A Systematic Review of UAV Applications for Mapping Neglected and Underutilised Crop Species’ Spatial Distribution and Health

Abstract

Timely, accurate spatial information on the health of neglected and underutilised crop species (NUS) is critical for optimising their production and food and nutrition in developing countries. Unmanned aerial vehicles (UAVs) equipped with multispectral sensors have significantly advanced remote sensing, enabling the provision of near-real-time data for crop analysis at the plot level in small, fragmented croplands where NUS are often grown. The objective of this study was to systematically review the literature on the remote sensing (RS) of the spatial distribution and health of NUS, evaluating the progress, opportunities, challenges, and associated research gaps. This study systematically reviewed 171 peer-reviewed articles from Google Scholar, Scopus, and Web of Science using the PRISMA approach. The findings of this study showed that the United States (n = 18) and China (n = 17) were the primary study locations, with some contributions from the Global South, including southern Africa. The observed NUS crop attributes included crop yield, growth, leaf area index (LAI), above-ground biomass (AGB), and chlorophyll content. Only 29% of studies explored stomatal conductance and the spatial distribution of NUS. Twenty-one studies employed satellite-borne sensors, while only eighteen utilised UAV-borne sensors in conjunction with machine learning (ML), multivariate, and generic GIS classification techniques for mapping the spatial extent and health of NUS. The use of UAVs in mapping NUS is progressing slowly, particularly in the Global South, due to exorbitant purchasing and operational costs, as well as restrictive regulations. Subsequently, research efforts must be directed toward combining ML techniques and UAV-acquired data to monitor NUS’ spatial distribution and health to provide necessary information for optimising food production in smallholder croplands in the Global South.

An Autonomous Tracking and Landing Method for Unmanned Aerial Vehicles Based on Visual Navigation

“…UAVs offer numerous advantages, such as strong maneuverability, low maintenance costs, vertical takeoff ability, and impressive hovering capabilities. As a result, they are widely used in various fields, including search and rescue, exploration, disaster monitoring, inspection, and agriculture [1][2][3][4]. However, limitations on payload and flight time significantly restrict the range of UAV missions.…”

Comprehensive Investigation of Unmanned Aerial Vehicles (UAVs): An In-Depth Analysis of Avionics Systems

“…On the other hand, the review in [51] examined the drone-integrated Geographic Information System (GIS) in different fields, differently from the work in [52], which focused on UAVs' potential to advance climate change research and monitoring. Although the work in [53] mainly accounted for the UAV remote sensing of crop species, it included some of the multispectral sensors used in such applications, thus enriching the informative background about UAVs. In a more general approach, the review in [54] considered a structured presentation of the recent trends in the UAV field, classifying them according to their flight characteristics, showcasing the potential areas for further development, and addressing the hardware/software within a UAV.…”

“…As can be noted from the literature survey encompassing the modern reviews in [46][47][48][49][50][51][52][53][54][55][56][57][58][59][60][61][62][63], the majority of these articles actually focus on the UAV domain of usage and application fields. In other terms, there exist no reviews about the drones themselves, involving different architectures, structures, avionics, and software-to-hardware branches (i.e., the results of algorithms over the behavioral mechanism of sensors).…”