Reliable geolocation of thermal hotspots, such as smoldering embers that can reignite after vegetation fire suppression, deep-seated peat fires, or underground coal seam fires, is critical to prevent fire resurgence, limit prolonged greenhouse gas em...
The application of UAVs in surveillance, disaster management, and military operations has surged, necessitating robust and real-time tracking systems for moving targets. However, accurately tracking and predicting the trajectories of ground targets p...
Unmanned aerial vehicles (UAVs) are vital for surveillance missions requiring the geolocation of moving ground targets, yet small, resource-constrained platforms often lack integrated, robust systems that can handle disturbances such as wind, occlusi...
In this work, we propose a geolocation framework for distant ground targets integrating laser rangefinder sensors with multimodal visual servo control. By simulating binocular visual servo measurements through monocular visual servo tracking at fixed...
The geolocalization of unmanned aerial vehicles (UAVs) in satellite-denied environments has emerged as a key research focus. Recent advancements in this area have been largely driven by learning-based frameworks that utilize convolutional neural netw...
Cross-view geolocalization matches the same target in different images from various views, such as views of unmanned aerial vehicles (UAVs) and satellites, which is a key technology for UAVs to autonomously locate and navigate without a positioning s...
Geo-localization has been widely applied as an important technique to get the longitude and latitude for unmanned aerial vehicle (UAV) navigation in outdoor flight. Due to the possible interference and blocking of GPS signals, the method based on ima...
Visual geo-localization can achieve UAVs (Unmanned Aerial Vehicles) position during GNSS (Global Navigation Satellite System) denial or restriction. However, The performance of visual geo-localization is seriously impaired by illumination variation,...
Visual geo-localization plays a crucial role in positioning and navigation for unmanned aerial vehicles, whose goal is to match the same geographic target from different views. This is a challenging task due to the drastic variations in different vie...
Cross-view image matching has attracted extensive attention due to its huge potential applications, such as localization and navigation. Unmanned aerial vehicle (UAV) technology has been developed rapidly in recent years, and people have more opportu...
Low-cost and real-time remote sensing of moving targets is increasingly required in civilian applications. Micro unmanned aerial vehicles (UAVs) provide a promising platform for such missions because of their small size and flexible deployment, but t...
Since unmanned aerial vehicles (UAVs), such as drones, are used in various fields due to their high utilization and agile mobility, technologies to deal with multiple UAVs are becoming more important. There are many advantages to using multiple drone...
Within research on the cross-view geolocation of UAVs, differences in image sources and interference from similar scenes pose huge challenges. Inspired by multimodal machine learning, in this paper, we design a single-stream pyramid transformer netwo...
The past decade has witnessed a growing demand for drone-based fire detection systems, driven by escalating concerns about wildfires exacerbated by climate change, as corroborated by environmental studies. However, deploying existing drone-based fire...
Today, unmanned aerial vehicles (UAVs) are heavily dependent on Global Navigation Satellite Systems (GNSSs) for positioning and navigation. However, GNSS signals are vulnerable to jamming and spoofing attacks. This poses serious security risks, espec...
This paper develops a framework for geolocating a ground moving target with images taken from an unmanned aerial vehicle (UAV). Unlike the usual moving target geolocation approaches that rely heavily on a laser rangefinder, multiple UAVs, prior infor...
The estimation of Unmanned Aerial Vehicle (UAV) poses using visual information is essential in Global Navigation Satellite System (GNSS)-denied environments. In this paper, we propose a UAV visual navigation algorithm based on visual-geography Bundle...
Unmanned aerial vehicles (UAVs) must keep track of their location in order to maintain flight plans. Currently, this task is almost entirely performed by a combination of Inertial Measurement Units (IMUs) and reference to GNSS (Global Navigation Sate...
This paper develops a framework for geolocating ground-based moving targets with images taken from dual unmanned aerial vehicles (UAVs). Unlike the usual moving-target geolocation methods that rely heavily on accurate navigation state sensors or assu...
In unmanned aerial vehicle (UAV)-mounted base station (MBS) networks, user equipment (UE) experiences dynamic channel variations because of the mobility of the UAV and the changing weather conditions. In order to overcome the degradation in the quali...
Cross-view image matching between UAV and satellite platforms is critical for geographic localization but remains challenging due to domain gaps caused by disparities in imaging sensors, viewpoints, and illumination conditions. To address these chall...
The stable flight of drones relies on Global Navigation Satellite Systems (GNSS). However, in complex environments, GNSS signals are prone to interference, leading to flight instability. Inspired by cross-view machine learning, this paper introduces...
In the last few years, uncrewed aerial systems (UASs) have been broadly employed for many applications including urban traffic monitoring. However, in the detection, tracking, and geolocation of moving vehicles using UAVs there are problems to be enc...
Cross-view geo-localization (CVGL) presents significant challenges due to the drastic variations in perspective and scene layout between unmanned aerial vehicle (UAV) and satellite images. Existing methods have made certain advancements in extracting...
UAVs typically rely on satellite navigation for positioning, yet this method proves ineffective in instances where the signal is inadequate or communication is disrupted. Visually based positioning technology has emerged as a reliable alternative. In...
