|
|
|
|
|
| Spatial Exploration of Multiple Cropping Efficiency in China Based on Time Series Remote Sensing Data and Econometric Model |
| ZUO Li-jun, WANG Xiao, LIU Fang , YI Ling |
| Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, P.R.China |
|
|
|
摘要 This study explored spatial explicit multiple cropping efficiency (MCE) of China in 2005 by coupling time series remote sensing data with an econometric model - stochastic frontier analysis (SFA). We firstly extracted multiple cropping index (MCI) on the basis of the close relationship between crop phenologies and moderate-resolution imaging spectroradiometer (MODIS) enhanced vegetation index (EVI) value. Then, SFA model was employed to calculate MCE, by considering several indicators of meteorological conditions as inputs of multiple cropping systems and the extracted MCI was the output. The result showed that 46% of the cultivated land in China in 2005 was multiple cropped, including 39% doublecropped land and 7% triple-cropped land. Most of the multiple cropped land was distributed in the south of Great Wall. The total efficiency of multiple cropping in China was 87.61% in 2005. Southwestern China, Ganxin Region, the middle and lower reaches of Yangtze River and Huanghuaihai Plain were the four agricultural zones with the largest rooms for increasing MCI and improving MCE. Fragmental terrain, soil salinization, deficiency of water resources, and loss of labor force were the obstacles for MCE promotion in different zones. The method proposed in this paper is theoretically reliable for MCE extraction, whereas further studies are need to be done to investigate the most proper indicators of meteorological conditions as the inputs of multiple cropping systems.
Abstract This study explored spatial explicit multiple cropping efficiency (MCE) of China in 2005 by coupling time series remote sensing data with an econometric model - stochastic frontier analysis (SFA). We firstly extracted multiple cropping index (MCI) on the basis of the close relationship between crop phenologies and moderate-resolution imaging spectroradiometer (MODIS) enhanced vegetation index (EVI) value. Then, SFA model was employed to calculate MCE, by considering several indicators of meteorological conditions as inputs of multiple cropping systems and the extracted MCI was the output. The result showed that 46% of the cultivated land in China in 2005 was multiple cropped, including 39% doublecropped land and 7% triple-cropped land. Most of the multiple cropped land was distributed in the south of Great Wall. The total efficiency of multiple cropping in China was 87.61% in 2005. Southwestern China, Ganxin Region, the middle and lower reaches of Yangtze River and Huanghuaihai Plain were the four agricultural zones with the largest rooms for increasing MCI and improving MCE. Fragmental terrain, soil salinization, deficiency of water resources, and loss of labor force were the obstacles for MCE promotion in different zones. The method proposed in this paper is theoretically reliable for MCE extraction, whereas further studies are need to be done to investigate the most proper indicators of meteorological conditions as the inputs of multiple cropping systems.
|
|
Received: 30 July 2012
Accepted:
|
| Fund: This work was supported by the National Natural Science Foundation of China (41001277) and the National 973 Program of China (2010CB95090102). The authors also express appreciation to all persons and institutes who kindly made their data available for this analysis. |
|
Corresponding Authors:
Correspondence ZUO Li-jun, Tel: +86-10-64889202, Mobile: 13466629007, E-mail: zuolj@irsa.ac.cn
E-mail: zuolj@irsa.ac.cn
|
Cite this article:
ZUO Li-jun, WANG Xiao, LIU Fang , YI Ling.
2013.
Spatial Exploration of Multiple Cropping Efficiency in China Based on Time Series Remote Sensing Data and Econometric Model. Journal of Integrative Agriculture, 12(5): 903-913.
