Total Nitrogen Estimation in Agricultural Soils via Aerial Multispectral Imaging and LIBS

TL;DR

This paper presents an AI-driven UAV multispectral imaging method combined with LIBS for rapid, in-field estimation of soil total nitrogen, improving decision-making for fertilizer application and crop management.

Contribution

It introduces a novel UAV-based multispectral sensing approach integrated with machine learning models for real-time soil nitrogen estimation, reducing reliance on traditional lab methods.

Findings

Support vector machine achieved high prediction accuracy.

Multispectral data effectively correlated with soil nitrogen levels.

Method enables near real-time soil health assessment.

Abstract

Measuring soil health indicators is an important and challenging task that affects farmers' decisions on timing, placement, and quantity of fertilizers applied in the farms. Most existing methods to measure soil health indicators (SHIs) are in-lab wet chemistry or spectroscopy-based methods, which require significant human input and effort, time-consuming, costly, and are low-throughput in nature. To address this challenge, we develop an artificial intelligence (AI)-driven near real-time unmanned aerial vehicle (UAV)-based multispectral sensing (UMS) solution to estimate total nitrogen (TN) of the soil, an important macro-nutrient or SHI that directly affects the crop health. Accurate prediction of soil TN can significantly increase crop yield through informed decision making on the timing of seed planting, and fertilizer quantity and timing. We train two machine learning models including multi-layer perceptron and support vector machine to predict the soil nitrogen using a suite of data classes including multispectral characteristics of the soil and crops in red, near-infrared, and green spectral bands, computed vegetation indices, and environmental variables including air temperature and relative humidity. To generate the ground-truth data or the training data for the machine learning models, we measure the total nitrogen of the soil samples (collected from a farm) using laser-induced breakdown spectroscopy (LIBS).