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遥感技术与应用  2016, Vol. 31 Issue (4): 663-671    DOI: 10.11873/j.issn.1004-0323.2016.4.0663
模型与反演     
2001~2011年中国农田最大光能利用率参数时空变化特征
康婷婷1,居为民2,张春华3
(1.江苏师范大学城市与环境学院,江苏 徐州 221116;
2.南京大学国际地球系统科学研究所,江苏 南京 210023;
3.鲁东大学资源与环境工程学院,山东 烟台 264025)
Study on the Spatial and Temporal Variations of China’s Cropland Maximum Light Use Efficiency in 2001~2011
Kang Tingting1,Ju Weimin2,Zhang Chunhua3
(1.School of Urban and Environment Sciences,Jiangsu Normal University,Xuzhou 221116,China;
2.International Institute for Earth System Science,Nanjing University,Nanjing 210023,China;
3.School of Resources and Environmental Engineering,Ludong University,Yantai 264025,China)
 全文: PDF(10023 KB)  
摘要:

基于遥感数据的光能利用率模型被广泛应用于计算陆地生态系统的生产力,其结果对最大光能利用率(ε max)参数非常敏感。利用农业产量统计数据、MODIS遥感数据、气象观测数据和植被光合模型(VPM)推算2001~2011年全国各省逐年的农田平均ε max,并分析其时空变化特征及其影响因素。研究结果表明:2001~2011年全国31个省的农田ε max的变化范围为0.57~2.20 g C·MJ-1,呈现出东部和中部较高、西北和西南较低的分布特征。大部分省份农田ε max呈现上升趋势,但在2001~2007年存在年际波动,2008年后ε max呈相对稳定增长趋势。各省农田ε max的年际波动幅度呈现北高南低、东高西低的分布特征。大部分省份农田ε max的年际变化与单位耕地面积农用化肥施用量存在显著的正相关性(P<0.05);C4作物面积比例变化也是导致农田ε max变化的原因之一。在利用光能利用率模型计算农田生产力时,需要发展考虑ε max 时空变化的参数化方案。

关键词: 最大光能利用率VPM模型农田时空变化影响因子    
Abstract:

Remote sensing driven light use efficiency models have been widely utilized to calculate the productivity of terrestrial ecosystems.The outputs of these models are very sensitive to maximum light use efficiency (ε max.In this study,the province\|level yield census data,MODIS reflectance data,locally observed meteorological data,and the Vegetation Photosynthesis Model (VPM) were employed to derive annual mean province\|level cropland ε max  in the mainland of China from 2001 to 2011.Then,the spatial,temporal variations of ε max and possible driving factors were analyzed.The results show that,during the study period,the province\|level means of cropland ε max in 31 provinces varied between 0.57~2.20 g C·MJ-1,which was higher in the east and central parts and lower in the northwest and southwest parts.Annual mean cropland ε max increased in most provinces  but showed interannual fluctuations during the period from 2001 to 2007.It relatively steadily increased since 2008.The interannual fluctuations of province\|level cropland ε max were normally higher in the north than in the south,and higher in the east than in the west.The annual means of cropland ε max had strong positi e correlation with the amount of fertilizer used in per unit area of cultivated cropland in most provinces,and it reached significant level (P<0.05),so the increase of the consumption of chemical fertilizer in these regions was one of the main causes of the increase of cropland ε max.Since the interannual fluctuations of ε max  were also related to the yield fraction of C4 crops (corn),the increase of the yield fraction of C4 crops could also induce the increase of cropland ε max.This study proves that it is of importance to develop a parameterization scheme accounting for the temporal and spatial variations of  max for improving the calculation of productivity in croplands by using light use efficiency models and remote sensing data.

