Analysis of dynamics for 15 vegetation indices based on Sentinel-2A image data for the test sites of winter wheat crop different on the state from each other within the forest-steep zone in Ukraine

  • Galina Zholobak Scientific Centre for Aerospace Research of the Earth Institute of Geological Science National Academy of Sciences of Ukraine, Kyiv, Ukraine
  • Oksana Sybirtseva Scientific Centre for Aerospace Research of the Earth Institute of Geological Science National Academy of Sciences of Ukraine, Kyiv, Ukraine
  • Mariana Vakolyuk Scientific Centre for Aerospace Research of the Earth Institute of Geological Science National Academy of Sciences of Ukraine, Kyiv, Ukraine
  • Inna Romanciuc Scientific Centre for Aerospace Research of the Earth Institute of Geological Science National Academy of Sciences of Ukraine, Kyiv, Ukraine
Keywords: vegetation indices, Sentinel-2А, winter wheat crop, total nitrogen content

Abstract

Dynamics of 15 vegetation indices estimated from the Sentinel-2A images within two test sites with the area of 1 ha for the production crops of two winter wheat cultivars (Bohdana and Skagen) are analyzed for winter dormancy and spring-early summer in 2016. The decrease of total nitrogen content in dry matter of the plant organs, which are formed the reflecting surface of the vegetation cover from the booting stage to milk one is consistent with the behavior of the Green NDVI (740, 560) for the both test sites of winter wheat cover. Dynamics of the other 14 indices have been analyzed under the conditions of the deterioration of phytosanitary situation for the winter wheat crop of Bohdana cultivar.

References

Zholobak, G. M., Sybirtseva, О. M., Vakolyuk, M. V., Zakharchyk, Yu. V. (2017) Remote monitoring of the state of winter wheat during the spring-summer vegetation of 2016 year, by using vegetatin indices of Sentinel-2A satellite (case study by forest-steppe area of Ukraine). Ukrainskyi zhurnal dystantsiinoho zonduvannia Zemli. 15. 23-30. (in Ukrainian). https://ujrs.org.ua/ujrs/article/view/115

Eroshenko, F.V., Eroshenko, A.A., Simatin, T.V. (2015) Ispol'zovanie azota rasteniyami ozimoj pshenicy // Dostizheniya nauki i tekhniki APK. v. 29. No 11. p. 58-61. (in Russian). http://agroapk.ru/68-archive/11-2015/1127-2015-11-18-ru

Romanciuc, I. F., Sakhatsky, A.I., Apostolov, A. A. (2018) The estimation of soil humidity by the satellite Sentinel-2 imageries (object of study is the Baryshivs'kyi district of the Kiev region). Dopov. Nac. akad. nauk Ukr. 1:60-66 (in Ukrainian). https://doi.org/10.15407/dopovidi2018.01.060

Spirina, V. Z. (2014) Agrohimicheskie metody issledovaniya pochv, rastenij i udobrenij: ucheb. posobie / V. Z. Spirina, T. P Solov'eva. - Tomsk: Izdatel'skij Dom Tomskogo gosudarstvennogo universiteta, - 336 p. (in Russian).

Tarasiuk, O. I., Pochynok, V. M. (2015) Vmist u lystkov azotu ta produktyvnist linii ozymoi miakoi pshenytsi, unikalnykh za khlibopekarskymy vlastyvostiamy. Fiziologiya rastenij i genetika. v. 47. n 1. p 66–73.

Shadchyna, T. M. (2001) Naukovi osnovy dystantsiinoho monitorynhu stanu posiviv zernovykh Kyiv. Fitosotsiotsentr. 220 p

Tian, Y. C., Yao, X., Yang, J., Cao, W. X., Hannaway, D. B., Zhu, Y. (2011) Assessing newly developed and published vegetation indices for estimating rice leaf nitrogen concentrationwith ground- and space-based hyperspectral reflectance. Field Crops Res. V. 120. - P. 299–310. https://doi.org/10.1016/j.fcr.2011.01.009

Belgiu, M., Csillik, O. (2018) Sentinel-2 cropland mapping using pixel-based and object-based timeweighted dynamic time warping analysis. Remote Sensing of Environment. V. 204. - N 1. - P. 509–523. https://doi.org/10.1016/j.rse.2017.10.005

Clevers, J. G. P. W., Kooistra, L., M. van den Brande, M. M. (2017) Using Sentinel-2 Data for Retrieving LAI and Leaf and Canopy Chlorophyll Content of a Potato Crop. Remote Sens. V. 9. - N 5. - P. 405–420. https://doi.org/10.3390/rs9050405

Dash, J., Curran, P. J. (2004) The MERIS terrestrial chlorophyll index. Int. Journal of Remote Sensing. V. 25. - N 23. - P. 5403–5413. https://doi.org/10.1080/0143116042000274015

Dawson, T. P., Curran, P. J. (1998) A new technique for interpolating the reflectance red edge position. International Journal of Remote Sensing. V. 19. - № 11. - Р. 2133–2139. https://doi.org/10.1080/014311698214910

Gitelson, A. A., Kaufman, Y. J., Merzlyak M. N. (1996) Use of a green channel in remote sensing of global vegetation from EOS-MODIS. Remote Sensing of Environment. V. 58. - № 3. - P. 289–298. https://doi.org/10.1016/s0034-4257(96)00072-7

Gitelson, A. A., Keydan, G. P., Merzlyak M. N. (2006) Three-band model for noninvasive estimation of chlorophyll, carotenoids, and anthocyanin contents in higher plant leaves. Geophysical Research. Letters 33, L 11402. https://doi.org/10.1029/2006gl026457

Horler, D. N. H., Dockray, M., Barber, J. (1983) The red edge of plant leaf reflectance. Int. Journal of Remote Sensing. V. 4. - N 2. - P. 273–288. https://doi.org/10.1080/01431168308948546

Huete, A. R. (1988) A soil-adjusted vegetation index (SAVI) Remote Sensing of Environment. V. 25. - N 3. - P. 295–309. https://doi.org/10.1016/0034-4257(88)90106-x

Herrmann, I., Pimstein, A, Karnieli, A., Cohen, Y., Alchanatis, V., Bonfil, D. J. (2011) LAI assessment of wheat and potato crops by VENμS and Sentinel-2 bands. Remote Sensing of Environment. V.115. № 8. P. 2141–2151. https://doi.org/10.1016/j.rse.2011.04.018

Rouse, J. W., Haas, Jr. R. H., Schell, J. A., Deering, D. W. (1973) Monitoring the vernal advancement and retrogradation (green wave effect) of natural vegetation Prog. Rep. RSC 1978-1, 93 p.

Soderstrom, M., Piikki, K., Stenberg, M., Stadig, H., Martinsson J. (2017) Producing nitrogen (N) uptake maps in winter wheat by combining proximal crop measurements with Sentinel-2 and DMC satellite images in a decision support system for farmers. Acta agriculturae scandinavica, section B - soil and plant science. V. 67. N 7. P. 637–650. https://doi.org/10.1080/09064710.2017.1324044

Strong, C. J., Burnside, N. G., Llewellyn, D. (2017) The potential of small-Unmanned Aircraft Systems for the rapid detection of threatened unimproved grassland communities using an Enhanced Normalized Difference Vegetation Index. PLoS ONE. № 12 (10). Р. 1–16. https://doi.org/10.1371/journal.pone.0186193

Section
Earth observation data applications: Challenges and tasks