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The Improvement of the Agricultural Yields Forecasting Model Using the Software Product "œLand Viewer"
Corresponding Author(s) : Pavlо Kolodiy
Geomatics and Environmental Engineering,
Vol. 14 No. 1 (2020): Geomatics and Environmental Engineering
Abstract
Using the data of the remote sensing the Earth, new opportunities in assessing the state of agricultural crops and yield forecasting have been considered. In addition to the above-ground information, as shown by numerous studies conducted earlier, most parameters of the germination and development of agricultural crops can be restored and used from satellite images. Thanks to the software product "œLand Viewer", which enables pictures to be taken from Landsat 4, 5, 7, 8, Sentinel 2 and Terra satellites, and it will provide improving the model and assessment of the biomass potential of agricultural crops. The data obtained from remote sensing during the cropping season, show the in-formation on the condition of agricultural crops sown according to the vegetation stages (photosynthesis process) in crops. At various levels of development, in terms of the Normalized Difference Vegetation Index (NDVI), the seasonal pattern of crops photosynthesis is well reflected, which is associated with the above-ground biomass. The results have been presented in the current model of crop yield forecasting. The improved forecasting model enables significant increases in the economic efficiency of the research, and ensure the accuracy of the data on the physiological processes of agricultural crops, yields, and efficiency of obtaining the data on the research object.
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- Jensen J.R.: Remote Sensing of the Environment: An Earth Resource Perspective. 2nd ed. Prentice-Hall, Upper Saddle River 2007.
- Kolodiy P, Pіdlypna М.: The Research of the Agricultural Land Condition Based on Landsat 8 and Sentinel‑2 Satellites Data Mergers. [in:] Adamczyk T., Dębińska E. (Eds.), Geographic Information Systems Conference and Exhibition “GIS ODYSSEY 2017”, 4th to 8th of September 2017, Trento – Vattaro, Italy: Conference proceedings, Croatian Information Society – GIS Forum, Zagreb, pp. 191–195, http://www.gis.us.edu.pl/index.php?option=com_mtree&task=att_download&link_id=744&cf_id=24 [access: 29.06.2019]
- EOS – Earth Observing System, https://eos.com/blog/6-spectral-indexes-on-top-of-ndvi-to-make-your-vegetation-analysis-complete/ [access: 7.07.2019].
- Pіdlypna М., Kolodiy P.: Improvement of Prediction Models Crop Yields in Software Products Land Viewer [Усовершенствование модели прогнозирования урожайности сельскохозяйственных культур в программном продукте Land Viewer ]. International collection of scientific papers of the Global International Scientific Analytical Project participants, 2017: http://gisap.eu/node/134508 [access: 29.06.2019]
- EOS – Earth Observing System, https://eos.com/landviewer/?lat=49.32456&lng=28.78075&z=12&datasets=4&id=S2A_tile_20170605_35UPQ_0&b=SWIR1,Red8,Blue&anti [access: 7.07.2018].
- Pettorelli N.: The Normalized Difference Vegetation Index. Oxford University Press, New York 2013. https://www.researchgate.net/publication/233408135_The_Normalized_Difference_Vegetation_Index_NDVI_Unforeseen_successes_in_animal_ecology [access: 23.06.2019].
- EOS – Earth Observing System, https://eos.com/landviewer/?lat=49.32456& lng=28.78075&z=12&datasets=4&id=S2B_tile_20180705_35UPQ_0&b=SWIR1,Red8,Blue&anti [access: 7.07.2018].
- Gitelson A.A., Kaufman Y.J., Merzlyak M.N.: Use of a green channel in remote sensing of global vegetation from EOS. Remote Sensing of Environment, vol. 58, issue 3, 1996, pp. 289–298.
- EOS – Earth Observing System, https://eos.com/landviewer/?lat=49.32456&lng=28.78075&z=12&datasets=4&id=S2A_tile_20190824_35UPQ_0&b=SWIR1,Red8,Blue&anti [access: 7.07.2018].
- Vinnitsa Regional State Administration – News of RDA [Вінницька облас- на державна адміністрація – Новини РДА], http://www.vin.gov.ua/news/novyny-rda [access: 7.07.2018].
References
Jensen J.R.: Remote Sensing of the Environment: An Earth Resource Perspective. 2nd ed. Prentice-Hall, Upper Saddle River 2007.
Kolodiy P, Pіdlypna М.: The Research of the Agricultural Land Condition Based on Landsat 8 and Sentinel‑2 Satellites Data Mergers. [in:] Adamczyk T., Dębińska E. (Eds.), Geographic Information Systems Conference and Exhibition “GIS ODYSSEY 2017”, 4th to 8th of September 2017, Trento – Vattaro, Italy: Conference proceedings, Croatian Information Society – GIS Forum, Zagreb, pp. 191–195, http://www.gis.us.edu.pl/index.php?option=com_mtree&task=att_download&link_id=744&cf_id=24 [access: 29.06.2019]
EOS – Earth Observing System, https://eos.com/blog/6-spectral-indexes-on-top-of-ndvi-to-make-your-vegetation-analysis-complete/ [access: 7.07.2019].
Pіdlypna М., Kolodiy P.: Improvement of Prediction Models Crop Yields in Software Products Land Viewer [Усовершенствование модели прогнозирования урожайности сельскохозяйственных культур в программном продукте Land Viewer ]. International collection of scientific papers of the Global International Scientific Analytical Project participants, 2017: http://gisap.eu/node/134508 [access: 29.06.2019]
EOS – Earth Observing System, https://eos.com/landviewer/?lat=49.32456&lng=28.78075&z=12&datasets=4&id=S2A_tile_20170605_35UPQ_0&b=SWIR1,Red8,Blue&anti [access: 7.07.2018].
Pettorelli N.: The Normalized Difference Vegetation Index. Oxford University Press, New York 2013. https://www.researchgate.net/publication/233408135_The_Normalized_Difference_Vegetation_Index_NDVI_Unforeseen_successes_in_animal_ecology [access: 23.06.2019].
EOS – Earth Observing System, https://eos.com/landviewer/?lat=49.32456& lng=28.78075&z=12&datasets=4&id=S2B_tile_20180705_35UPQ_0&b=SWIR1,Red8,Blue&anti [access: 7.07.2018].
Gitelson A.A., Kaufman Y.J., Merzlyak M.N.: Use of a green channel in remote sensing of global vegetation from EOS. Remote Sensing of Environment, vol. 58, issue 3, 1996, pp. 289–298.
EOS – Earth Observing System, https://eos.com/landviewer/?lat=49.32456&lng=28.78075&z=12&datasets=4&id=S2A_tile_20190824_35UPQ_0&b=SWIR1,Red8,Blue&anti [access: 7.07.2018].
Vinnitsa Regional State Administration – News of RDA [Вінницька облас- на державна адміністрація – Новини РДА], http://www.vin.gov.ua/news/novyny-rda [access: 7.07.2018].