Application of vegetation indexes derived from satellite images IRS–1D LISS–III for determination of crop status

1Kokhan, SS
1National University of Life and Environmental Sciences of Ukraine, Kyiv, Ukraine
Kosm. nauka tehnol. 2011, 17 ;(5):58-63
https://doi.org/10.15407/knit2011.05.058
Publication Language: Ukrainian
Abstract: 
A scale for the determination of crop density is developed on the basis of normalized vegetation index value derived from the series of satellite images IRS-1D LISS-III for the spring and summer season and with the use of ground data.
Keywords: crop status, satellite images, vegetation index
References: 
1. Babych S. M. Methodological aspects of analytical opratsyu tion information in aerospace monitoring crops. In: Systemni doslidzhennja ta modeljuvannja v zemlerobstvi, 410 p. (Nyva, Kyiv, 1998) [in Ukrainian].
2. Zholobak G. M., Sakhatsky O. I. Calibration data in problems of nature-related crops. In: Multispectral remote sensing in nature management, Ed.by V.I. Lyalko, M.O. Popov, 262— 268 (Nauk.dumka, Kyiv, 2006) [in Ukrainian].
3. Lyalko V. I., Sakhatsky O. I., Zholobak G. M. Features forecasting yields for many crops spectral remote sensing data. In: Multispectral remote sensing in nature management, Ed.by V.I. Lyalko, M.O. Popov, 176— 191 (Nauk.dumka, Kyiv, 2006) [in Ukrainian].
4. Chavez P. S. An improved dark-object subtraction technique for atmospheric scattering correction of multispectral data. Remote Sens. Environ., 24, 459—479 (1988).
https://doi.org/10.1016/0034-4257(88)90019-3
5. Chavez P. S. Radiometric calibration of Landsat Thematic Mapper multispectral images. Photogrammetric Engineering and Remote Sensing, 55 (9), 1285—1294 (1989).
6. Fritz S., et al. The use of MODIS data to derive acreage estimations for larger fields: A case–study in the south– western Rostov region of Russia. Int. J. Appl. Earth Obs. Geoinf., 10, 453—466 (2008).
https://doi.org/10.1016/j.jag.2007.12.004
7. Martinez-Casasnovas J. A., et al. Mapping multi-year cropping patterns in small irrigation districts from time–series analysis of Landsat TM images. Eur. J. Agron., 23, 159—169 (2005).
https://doi.org/10.1016/j.eja.2004.11.004

8. Turker M., Arikan M. Sequential masking classification of multi-temporal Landsat 7 ETM+ images for field-based crop mapping in Karacabey, Turkey. Int. J. Remote Sens., 26, 3813—3830 (2005).
https://doi.org/10.1080/01431160500166391