environment，2006，100（2）:150-166.