Remote sensing validation with in-situ measurements for efficient crop irrigation management

Remote sensing validation with in-situ measurements for efficient crop irrigation management

I. Terlizzi, F. Morbidini, C. Maucieri, C. Bettanini, G. Colombatti, S. Chiodini, F. Toson, M. Borin

Abstract. The multi-spectral data acquired with either satellite imagery, UAV or tethered and stratospheric balloons can be used to calculate vegetation indices directly related to the well-being of the crops providing a quantitative information about its health and growth. The vegetation indices are calculated combining measurements from different parts of the electromagnetic spectrum, typically in the visible and near-infrared ranges. The aim of this work is to integrate the remote sensing data with in-situ collected measurements in order to validate remote observations for monitoring soybean water status and requirements. The study is conducted in Italy on a field of 160 x 40 m2, divided into four plots of 40 x 40 m2; two of them are irrigated at 100% of the CRW (Crop Water Requirement) and two irrigated at 70% of CWR. In each plot tensiometers and capacitive probes directly measure the soil moisture, along with a climate station used to monitor environmental parameters. The in-situ data are correlated with multi band satellite images by the PlanetScope constellation providing a ground resolution of 3 m. The use of UAV or balloons is needed to monitor the diurnal variation of the indices, as the satellite revisit time is once per day around 9:00 and 10:00 UTC on the site. The balloon payload is equipped with commercial cameras and dedicated filters to acquire images in the same spectral bands as satellites. The importance of this study lies in the possibility of managing the fields irrigation basing on the actual physiological need of the crop rather than relying on a predefined timetable, resulting in a more efficient and environmentally responsible irrigation. The article will present the methodology and the instruments applied, together with the results obtained.

Keywords
Vegetation Index, Satellite, Multi-Spectral, Remote Sensing

Published online 11/1/2023, 4 pages
Copyright © 2023 by the author(s)
Published under license by Materials Research Forum LLC., Millersville PA, USA

Citation: I. Terlizzi, F. Morbidini, C. Maucieri, C. Bettanini, G. Colombatti, S. Chiodini, F. Toson, M. Borin, Remote sensing validation with in-situ measurements for efficient crop irrigation management, Materials Research Proceedings, Vol. 37, pp 262-265, 2023

DOI: https://doi.org/10.21741/9781644902813-57

The article was published as article 57 of the book Aeronautics and Astronautics

Content from this work may be used under the terms of the Creative Commons Attribution 3.0 license. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.

References
[1] Aydinsakir K. “Yield and quality characteristics of drip-irrigated soy bean under different irrigation levels”. In: Agronomy Journal 110 (2018),pp. 1473–1481. https://doi.org/10.2134/agronj2017.12.0748
[2] Massari C et al. “A review of irrigation information retrievals from space and their utility for users.” In: Remote Sensing 13 (20 2021), p. 4112. https://doi.org/10.3390/rs13204112
[3] Campos I et al. “Estimation of total available water in the soil layer by integrating actual evapotranspiration data in a remote sensing-driven soil water balance.” In: Hydrology 534 (2016), pp. 427–439. https://doi.org/10.1016/j.jhydrol.2016.01.023
[4] Ahmad U, Alvino A, and Marino S. “A review of crop water stress assessment using remote sensing. Remote Sensing”. In: Agronomy Journal 13 (2021), p. 4155. https://doi.org/10.3390/rs13204155
[5] Information on https://leonardolaureti.wordpress.com/2021/01/08/interpretazione-degli-indici/