|
| [1]Ali A M S. 2007. Population pressure, agriculturalintensification and changes in rural systems inBangladesh. Geoforum, 38, 720-738[2]Amundoson R, Guo Y, Gong P. 2003. Soil diversity andland use in the United States. Ecosystems, 6, 470-482[3]Audsley E, Pearn K R, Simota C, Cojocaru G, Koutsidou E,Rounsevell M D A, Trnka M, Alexandrov V. 2006. Whatcan scenario modelling tell us about future Europeanscale agricultural land use, and what not? Environmental Science & Policy, 9, 148-162[4]Chen J. 2007. Rapid urbanization in China: A real challengeto soil protection and food security. CATENA, 69, 1-15[5]Coelli T, Prasado-Rao D S, Battese G E. 1998. AnIntroductionto Efficiency and Productivity Analysis.Kluwer Academic Publishers, Boston.Dabrowska-Zielinska K, Kogan F, Ciolkosz A,Gruszczynska M, Kowalik W. 2002. Modelling of cropgrowth conditions and crop yield in Poland usingAVHRR-based indices. International Journal ofRemote Sensing, 23, 1109-1123[6]Fan J L, Wu B F. 2004a. A methodology for retrievingcropping index from NDVI profile. Journal of RemoteSensing, 8, 628-636[7](in Chinese)Fan J L, Wu B F. 2004b. A study on cropping index potentialbased on GIS. Journal of Remote Sensing, 8, 637-644(in Chinese)[8]FAO. 1994. AEZ in Asia. World Soil Resources Report 75.FAO, Rome, Italy.FAO. 1996. Agro-Ecological Zoning Guidelines. FAO,Rome, Italy.George C S L, Samuel P S H, 2003. China’s land resourcesand land-use change: insights from the 1996 landsurvey. Land Use Policy, 20, 87-107[9]Hayami Y, Ruttan V. 1985. Agricultural Development: AnInternational Perspective. Johns Hopkins Press,Baltimore, USA.Liu J Y, Zhan J Y, Deng X Z. 2005. Spatio-temporal patternsand driving forces of urban land expansion in Chinaduring the economic reform era. AMBIO, 34, 450-455[10]Liu J Y, Zhang Z X, Xu X L, Kuang W H, Zhou W C, ZhangS W, Li R D, Yan C Z, Yu D S, Wu S X, et al. 2010. Spatialpatterns and driving forces of land use change in Chinaduring the early 21st century. Journal of GeographicalSciences, 20, 483-494[11]Liu X H. 1982. Farming System. China Agriculture Press,Beijing, China. (in Chinese)[12]Liu X H, Gao W, Chen F, Hu Y. 2005. Science of FarmingSystem. China Agricultural University Press, Beijing,China. (in Chinese)[13]Jonsson P, Eklundh L. 2002. Seasonality extraction byfunction fitting to time-series of satellite sensor data.IEEE Transactions on Geoscience and Remote Sensing,40, 1824-1832[14]Keys E, McConnell W J. 2005. Global change and theintensification of agriculture in the tropics. GlobalEnvironmental Change, 15, 320-337[15]Ramankutty N, Foley J A. 1999. Estimating historicalchanges in global land cover Croplands from 1700 to1992. Global Ecology and Biogeography, 13, 997-1027[16]Sakamoto T, Yokozawa M, Toritani H, Shibayama M,Ishitsuka N, Ohno H. 2005. A crop phenology detectionmethod using time-series MODIS data. Remote Sensingof Environment, 96, 366-374[17]Simonneaux V, Duchemin B, Helson D, Er-Raki S, Olioso A,Chehbouni A G. 2008. The use of high-resolution imagetime series for crop classification and evapotranspirationestimate over an irrigated area in central Morocco.International Journal of Remote Sensing, 29, 95-116[18]Stehfest E, Heistermann M, Priess J A, Ojima D S, AlcamoJ. 2007. Simulation of global crop production with theecosystem model DayCent. Ecological Modeling, 209,203-219[19]Tilman D. 1999. Global environmental impacts of agriculturalexpansion: the need for sustainable and efficientpractices. Proceedings of the National Academy ofSciences of the United States of America, 96, 5995-6000[20]Turner II B L, Doolittle W E. 1978. The concept and measureof agricultural intensity. Professional Geographer, 30,297-301[21]Turner II B L, Hanham R Q, Portararo A V. 1977. Populationpressure and agricultural intensity. Annals of theAssociation of American Geographers, 67, 384-396[22]Verburg P H, Chen Y Q, Veldkamp A. 2000, Spatialexplorations of land use change and grain productionin China. Agriculture Ecosystems and Environment,82, 333-354[23]Xiao X M, Boles S B, Frolking S, Li C S, Babu J Y, Salas W,Moore B. 2006. Mapping paddy rice agriculture in Southand Southeast Asia using multi-temporal MODISimages. Remote Sensing of Environment, 100, 95-113[24]Yan H M, Cao M K, Liu J Y, Zhuang D F, Guo J K, Liu M L,2005. Characterizing spatial patterns of multiplecropping system in China from multi-temporal remotesensing images. Transactions of the Chinese Societyof Agricultural Engineering, 21, 85-90[25](in Chinese)Zhang X Y, Friedl M A, Schaaf C B, Strahler A H, Hodges JC F, Gao F, Reed B C, Huete A. 2003. Monitoringvegetation phenology using MODIS. Remote Sensingof Environment, 84, 471-475[26](in Chinese)Zuo L J, Dong T T, Wang X, Zhao X L, Yi L. 2009. Multiplecroppingindex of Northern China based on MODIS/EVI. Transactions of the Chinese Society of AgriculturalEngineering, 25, 141-146. (in Chinese) |
| No Suggested Reading articles found! |
|
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
| |
Shared |
|
|
|
|
| |
Discussed |
|
|
|
|
