Forecast of Yield of Major Crops in Ukraine in War Conditions 2022 Based on MODIS and Sentinel-2 Satellite Data

Nataliia Kussul, Sophia Drozd and Hanna Yailymova

References:

1. Svit perebuvaie na pochatku prodovolchoi kryzy, abo yakyi vrozhai vanhuie NASA Harvest Ukraini [The globe is at the beginning of food crisis or what yield NASA Harvest forecasts for Ukraine], 2022, [Online]. Available: https://kurkul.com/ spetsproekty/1338-svit-perebuvaye-na-pochatkoviy-stadiyi-prodovolchoyi-krizi-yakiy-vrojay-vanguye-nasa-harvest-ukrayini.
2. D. Rawtani, G. Gupta, N. Khatri, P. K. Rao, and C. M. Hussain, “Environmental damages due to war in Ukraine: A perspective,” Sci. Total Environ., vol. 850, no. 157932, p. 157932, 2022, doi: 10.1016/j.scitotenv. 2022.157932.
3. A. Kolotii and et al., “Comparison of biophysical and satellite predictors for wheat yield forecasting in Ukraine,” The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. XL-7/W3, pp. 39-44, 2015, doi: 10.5194/isprsarchives-xl-7-w3-39-2015.
4. F. Kogan and et al., “Winter wheat yield forecasting: A comparative analysis of results of regression and biophysical models,” J. Autom. Inf. Sci., vol. 45, no. 6, pp. 68-81, 2013, doi: 10.1615/JAutomat InfScien.v45.i6.70.
5. F. Kogan and et al., “Winter wheat yield forecasting in Ukraine based on Earth observation, meteorological data and biophysical models,” Int. J. Appl. Earth Obs. Geoinf., vol. 23, pp. 192–203, 2013, doi: 10.1016/j.jag.2013.01.002.
6. M. E. Holzman and R. E. Rivas, “Early maize yield forecasting from remotely sensed temperature/ vegetation index measurements,” IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., vol. 9, no. 1, pp. 507-519, 2016, doi: 10.1109/JSTARS.2015. 2504262.
7. T. Ben Hassen and H. El Bilali, “Impacts of the Russia-Ukraine war on global food security: Towards more sustainable and resilient food systems?,” Foods, vol. 11, no. 15, p. 2301, 2022, doi: 10.3390/foods 11152301.
8. S. Skakun and et al., “Winter wheat yield assessment from Landsat 8 and Sentinel-2 data: Incorporating surface reflectance, through phenological fitting, into regression yield models,” Remote Sens. (Basel), vol. 11, no. 15, p. 1768, 2019, doi: 10.3390/ rs11151768.
9. S. Skakun and et al., “Winter wheat yield assessment using Landsat 8 and sentinel-2 data,” in IGARSS 2018 - IEEE International Geoscience and Remote Sensing Symposium, 2018, doi: 10.1109/IGARSS.2018. 8519134.
10. S. Skakun, E. Vermote, J.-C. Roger, and B. Franch, “Combined use of Landsat-8 and sentinel-2A images for winter crop mapping and winter wheat yield assessment at regional scale,” AIMS Geosci., vol. 3, no. 2, pp. 163-186, 2017, doi: 10.3934/geosci. 2017.2.163.
11. I. Becker-Reshef, E. Vermote, M. Lindeman, and C. Justice, “A generalized regression-based model for forecasting winter wheat yields in Kansas and Ukraine using MODIS data,” Remote Sens. Environ., vol. 114, no. 6, pp. 1312-1323, 2010, doi: 10.1016/j.rse.2010. 01.010.
12. O. Kussul, N. Kussul, S. Skakun, and et al., “Assessment of relative efficiency of using MODIS data to winter wheat yield forecasting in Ukraine,” 2013 IEEE International Geoscience and Remote Sensing Symposium, 2013, doi: 10.1109/IGARSS. 2013. 6723516.
13. A. Shelestov, M. Lavreniuk, V. Vasiliev, and et al., “Cloud approach to automated crop classification using Sentinel-1 imagery,” IEEE Transactions on Big Data, 2019, vol. 6. no. 3, pp. 572-582, doi: 10.1109/TBDATA.2019.2940237.
14. N. Kussul, L. Mykola, A. Shelestov, and S. Skakun, “Crop inventory at regional scale in Ukraine: Developing in season and end of season crop maps with multi-temporal optical and SAR satellite imagery,” European Journal of Remote Sensing, vol. 51(1), pp. 627-636, doi: 10.1080/22797254.2018. 1454265.