Land cover classification in Ukrainian Carpathians using the MERIS terrestrial chlorophyl index and red edge position from envisat MERIS data

Рубрика: 
Study of the Earth from Space
1Lyalko, VI, 1Shportiuk, ZM, 1Sakhatsky, OI, 1Sibirtseva, ОN
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
Kosm. nauka tehnol. 2006, 12 ;(5-6):010-014
https://doi.org/10.15407/knit2006.05.010
Язык публикации: Ukrainian
Аннотация: 
We present some results of a preliminary study of the possibility to use MERIS data for land cover classification in the Ukrainian Carpathians. The ENVISAT MERIS data (16 April 2004) with a rough space resolution of 1200 m are used to calculate the red edge indices: the Red Edge Position (REP), MERIS Terrestrial Chlorophyll Index (MTCI) and NDVI. The classification using REP and MTCI images gives better results that with reflectance by the method of minimum distance to means (MMDM). The calculation results showed that the MERIS image with a rough space resolution provided moderate classification results: only coniferous forests and snow are well classified. MTCI is sensitive to a broad range of the chlorophyll contents and much less sensitive to topographical effect in mountain region. The investigation results show a good correlation between REP and MTCI and a high potential for monitoring for the ecosystems in mountain regions using a combination of both indices.
Ключевые слова: chlorophyl index, data, red edge
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References: 
1. Lyalko V. I., Shportyuk Z. M., Sakhatskyi O. I., et al. Investigation of forest condition using the position of the red edge according to the MERIS video spectrometer. In: 5th Ukrainian Conference on Space Research: Abstracts, NCUIKS, Evpatoria, September 4—11, 2005, 137 (Institute of Space Researches NANU-NKAU, Kyiv, 2005) [in Ukrainian].
2. Shportyuk Z. M., Lyalko V. I., Pjanilo Ya. D., et al. Spectral methods of processing and analysing of information in remote sensing of vegetation: Preprint No. 4-93, Pidstrigach Research center of mathematical modeling of NAS of Ukraine, 54 p. (Lviv, 1993) [in Ukrainian].
3. Baret F., Jacquemoud S., Guyot G., et al. Modeled analysis of the biophysical nature of spectral shift and comparison with information content of broad bands. Remote Sens. Environ., 41 (2), 133—142 (1992).
4. Clevers J. G. P. W., Bartholomeus H., Muecher C. A., et al. Land covers classification with the Medium Resolution Imaging Spectrometer (MERIS). In: Oluic M. (Ed.) New Strategies for European Remote Sensing, 687—694 (Millpress, Rotterdam, 2005).
5. Collins W., Chang S. H., Raines G., et. al. Airborne Biogeophysical Mapping of Hidden Mineral Deposits. Economic. Geol., 78 (4), 737—749 (1983).
6. Dash J., Curran P. J. The MERIS terrestrial chlorophyll index. Int. J. Remote Sens., 25, 5403— 5413 (2004).
7. Dawson J., Curran P. J. A new technique for interpolating the reflectance red edge position. Int. J. Remote Sens., 19, 2133—2139 (1998).