Optimizing data collection in precision agriculture – comparing remote sensing and in situ analyses

Endalkachew Abebe Kebede1,3, Silviya Vasileva1, Bozhidar Ivanov2, Orhan Dengiz3 and Bojin Bojinov1
1 Agricultural University of Plovdiv, 4000 Plovdiv, Bulgaria
2 Agricultural Academy, Institute of Agricultural Economics, 1113 Sofia, Bulgaria
3 Department of Soil Science and Plant Nutrition, Ondokuz Mayis University, Samsun, Turkey

Abstract

Kabede, E.A., Vasileva, S., Ivanov, B., Dengiz, O. & Bojinov, B. (2024). Optimizing data collection in precision agriculture – comparing remote sensing and in situ analyses. Bulg. J. Agric. Sci., 30(1), 11–16

Remote sensing has a potential application in assessing and monitoring the plants’ biophysical properties using the spectral responses of plants and soils within the electromagnetic spectrum. However, only a few reports compare the performance of different remote sensing approaches against in-situ spectral measurement. The current study assessed potential applications of open data source satellite images (Sentinel 2 and Landsat 9) in estimating the biophysical properties of a crop on a study farm. A Landsat 9 (30 m resolution) and Sentinel-2 (10 m resolution) satellite images with less than 10% cloud cover have been extracted from the open data sources for the period of December 2021 – April 2022. In addition, SpectraVue 710s Leaf Spectrometer was used to measure the spectral response of the crop in April at five different locations within the same field. Results obtained by different data collection methods were compared to evaluate them for applicability in precision agriculture.

Keywords: precision agriculture; vegetation indices; NDVI

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