Thermal infrared imagery is very much gaining in importance in the diagnosis of energy losses in cultural heritage through non-destructive measurement methods. Hence, owing to the fact that it is a very innovative and, above all, safe solution, it is...
Operational forest monitoring often requires fine-detail information in the form of an orthomosaic, created by stitching overlapping nadir images captured by aerial platforms such as drones. RGB drone sensors are commonly used for low-cost, high-reso...
The sustainable development of agriculture is closely related to the adoption of precision agriculture techniques, and accurate crop classification is a fundamental aspect of this approach. This study explores the application of machine learning tech...
In the recent decade, the rapid development of drone technologies has made many spatial problems easier to solve, including the problem of 3D reconstruction of large objects. A review of existing solutions has shown that most of the works lack the au...
In the field of drone-to-drone detection tasks, the issue of fusing temporal information with infrared and visible light data for detection has been rarely studied. This paper presents the first temporal misaligned rgb-thermal dataset for drone-to-dr...
Constant detection and monitoring of archaeological sites and objects have always been an important national goal for many countries. The early identification of changes is crucial to preventive conservation. Archaeologists have always considered usi...
Developing accurate activity data on tree biomass using remote sensing tools such as LiDAR and drone-mounted sensors is essential for improving carbon accounting in the agricultural sector. However, direct biomass measurements of perennial fruit tree...
With the global population on the rise and arable land diminishing, the need for sustainable and precision agriculture has become increasingly important. This study explores the application of unoccupied aerial systems (UAS) in precision agriculture,...
Detection and Semantic Segmentation of vehicles in drone aerial orthomosaics has applications in a variety of fields such as security, traffic and parking management, urban planning, logistics, and transportation, among many others. This paper presen...
Monitoring marine fauna is essential for mitigating the effects of disturbances in the marine environment, as well as reducing the risk of negative interactions between humans and marine life. Drone-based aerial surveys have become popular for detect...
This paper proposes a cluster-based flight path construction method for automated drone-assisted pear pollination systems in orchard environments. The approach uses RGB-D (Red-Green-Blue-Depth) sensing through an observation drone equipped with RGB a...
Tree of heaven (Ailanthus altissima) is a highly invasive tree species in the USA and the preferred host of an invasive insect, the spotted lanternfly (Lycorma delicatula). Currently, pest managers rely solely on ground surveys for detecting both A. ...
Interest in drone solutions in forestry applications is growing. Using drones, datasets can be captured flexibly and at high spatial and temporal resolutions when needed. In forestry applications, fundamental tasks include the detection of individual...
Crop growth is often uneven within an agricultural parcel, even if it has been managed evenly. Aerial images are often used to determine the presence of vegetation and its spatial variability in field parcels. However, the reasons for this uneven gro...
Nowadays, the public service practice applicability of drones and remote sensing sensors is being explored in almost all industrial and military areas. In the present research, in collaboration with different universities, we investigate the applicab...
In this work, a new method is proposed that allows the use of a single RGB camera for the real-time detection of objects that could be potential collision sources for Unmanned Aerial Vehicles. For this purpose, a new network with an encoder–dec...
Drone-based photogrammetry typically requires the task of georeferencing aerial images by detecting the center of Ground Control Points (GCPs) placed in the field. Since this is a very labor-intensive task, it could benefit greatly from automation. I...
Monitoring crop damage caused by wildlife remains a significant challenge in agricultural management, particularly in the case of large-scale monocultures such as maize. The given study presents a semi-automated process for detecting wildlife-induced...
This paper investigated the utility of drone-based environmental monitoring to assist with forest inventory in Queensland private native forests (PNF). The research aimed to build capabilities to carry out forest inventory more efficiently without th...
Crop height and biomass are the two important phenotyping traits to screen forage population types at local and regional scales. This study aims to compare the performances of multispectral and RGB sensors onboard drones for quantitative retrievals o...
Drones are being increasingly used in conservation to tackle the illegal poaching of animals. An important aspect of using drones for this purpose is establishing the technological and the environmental factors that increase the chances of success wh...
This study explores the efficacy of drone-acquired RGB images and the YOLO model in detecting the invasive species Siam weed (Chromolaena odorata) in natural environments. Siam weed is a perennial scrambling shrub from tropical and sub-tropical Ameri...
An efficient metal recovery in heap leach operations relies on uniform distribution of leaching reagent solution over the heap leach pad surface. However, the current practices for heap leach pad (HLP) surface moisture monitoring often rely on manual...
Recent improvements in low-altitude remote sensors and image processing analysis can be utilised to support archaeological research. Over the last decade, the increased use of remote sensing sensors and their products for archaeological science and c...
Traditional methods of counting seedling inventory are expensive, time-consuming, and lacking in spatial resolution. Although previous studies have explored the use of drones for seedling inventory, a cost-effective and accurate solution that can det...
