Crop Yield Map Development Based on Satellite and UAV Data

Abstract

Agriculture is one of the promising areas for the introduction of remote sensing technologies. With its help, you can timely receive a wide range of dynamic information about the conditions for the crops growth and development and make the necessary adjustments to obtain the planned result. The paper presents the results of early forecasting of spring wheat yields based on Dove (PlanetScope) satellite data from Planet Labs and DJI P4 Multispectral unmanned data. The maps of the yield of spring wheat were constructed using satellite and unmanned data with a spatial resolution of 3 m and 5 cm, respectively. A statistical assessment of the inhomogeneity of the spectral optical characteristics of agricultural crops has been carried out. The degree of correlation dependence between the value of the integral of the index (NDVI, VARI, MSAVI2, ClGreen) and the yield in different periods of the growing season has been determined.

Bias correction of Sentinel-2 with unmanned aerial vehicle multispectral data for use in monitoring walnut fruit forest in western Tien Shan, Kyrgyzstan

“…21 In this context, remote sensing (RS) has already shown its potential and effectiveness in spatiotemporal vegetation monitoring. 19,[22][23][24] Additionally, many satellite platforms (e.g., Landsat, MODIS, Aster, SPOT, Sentinel-1, and Sentinel-2) are now providing free datasets, thus promoting satellite imagery for many agricultural applications, 14,22,23,[25][26][27] including those with multisensor data fusion approachs. 28 For example, remotely sensed images from Sentinel-2 used in our research offer decametric resolution in terms of space and time, with a ground sample distance of up to 10 m and a revisit time of 6 days.…”

“…Knowledge of spatial variability among and within forest parcels is a key factor for the users of walnut fruit forests to estimate yield and quality 21 . In this context, remote sensing (RS) has already shown its potential and effectiveness in spatiotemporal vegetation monitoring 19 , 22 – 24 Additionally, many satellite platforms (e.g., Landsat, MODIS, Aster, SPOT, Sentinel-1, and Sentinel-2) are now providing free datasets, thus promoting satellite imagery for many agricultural applications, 14 , 22 , 23 , 25 – 27 including those with multisensor data fusion approachs 28 .…”