Model for Estimating Soil Chemical Properties with RGB Drone Images

Authors

DOI:

https://doi.org/10.29019/enfoqueute.1078

Keywords:

precision agriculture, spectral indices, Phantom 4 Pro, PIX4Dmapper, ArcGIS

Abstract

Precision agriculture optimizes crop management by providing accurate data on soil chemical properties, thereby improving agricultural productivity and sustainability. This study aims to develop models to estimate soil chemical properties, such as pH, electrical conductivity (EC), and organic matter (OM), by analyzing drone-captured RGB images. The methodology included photogrammetric flights with a DJI Phantom 4 Pro drone equipped with a 20 Mpx camera and simultaneous sampling, laboratory analysis and on-site measurements, with Royal Eijkelkamp EC meter set voor grond multiparameter sensors and pH meter set for soil and water. The aerial images were processed with the PIX4Dmapper software, to generate the orthophoto and spectral bands. With the resulting orthophoto of 1.6 cm/pixel, eight spectral indices were calculated, using the spatial analysis tools of ArcGIS software. The in situ results showed an average pH value of 5.83, indicating a slightly acidic soil, and an EC of 1.09 dS/m, suggesting a soil with a low concentration of dissolved salts. Laboratory analyses showed a medium-high content of OM, with an average of 5.19 %. A strong correlation was found between OM and pH_index with coefficients of determination R2=0.55, while moderate correlations were also observed between pH with pH_index and EC with sal_index6 with coefficients of determination R2=-0.39 and R2=0.42 respectively. The aforementioned results allowed the generation of two models for the estimation of these variables from RGB images.

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Published

2024-10-01

How to Cite

Alava, M., García Solórzano, A. J., Pacheco Gil, H. A., & Delgado Marcillo, C. M. (2024). Model for Estimating Soil Chemical Properties with RGB Drone Images. Enfoque UTE, 15(4), 19–26. https://doi.org/10.29019/enfoqueute.1078

Issue

Vol. 15 No. 4 (2024)

Section

Miscellaneous

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