Possibilities for the prognostication of the productivity of cereals from multizonal AVHRR, NOAA, and Landsat TM images (by the example of the Kyiv Region)

1Lyalko, VI, 1Sakhatsky, AI, 1Khodorovsky, AYa., 1Zholobak, GM, 1Buyanova, IYa.
1State institution «Scientific Centre for Aerospace Research of the Earth of the Institute of Geological Sciences of the National Academy of Sciences of Ukraine», Kyiv, Ukraine
Косм. наука технол. 2002, 8 ;(2-3):249-254
Язык публикации: Русский
Аннотация: 
Отсутствует
Ключевые слова: дистанционное зондирование Земли
References: 
1. Bochenek Z. Operational use of NOAA data for crop condition assessment in Poland. In: Proc. of the 19th EARSeL Symposium on Remote Sensing in the 21 st Century, Valladolid, Spain, 31 May— 2 June 1999, 387—392 (2000).
2. Bullok P. R. Operational estimates of Western Canada grain production using NOAA AVHRR LAC data. Canadian Journal of Remote Sensing, 18 (1), 23—25 (1992).
3. Illera P., Delgado J. A., Fernández Unzueta A., Fernández Manso A. A. Integration of NOAA-AVHRR and meteorological data in a CIS-Application for vegetation monitoring in Castilla y Leon, Spain. In: Proc. of the 19th EARSeL Symposium on Remote Sensing in the 21 st Century, Valladolid, Spain, 31 May— 2 June 1999, 47—54 (2000).
4. Kumar K., and Monteith G. L. Remote sensing of Crop Growth. In: Smith H. (Ed) Plants and the Daylight Spectrum, 133—144 (Academic Press, London, 1981).
5. Prince S. D. A model of regional primary production for use with coarse resolution satellite data. Int. J. of Remote sensing, 6, 1313—1330 (1991).
6. Rasmussen M. S. Assessment of millet yield and production in northern Burkina Faso using integrated NDVI from the AVHRR. Int. J. of Remote sensing, 18, 3431—3442 (1992).
7. Rasmussen M. S. Operational yield forecast using AVHRR NDVI data reduction of environmental and inter annual variability. Int. J. of Remote sensing, 18, 1059—1077 (1997).
8. Rasmussen M. S. Developing simple, operational, consistent NDVI-vegetation models by applying environmental and climatic information: Part 1. Assessment of net primary production. Int. J. of Remote sensing, 19, 97—117 (1998).
9. Rasmussen M. S. Developing simple, operational, consistent NDVI — vegetation models by applying environmental and climatic information. Part II: Crop yield assessment. Int. J. of Remote sensing, 19, 119—139 (1998).
10. Ruimy M. S., Saugier B. and Dedieu G. Methodology for the estimation of terrestrial net primary production from remotely-sensed data. J. Geophys. Res., 99 (D3), 5263— 5283 (1994).
11. Steven M. D., and Demetriades-Shah T. H. Spectral indices of crop productivity under condition of stress. In: Advances in Digital Image Processing, Int. J. of Remote Sensing Society, 18, 593—601; 3431—3442 (Nottingham, 1987).