Journal of Geographical Sciences

, Volume 22, Issue 4, pp 653–668 | Cite as

Changes in rice cropping systems in the Poyang Lake Region, China during 2004–2010

  • Peng Li
  • Zhiming Feng
  • Luguang Jiang
  • Yujie Liu
  • Xiangming Xiao


Rice cropping systems not only characterize comprehensive utilization intensity of agricultural resources but also serve as the basis to enhance the provision services of agro-ecosystems. Yet, it is always affected by external factors, like agricultural policies. Since 2004, seven consecutive No.1 Central Documents issued by the Central Government have focused on agricultural development in China. So far, few studies have investigated the effects of these policies on the rice cropping systems. In this study, based upon the long-term field survey information on paddy rice fields, we proposed a method to discriminate the rice cropping systems with Landsat data and quantified the spatial variations of rice cropping systems in the Poyang Lake Region (PLR), China. The results revealed that: (1) from 2004 to 2010, the decrement of paddy rice field was 46.76 km2 due to the land use change. (2) The temporal dynamics of NDVI derived from Landsat historical images could well characterize the temporal development of paddy rice fields. NDVI curves of single cropping rice fields showed one peak, while NDVI curves of double cropping rice fields displayed two peaks annually. NDVI of fallow field fluctuated between 0.15 and 0.40. NDVI of the flooded field during the transplanting period was relatively low, about 0.20±0.05, while NDVI during the period of panicle initiation to heading reached the highest level (above 0.80). Then, several temporal windows were determined based upon the NDVI variations of different rice cropping systems. (3) With the spatial pattern of paddy rice field and the NDVI threshold within optimum temporal windows, the spatial variation of rice cropping systems was very obvious, with an increased multiple cropping index of rice about 20.2% from 2004 to 2010. The result indicates that agricultural policies have greatly enhanced the food provision services in the PLR, China.


rice cropping systems NDVI temporal windows threshold method Landsat the Poyang Lake region (PLR) 