Key words: Light use efficiency    Vegetation photosynthesis model    Croplands    Spatial and temporal variations    Driving factors
收稿日期: 2015-11-12 出版日期: 2016-10-14
:  TP 79  
基金资助:

中国科学院碳专项(XDA05050602-1),国家自然科学基金项目(41371070)。

通讯作者: 居为民(1963-),男,江苏南通人,博士生导师,主要从事生态环境遥感和全球变化研究。Email:juweimin@nju.edu.cn。    
作者简介: 康婷婷(1989-),女,山东聊城人,主要从事植被遥感应用方面的研究。Email:kangtingting.1989@163.com。
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引用本文:

康婷婷,居为民,张春华. 2001~2011年中国农田最大光能利用率参数时空变化特征[J]. 遥感技术与应用, 2016, 31(4): 663-671.

Kang Tingting,Ju Weimin,Zhang Chunhua. Study on the Spatial and Temporal Variations of China’s Cropland Maximum Light Use Efficiency in 2001~2011. Remote Sensing Technology and Application, 2016, 31(4): 663-671.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2016.4.0663        http://www.rsta.ac.cn/CN/Y2016/V31/I4/663

[1]Li Gang,Wang Daolong,Zhang Hua,et al.Spatio-temporal Variations Analysis of Grassland’s Light Use Efficiency in Inner Mongolia based on MODIS Data[J].Journal of Natural Resources,2010,25(6):1001-1012.[李刚,王道龙,张华,等.基于MODIS数据的内蒙古草地光能利用率时空变化分析[J].自然资源学报,2010,25(6):1001-1012.]

[2]Zhu Wenquan,Pan Yaozhong,He Hao,et al.Simulation of Light Utilization Efficiency of Typical Vegetation in China[J].Chinese Science Bulletin,2006,51(6):700-706.[朱文泉,潘耀忠,何浩,等.中国典型植被最大光利用率模拟[J].科学通报,2006,51(6):700-706.]

[3]Tong Xiaojuan,Li Jun,Wang Ling.A Review on Radiation Use Efficiency of the Cropland[J].Chinese Journal of Ecology,2008,27(6):1021-1028.[同小娟,李俊,王玲.农田光能利用效率研究进展[J].生态学杂志,2008,27(6):1021-1028.]

[4]Li A N,Bian J H,Lei G B,et al.Estimating the Maximal Light Use Efficiency for Different Vegetation through the CASA Model Combined with Time-series Remote Sensing Data and Ground Measurements[J].Remote Sensing,2012,4(12):3857-3876.

[5]Mo X G,Liu S X.Simulating Evapotranspiration and Photosynthesis of Winter Wheat over the Growing Season[J].Agricultural and Forest Meteorology,2001,109(3):203-222.

[6]Sabine T P,Robert M N,Saman S,et al.Will Intra-specific Differences in Transpiration Efficiency in Wheat Be Maintained in a High CO2 World? A FACE Study[J].Physiologia Plantarum,2013,148(2):232-245.

[7]Yan H M,Fu Y L,Xiao X M,et al.Modeling Gross Primary Productivity for Winter Wheat-maize Double Cropping System Using MODIS Time Series and CO2 Eddy Flux Tower Data[J].Agriculture Ecosystems and Environment,2009,129(4):391-400.

[8]Lobell D B,Hicke J A,Asner G P,et al.Satellite Estimates of Productivity and Light Use Efficiency in the United States Agriculture,1982-1998[J].Global Change Biology,2002,8(8):722-735.

[9]Bandaru V,West T O,Ricciuto D M,et al.Estimating Crop Net Primary Production Using National Inventory Data and MODIS-derived Parameters[J].ISPRS Journal of Photogrammetry and Remote Sensing,2013,80:61-71.

[10]Huete A,Didan K,Miura T,et al.Overview of the Radiometric and Biophysical Performance of the MODIS Vegetation Indices[J].Remote Sensing of Environment,2002,83(1):195-213.

[11]Xiao X M,Hollinger D,Aber J,et al.Satellite-based Modeling of Gross Primary Production in an Evergreen Needle Leaf Forest[J].Remote Sensing of Environment,2004,89(4):519-534.

