An integrated crop condition monitoring system with remote sensing

Transactions of the ASABE

Volumn 53, Issue 3, 2010, Pages 971-979

  Wang, B F ^a   Meng, J H ^a   Li, Q Z ^a  

^a INSTITUTE OF REMOTE SENSING APPLICATIONS   (China)

Author keywords

Crop growth profile monitoring; Instantaneous monitoring; Integrated crop condition monitoring system; Remote sensing

Indexed keywords

CHINESE GOVERNMENT; CROP CONDITION; CROP GROWTH; DIFFERENCE IMAGES; ENVIRONMENTAL CONDITIONS; GROWING SEASON; INSTANTANEOUS MONITORING; MARKET VOLATILITY; MONITORING METHODS; NORMALIZED DIFFERENCE VEGETATION INDEX; OPERATIONAL SYSTEMS; PREVIOUS YEAR; PROFILE MONITORING; SPATIAL DISTRIBUTION; SPATIAL VARIATIONS; SPECIFIC TIME; TEMPORAL VARIATION;

CROPS; CULTIVATION; DAMPING; DECISION MAKING; PROCESS CONTROL; PROCESS MONITORING; REMOTE SENSING; SIZE DISTRIBUTION; VEGETATION;

CONDITION MONITORING;

CROP PRODUCTION; ENVIRONMENTAL CONDITIONS; FOOD SAFETY; GROWING SEASON; GROWTH RATE; NDVI; REMOTE SENSING; SPATIAL DISTRIBUTION; SPATIAL VARIATION; TEMPORAL VARIATION;

CHINA;

EID: 77954140813     PISSN: 21510032     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (32)