UAV localization in denial environments is a hot research topic in the field of cross-view geo-localization. The previous methods tried to find the corresponding position directly in the satellite image through the UAV image, but they lacked the cons...
High-precision, real-time, and long-range target geo-location is crucial to UAV reconnaissance and target strikes. Traditional geo-location methods are highly dependent on the accuracies of GPS/INS and the target elevation, which restricts the target...
Accurate monitoring of rice phenology is critical for crop management, cultivars breeding, and yield estimating. Previously, research for phenology detection relied on time-series data and orthomosaic and manually plotted regions, which are difficult...
Multi-view scene matching refers to the establishment of a mapping relationship between images captured from different perspectives, such as those taken by unmanned aerial vehicles (UAVs) and satellites. This technology is crucial for the geo-localiz...
Nowadays, various unmanned aerial vehicle (UAV) applications become increasingly demanding since they require real-time, autonomous and intelligent functions. Towards this end, in the present study, a fully autonomous UAV scenario is implemented, inc...
GNSS positioning accuracy can be degraded in areas where the surrounding object geometry and morphology interacts with the GNSS signals. Specifically, urban environments pose challenges to precise GNSS positioning because of signal interference or in...
We investigate footprint geolocation uncertainties of a spectroradiometer mounted on an unmanned aircraft system (UAS). Two microelectromechanical systems-based inertial measurement units (IMUs) and global navigation satellite system (GNSS) receivers...
In Global Navigation Satellite System (GNSS)-denied urban environments, unmanned ground vehicles (UGVs) face significant difficulties in maintaining reliable localization due to occlusion and structural complexity. Unmanned aerial vehicles (UAVs), wi...
Stranded beach litter is a ubiquitous issue. Manual monitoring and retrieval can be cost and labour intensive. Therefore, automatic litter monitoring and retrieval is an essential mitigation strategy. In this paper, we present important foundational...
In Global Navigation Satellite System (GNSS)-denied environments, image registration has emerged as a prominent approach to utilize visual information for estimating the position of Unmanned Aerial Vehicles (UAVs). However, traditional image-registra...
Target geolocation in long-range oblique photography (LOROP) is a challenging study due to the fact that measurement errors become more evident with increasing shooting distance, significantly affecting the calculation results. This paper introduces...
Cross-view geo-localization is a challenging task due to the significant changes in the appearance of target scenes from variable perspectives. Most existing methods primarily adopt Transformers or ConvNeXt as backbone models but often face high comp...
Unmanned aerial vehicles (UAVs) have been employed to perform aerial surveys in many industries owing to their versatility, relatively low cost, and efficiency. Ground control points (GCPs) are used for georeferencing to ensure orthophoto geolocation...
Unmanned aerial vehicle (UAV) self-localization in complex environments is critical when global navigation satellite systems (GNSSs) are unreliable. Existing datasets, often limited to low-altitude urban scenes, hinder generalization. This study intr...
Remote sensing platforms have become an effective data acquisition tool for digital agriculture. Imaging sensors onboard unmanned aerial vehicles (UAVs) and tractors are providing unprecedented high-geometric-resolution data for several crop phenotyp...
In this paper, we propose an original deep learning framework for the automated counting and geolocation of palm trees from aerial images using convolutional neural networks. For this purpose, we collected aerial images from two different regions in...
Traditional plant breeding evaluation methods are time-consuming, labor-intensive, and costly. Accurate and rapid phenotypic trait data acquisition and analysis can improve genomic selection and accelerate cultivar development. In this work, a techni...
This study explores the use of electronic countermeasures to disrupt communications systems in Unmanned Aerial Vehicles (UAVs), focusing on the protection of airspaces and critical infrastructures such as airports and power stations. The research aim...
High spatial resolution and geolocation accuracy canopy evapotranspiration (ET) maps are well suited tools for evaluation of small plot field trials. While creating such a map by use of an energy balance model is routinely performed, the acquisition...
This paper provides an in-depth literature review on image processing techniques, focusing on deep learning approaches for anomaly detection and classification in photovoltaics. It examines key components of UAV-based PV inspection, including data ac...
Recent years have witnessed the fast development of UAVs (unmanned aerial vehicles). As an alternative to traditional image acquisition methods, UAVs bridge the gap between terrestrial and airborne photogrammetry and enable flexible acquisition of hi...
Accurate geolocation and tracking of Radio-Frequency Interference (RFI) sources, which affect wireless and satellite systems such as Global Navigation Satellite Systems (GNSS) and Satellite Communication (SatCom) systems, are considered to be a signi...
Within the context of precision agriculture, goods insurance, public subsidies, fire damage assessment, etc., accurate knowledge about the plant population in crops represents valuable information. In this regard, the use of Unmanned Aerial Vehicles...
This research describes an experimental solution used for estimating the positions of pedestrians from video recordings. Additionally, clustering algorithms were utilized to interpret the data. The system employs the You Only Look Once (YOLO) algorit...
Unmanned aerial vehicles (UAVs) are a key driver of the low-altitude economy, where precise localization is critical for autonomous flight and complex task execution. However, conventional global positioning system (GPS) methods suffer from signal in...
of 2