16 January 2024
This study analyzes repercussions for the morphology, talweg, riverbanks and surrounding structures of several aquatic systems transformed by multipurpose reservoirs located within the Ecuadorian territory of South America. For this purpose, several...
At this time, many illegal activities are being been carried out, such as illegal mining, hunting, logging, and forest burning. These things can have a substantial negative impact on the environment. These illegal activities are increasingly rampant...
Globally, native semiarid grasslands and savannas have experienced a densification of woody plant species—leading to a multitude of environmental, economic, and cultural changes. These encroached areas are unique in that the diversity of tree s...
Recognizing initial degradation levels is essential to planning effective measures to restore tropical forest ecosystems. However, measuring indicators of forest degradation is labour-intensive, time-consuming, and expensive. This study explored the...
In recent years, remote sensing techniques such as satellite and drone-based imaging have been used to monitor Pine Wilt Disease (PWD), a widespread forest disease that causes the death of pine species. Researchers have explored the use of remote sen...
This paper presents a time- and cost-efficient method for the management of construction and demolition (C&D) debris at construction sites, demolition jobsites, and illegal C&D waste dumping sites. The developed method integrates various dron...
Uncrewed aerial systems (UASs) have emerged as powerful ecological observation platforms capable of filling critical spatial and spectral observation gaps in plant physiological and phenological traits that have been difficult to measure from space-b...
Unmanned aerial vehicles (UAVs), also known as drones, are a cost-effective alternative to traditional surveying methods, and they can be used to collect geospatial data over inaccessible or hard-to-reach locations. UAV-integrated miniaturized remote...
The evaluation of soil tillage quality parameters, such as cloddiness and surface roughness produced by tillage tools, is based on traditional methods ranging, respectively, from manual or mechanical sieving of ground samples to handheld rulers, non-...
The objective of this study is to investigate the potential of novel neural network architectures for measuring the quality and quantity parameters of silage grass swards, using drone RGB and hyperspectral images (HSI), and compare the results with t...
Drones have rapidly emerged as transformative tools in landscape research, enabling high-resolution spatial data acquisition, real-time environmental monitoring, and advanced modelling that surpass the limitations of traditional methodologies. This s...
In surface mining operations, geological pit wall mapping is important since it provides significant information on the surficial geological features throughout the pit wall faces, thereby improving geological certainty and operational planning. Conv...
Food security is one of the burning issues in the 21st century, as a tremendous population growth over recent decades has increased demand for food production systems. However, agricultural production is constrained by the limited availability of ara...
Turfgrass irrigation consumes a large amount of the scarce freshwater in arid/semi-arid regions. Approximately 50% of this irrigation water is wasted. It has been suggested that determining patterns of spatial variability in soil moisture to modify a...
Oat products are significant parts of a healthy diet. Pure oat is gluten-free, which makes it an excellent choice for people with celiac disease. Elimination of alien cereals is important not only in gluten-free oat production but also in seed produc...
Desert vegetation is an important part of arid and semi-arid areas, which plays an important role in preventing wind and fixing sand, conserving water and soil, maintaining the balanced ecosystem. Therefore, mapping the vegetation accurately is neces...
Non-destructive in-season grain yield (GY) prediction would strongly facilitate the selection process in plant breeding but remains challenging for phenologically and morphologically diverse germplasm, notably under high-yielding conditions. In recen...
To address the critical challenges of insufficient monitoring capabilities and vulnerable defense systems against drones in regional airports, this study proposes a multi-source data fusion framework for rapid UAV detection. Building upon the YOLO v1...
The site-specific management of cotton fields is necessary for evaluating the growth status of cotton and generating a defoliation prescription map. The traditional assessment method of pests and diseases is based on spot surveys and manual participa...
Breeding and selection of nursery plants require evaluation of a wide variety of traits. Characteristics that are visually scored in the field include aesthetic beauty as well as tolerance to (a)biotic stresses, among others. This work proposes metho...
The question of how to estimate the state of an unmanned aerial vehicle (UAV) in real time in multi-environments remains a challenge. Although the global navigation satellite system (GNSS) has been widely applied, drones cannot perform position estim...
Efficient diagnosis of apple diseases and pests is crucial to the healthy development of the apple industry. However, the existing single-source image-based classification methods have limitations due to the constraints of single-source input image i...
The detection and mapping of riverscapes with Unmanned Aerial Vehicles (UAVs, drones) provide detailed, reliable, and operable spatial information in hydrological sciences, enhancing conventional field survey techniques. In this study, we present the...
Drones equipped with visible and infrared sensors play a vital role in urban road supervision. However, conventional methods using RGB-IR image pairs often struggle to extract effective features. These methods treat these spectra independently, missi...
The biophysical properties of a crop are a good indicator of potential crop stress conditions. However, these visible properties cannot indicate areas exhibiting non-visible stress, e.g., early water or nutrient stress. In this research, maize crop b...
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