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ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa
CURRENT PROBLEMS IN REMOTE SENSING OF THE EARTH FROM SPACE

  

Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2019, Vol. 16, No. 5, pp. 183-193

Estimation of the spatial distribution of spring barley yield (Krasnoyarsk Territory) from ground and satellite spectrophotometric data

I.Yu. Botvich 1 , D.V. Emelyanov 1 , A.A. Larko 1 , N.O. Malchikov 1 , V.K. Ivchenko 2 , T.N. Demyanenko 2 , A.P. Shevyrnogov 1 
1 Institute of Biophysics SB RAS, Krasnoyarsk, Russia
2 Krasnoyarsk State Agrarian University, Krasnoyarsk, Russia
Accepted: 08.08.2019
DOI: 10.21046/2070-7401-2019-16-5-183-193
The paper presents a method for estimating the spatial distribution of spring barley yield, implemented based on the use of optical ground and satellite spectral data (PlanetScope with a spatial resolution of 3 meters). This approach is highly relevant for the development of precision farming technologies. Yield mapping is carried out on the basis of the data on spatial distribution of actual yield and spatial distribution of spectral optical characteristics. A feature of the method is the use of the integral values of vegetation indices (NDVI, MSAVI2, ClGreen) at various stages of crop development. Testing of the method was performed on the basis of stationary field experience, when traditional agriculture (deep plowing) was compared with resource-saving technologies (flat-cut, surface treatments and direct seeding at zero tillage). As a result, a method for estimating the spatial distribution of spring barley yield, implemented using optical ground and satellite spectral data (PlanetScope with a spatial resolution of 3 meters) was developed. The prediction of barley yields at the end of July on the basis of a linear regression model was performed, the values of the integral under the NDVI curve in different periods of time were used as parameters. The type of a multiple linear model for predicting barley with 7 variables was established (the coefficient of determination is 0.73; the root-mean-square error is 1.5). The spatial distribution of barley yield by satellite (PlanetScope) and ground data was mapped. The resulting yield maps will be used when planning work for the next year.
Keywords: precision farming, crop yield, growing season, spectroradiometer, barley, types of tillage, PlanetScope
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