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  1. Bouvet A, Le Toan T, Lam-Dao N, 2009. Monitoring of the rice cropping system in the Mekong Delta using ENVISAT/ASAR dual polarization data. IEEE Transactions on Geoscience and Remote Sensing, 47(2): 517–526.CrossRefGoogle Scholar
  2. Ding Y, 1961. Cultivation of rice in China. Beijing: China Agriculture Press. (in Chinese)Google Scholar
  3. Dobermann A, Witt C, Dawe D et al., 2002. Site-specific nutrient management for intensive rice cropping systems in Asia. Field Crops Research, 74(1): 37–66.CrossRefGoogle Scholar
  4. FAOSTAT, 2009. Statistical Database of the Food and Agricultural Organization of the United Nations. Rome.Google Scholar
  5. Gilbert M, Xiao X M, Chaitaweesub P et al., 2007. Avian influenza, domestic ducks and rice agriculture in Thailand. Agriculture, Ecosystems & Environment, 119(3/4): 409–415.CrossRefGoogle Scholar
  6. Heerink N, Qu F, Kuiper M et al., 2007. Policy reforms, rice production and sustainable land use in China: A macro-micro analysis. Agricultural Systems, 94(3): 784–800.CrossRefGoogle Scholar
  7. Huang Y, Sass R L, Fisher J et al., 1998. Model estimates of methane emission from irrigated rice cultivation of China. Global Change Biology, 4(8): 809–821.CrossRefGoogle Scholar
  8. Li D, Liu M, Cheng Y et al., 2011. Methane emissions from double-rice cropping system under conventional and no tillage in southeast China. Soil and Tillage Research, 113(2): 77–81.CrossRefGoogle Scholar
  9. Li P, Jiang L, Feng Z et al., 2011. Spatial pattern of food provision in Poyang Lake Region, China. Journal of Natural Resources, 26(2): 190–200. (in Chinese)Google Scholar
  10. Liew S C, Kam S P, Tuong T P et al., 1998. Application of multitemporal ERS-2 synthetic aperture radar in delineating rice cropping systems in the Mekong River Delta, Vietnam. IEEE Transactions on Geoscience and Remote Sensing, 36(5): 1412–1420.CrossRefGoogle Scholar
  11. Liu J Y, Liu M L, Tian H Q et al., 2005. Spatial and temporal patterns of China’s cropland during 1990–2000: An analysis based on Landsat TM data. Remote Sensing of Environment, 98(4): 442–456.CrossRefGoogle Scholar
  12. Martin V, Pfeiffer D U, Zhou X et al., 2011. Spatial Distribution and Risk Factors of Highly Pathogenic Avian Influenza (HPAI) H5N1 in China. PLoS pathogens, 7(3): e1001308. doi:10.1371/journal.ppat.1001308.CrossRefGoogle Scholar
  13. National Development and Reform Commission (NDRC), 2009. National plan for expansion of grain production capacity by 50 billion kilograms during 2009–2020. Beijing.
  14. Peng D, Huete A R, Huang J et al., 2010. Detection and estimation of mixed paddy rice cropping patterns with MODIS data. International Journal of Applied Earth Observation and Geoinformation, 13(1): 13–23.CrossRefGoogle Scholar
  15. Sakamoto T, Van Nguyen N, Ohno H et al., 2006. Spatio-temporal distribution of rice phenology and cropping systems in the Mekong Delta with special reference to the seasonal water flow of the Mekong and Bassac rivers. Remote Sensing of Environment, 100(1): 1–16.CrossRefGoogle Scholar
  16. Sakamoto T, Van Phung C, Kotera A et al., 2009. Analysis of rapid expansion of inland aquaculture and triple rice-cropping areas in a coastal area of the Vietnamese Mekong Delta using MODIS time-series imagery. Landscape and Urban Planning, 92(1): 34–46.CrossRefGoogle Scholar
  17. Silva L M M, Rodrigues C D F, 2001. New development in rice cropping systems and its effects on yield: A short appointment of the Portuguese situation. In: Chataigner J (ed.). Workshop on the New Development in Rice Agronomy and Its Effects on Yield and Quality in Mediterranean Areas, Montpellier: CIHEAM-IAMM, 1–5.Google Scholar
  18. Tong C, Hall C A S, Wang H, 2003. Land use change in rice, wheat and maize production in China (1961–1998). Agriculture, Ecosystems & Environment, 95(2/3): 523–536.CrossRefGoogle Scholar
  19. Torbick N, Salas W, Hagen S et al., 2011a. Monitoring rice agriculture in the Sacramento Valley, USA, with multi-temporal PALSAR and MODIS imagery. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS), 4(2): 451–457.CrossRefGoogle Scholar
  20. Torbick N, Salas W, Xiao X et al., 2011b. Integrating SAR and optical imagery for regional mapping of paddy rice attributes in the Poyang Lake watershed, China. Canadian Journal of Remote Sensing, 37(1): 17–26.CrossRefGoogle Scholar
  21. Tucker C J, 1979. Red and photographic infrared linear combinations for monitoring vegetation. Remote Sensing of Environment, 8(2): 127–150.CrossRefGoogle Scholar
  22. Van Niel T G, McVicar T R, 2003. A simple method to improve field-level rice identification: Toward operational monitoring with satellite remote sensing. Australian Journal of Experimental Agriculture, 43(4): 379–387.CrossRefGoogle Scholar
  23. Van Niel T G, McVicar T R, 2004. Determining temporal windows for crop discrimination with remote sensing: A case study in south-eastern Australia. Computers and Electronics in Agriculture, 45(1–3): 91–108.CrossRefGoogle Scholar
  24. Xiao X, Boles S, Frolking S et al., 2002a. Observation of flooding and rice transplanting of paddy rice fields at the site to landscape scales in China using VEGETATION sensor data. International Journal of Remote Sensing, 23(15): 3009–3022.CrossRefGoogle Scholar
  25. Xiao X, Boles S, Frolking S et al., 2002b. Landscape-scale characterization of cropland in China using VEGETATION sensor data and Landsat TM imagery. International Journal of Remote Sensing, 23(18): 3579–3594.CrossRefGoogle Scholar
  26. Xiao X, Boles S, Frolking S et al., 2006. Mapping paddy rice agriculture in South and Southeast Asia using multi-temporal MODIS images. Remote Sensing of Environment, 100(1): 95–113.CrossRefGoogle Scholar
  27. Xiao X, Boles S, Liu J et al., 2005. Mapping paddy rice agriculture in southern China using multi-temporal MODIS images. Remote Sensing of Environment, 95(4): 480–492.CrossRefGoogle Scholar
  28. Xiao X, He L, Salas W et al., 2002. Quantitative relationships between field-measured leaf area index of paddy rice fields and VEGETATION-sensor-derived vegetation index at the farm scale. International Journal of Remote Sensing, 23(18): 3595–3604.CrossRefGoogle Scholar
  29. Yang H, Li X B, 2000. Cultivated land and food supply in China. Land Use Policy, 17(2): 73–88.CrossRefGoogle Scholar
  30. Yu J, Zhang W, Wang D, 2011. The temporal and spatial evaluation on China’s agricultural policy output since 1978. Journal of Geographical Sciences, 21(3): 475–488.CrossRefGoogle Scholar
  31. Zhang J, Feng Z M, Yang Y Z, 2006. Current grain yield reduction at different spatial scales in China. Resources Science, 28(6): 28–32. (in Chinese)Google Scholar

Copyright information

© Science China Press and Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Peng Li
    • 1
    • 2
  • Zhiming Feng
    • 1
  • Luguang Jiang
    • 1
  • Yujie Liu
    • 1
  • Xiangming Xiao
    • 3
  1. 1.Institute of Geographic Sciences and Natural Resources ResearchCASBeijingChina
  2. 2.Graduate University of Chinese Academy of SciencesBeijingChina
  3. 3.Department of Botany and Microbiology, Center for Spatial AnalysisUniversity of OklahomaNormanUSA

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