[12]Kang Tingting,Gao Ping,Ju Weimin,et al.The Spatial and Temporal Variations of Maximum Light Use Efficiency and Possible Driving Factors of Croplands in Jiangsu Province[J].Acta Ecologica Sinica,2014,34(2):410-420.[康婷婷,高苹,居为民,等.江苏省农作物最大光能利用率时空特征及影响因子[J].生态学报,2014,34(2):410-420.][13]Chen J M,Deng F,Chen M Z.Locally Adjusted Cubic-spline Capping for Reconstructing Seasonal Trajectories of a Satellite-derived Surface Parameter[J].IEEE Transactions on Geoscience and Remote Sensing,2006,44(8):2230-2238.

[14]Ju W M,Gao P,Zhou Y L.Combining an Ecological Model with Remote Sensing and GIS Techniques to Monitor Soil Water Content of Croplands with a Monsoon Climate[J].Agricultural Water Management,2010,97(8):1221-1231.

[15]Huang Y,Zhang W,Sun W J,et al.Net Primary Production of Chinese Croplands from 1950 to 1999[J].Ecological Applications,2007,17(3):692-701.

[16]Prince S D,Haskett J,Steininger M,et al.Net Primary Production of US Midwest Croplands from Agricultural Harvest Yield Data[J].Ecological Applications,2001,11(4):1194-1205.

[17]Xiao X M,Zhang Q Y,Urbanski S,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.

[18]Xiao X M,Zhang Q Y,Hollinger D,et al.Modeling Gross Primary Production of an Evergreen Needle Leaf Forest Using MODIS and Climate Data[J].Ecological Applications,2005,15(3):954-969.

[19]Xiao X M,Zhang Q Y,Hutyra L,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.

[20]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.

[21]Wu Weixing,Wang Shaoqiang,Xiao Xiangming,et al.Simulation of Inner Mongolia Temperate Grassland Ecosystem Gross Primary Productivity Using MODIS Image and Climate Data[J].Science in China D Series,2008,38(8):993-1004.[伍卫星,王绍强,肖向明,等.利用MODIS影像和气候数据模拟中国内蒙古温带草原生态系统总初级生产力[J].中国科学D辑,2008,38(8):993-1004.]

[22]Wang Z,Xiao X M,Yan X D.Modeling Gross Primary Production of Maize Cropland and Degraded Grassland in Northeastern China[J].Agricultural and Forest Meteorology,2010,150(9):1160-1167.

[23]Kalfas J L,Xiao X M,Vanegas D X,et al.Modeling Gross Primary Production of Irrigated and Rain-fed Maize Using MODIS Imagery and CO2 Flux Tower Data[J].Agricultural and Forest Meteorology,2011,151(12):1514-1528.

[24]Wang H,Jia G,Fu C B,et al.Deriving Maximal Light Use Efficiency from Coordinated Flux Measurements and Satellite Data for Regional Gross Primary Production Modeling[J].Remote Sensing of Environment,2010,114(10):2248-2258.

[25]Zhu Wenquan,Pan Yaozhong,Zhang Jinshui.Estimation of Net Primary Productivity of Chinese Terrestrial Vegetation based on Remote Sensing[J].Journal of Plant Ecology,2007,31(3):413-424.[朱文泉,潘耀忠,张锦水.中国陆地植被净初级生产力遥感估算[J].植物生态学报,2007,31(3):413-424.]

[26]Zhang Y,Yu G,Yang J,et al.Climate-driven Global Changes in Carbon Use Efficiency[J].Global Ecology and Biogeography,2014,23(2):144-155.

[27]Ruimy A,Saugier B,Dedieu G.Methodology for the Estimation of Terrestrial Net Primary Production from Remotely Sensed Data[J].Journal of Geophysical Research,1994,99(D3):18515-18521.

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