1. Badhwar, G. D. 1980. Crop emergence date determination from spectral data. Photogram. Eng. and Remote Sensing 46: 369-377.
2. Bauer, M. E. 1985. Spectral inputs to crop identification and condition assessment. Proc. IEEE 73(6):1071-1085.
3. Crist, E. P., and W. A. Malila. 1980. Temporal-spectral analysis of technique of vegetation applications of Landsat. In Proc. 14th Intl. Symp. on Remote Sensing of Environment, 1031-1041. Tucson, Ariz.: International Center for Remote Sensing of Environment.
4. Doraiswamy, P. C., J. L. Hatfield, T. J. Jackson, B. Akhmedov, J. Prueger, and A. Stern. 2004. Crop condition and yield simulations using Landsat and MODIS. Remote Sensing Environ. 92(4):548-559.
5. Genovese, G., C. Vignolles, and T. Negre. 2001. A methodology for a combined use of normalized difference vegetation index and CORINE land cover data for crop yield monitoring and forecasting: A case study on Spain. Agronomie 21(1):91-111.
6. Hielkema, J. U., and F. L. Snijders. 1994. Operational use of environmental satellite remote sensing and satellite communications technology for global food security and locust control by FAO: The ARTEMIS and DIANA systems. Acta Astronautica 32(9):603-616.
7. Jackson, R. D., and A. R. Huete. 1991. Interpreting vegetation indices. Prev. Vet. Med. 11 (3-4) : 185-200.
8. Joint Agricultural Weather Facility and USDA. 2005. Major World Crop Areas and Climatic Profiles. Honolulu, Hawaii: University Press of the Pacific.
9. Kastens, J. H., T. L. Kastens, D. L. A. Kastens, K. P. Price, E. A. Martinko, and R. Lee. 2005. Image masking for crop yield forecasting using AVHRR NDVI time series imagery. Remote Sensing Environ. 99(3):341-356.
10. Liu, C. L., and B. F. Wu. 2004. Application of cloud detection algorithm for the advanced very-high resolution radiometer. Chinese J. Remote Sensing 8(6):677-687.
11. Liu, J., M. Liu, H. Tian, D. Zhuang, Z. Zhang, W. Zhang, X. Tang, and X. Deng. 2005. Spatial and temporal patterns of China's cropland during 1990-2000: An analysis based on Landsat TM data. Remote Sensing Environ. 98(4):442-456.
12. Macdonald, R. B., and F. G. Hall. 1980. Global crop forecasting. Science 208(4445):670-679.
13. McNairn, H., and R. J. Brown. 1999. Remote sensing in support of crop management. In Seminars of the United Nations Programme on Space Applications, 49. New York, N. Y.: United Nations.
14. Meng, J. H., and B. F. Wu. 2008. Study on the crop condition monitoring methods with remote sensing. Intl. Archives Photogram., Remote Sensing, and Spatial Info. Sci. (Beijing, China) 37 (part B 8) : 945-950.
15. Meng, J. H., B. F. Wu, Q. Z. Li, X. Du, and K. Jia. 2009. Monitoring crop phenology with MERIS data: A case study of winter wheat in North China Plain. In Proc. Progress in Electromagnetics Research Symposium, 1225-1228. Beijing, China.
16. Mkhabela, M. S., M. S. Mkhabela, and N. N. Mashinini. 2005. Early maize yield forecasting in the four agro-ecological regions of Swaziland using NDVI data derived from NOAA's-AVHRR. Agric. and Forest Meteorology 129 (1-2) : 1-9.
17. Neumann, K., M. Herold, A. Hartley, and C. Schmullius. 2007. Comparative assessment of CORINE 2000 and GLC2000: Spatial analysis of land cover data for Europe. Intl. J. Applied Earth Obs. and Geoinfo. 9(4):425-437.
18. Philipson, W. R., and W. L. Teng. 1998. Operational interpretation of AVHRR vegetation indices for world crop information. Photogram. Eng. and Remote Sensing 54(1):55-59.
19. Rahman, H., and G. Dedieu. 1994. SMAC: A simplified method for the atmospheric correction of satellite measurements in the solar spectrum. Intl. J. Remote Sensing 15(1):123-143.
20. Rao, M. V. K., R. S. Ayyangar, and P. P. N. Rao. 1982. Role of multispectral data in assessing crop management and crop yield. In Proc. Machine Processing of Remote Sensed Data Symposium. West Lafayette, Ind.: Purdue University.
21. Reichert, G. C., P. R. Nixon, and R. N. Dobbins. 2000. Statistics Canada's near real-time crop condition assessment program (CCAP) utilizing NOAA AVHRR data, remote sensing, GIS, and the internet. In Proc. Intl. Conf. on Agric. Statistics, n142-148. Washington, D. C.: USDA National Agricultural Statistics Service.
22. Ren, J., Z. Chen, Q. Zhou, and H. Tang. 2008. Regional yield estimation for winter wheat with MODIS-NDVI data in Shandong, China. Intl. J. Applied Earth Obs. and Geoinfo. 10(4):403-413.
23. Roerink, G. J., M. Menenti, and W. Verhoef. 2000. Reconstructing cloud-free NDVI composites using Fourier analysis of time series. Intl. J. Remote Sensing 21(9):1911-1917.
24. Schneider, S. R., D. F. McGinnis, and J. A. Gatlin. 1981. Use of NOAA AVHRR visible and near-infrared data for land remote sensing. NOAA Tech. Report NASS84. Washington, D. C.: USDA.
25. Vermote, E. F., D. Tanre, J. L. Deuze, M. Herman, and J. J. Morcrette. 1997. Second simulation of the satellite signal in the solar spectrum, 6S: An overview. IEEE Trans. Geosci. Remote Sensing 35(3):675-686.
26. Wiegand, C. L., A. J. Richardson, D. E. Escobar, and A. H. Gerbermann. 1991. Vegetation indices in crop assessments. Remote Sensing Environ. 35 (2-3) : 105-119.
27. Wu, B. F. 2000. China crop growth monitor and production estimate operational methods. Chinese J. Geography 55(1):25-35.
28. Wu, B. F. 2004. China crop watch system with remote sensing. Chinese J. Remote Sensing 8(6):481-497.
29. Wu, B. F., and C. L. Liu. 2000. Crop growth monitor system with coupling of NOAA and VGT data. In Proc. Vegetation 2000, 355-360. Lago Maggiore, Italy.
30. Wu, B. F., and C. L. Liu. 2004. 1-km AVHRR China land dataset. Chinese J. Remote Sensing 8(6):529-550.
31. Zhang, F., B. F. Wu, and C. L. Liu. 2003. An advanced tool for real-time crop monitoring in china. In Proc. IEEE Intl. Geosci. and Remote Sensing Symposium (IGARSS), IV: 2245-2247. Piscataway, N. J.: IEEE.
32. Zhang, F., B. F. Wu, C. L. Liu, Z. M. Luo, S. W. Zhang, and G. L. Zhang. 2004. A method to extract regional crop growth information with time series of NDVI data. Chinese J. Remote Sensing 8(6):515-528.