The METRIC energy balance model uses an auto-selection approach for identifying hot (dry, bare soil) and cold (fully transpiring crop) anchor pixels for the internal calibration of the model. When an unmanned aerial system (UAS) is used for imagery,...
The ash produced by forest fires is a complex mixture of organic and inorganic particles with many properties. Amounts of ash and char are used to roughly evaluate the impacts of a fire on nutrient cycling and ecosystem recovery. Numerous studies hav...
Wind drift and evaporation loss (WDEL) of mid-elevation spray application (MESA) and low-elevation spray application (LESA) sprinklers on a center pivot and linear-move irrigation machines are measured and reported to be about 20% and 3%, respectivel...
Geospatial crop water use mapping is critical for field-scale site-specific irrigation management. Landsat 7/8 satellite imagery with a widely adopted METRIC (Mapping Evapotranspiration at high Resolution with Internalized Calibration) energy balance...
Shrub-dominated ecosystems support biodiversity and play an important storage role in the global carbon cycle. However, it is challenging to characterize biophysical properties of low-stature vegetation like shrubs from conventional ground-based or r...
Quantifying forest structure to assess changing wildfire risk factors is critical as vulnerable areas require mitigation, management, and resource allocation strategies. Remote sensing offers the opportunity to accurately measure forest attributes wi...
Unmanned aircraft systems (UAS), commonly referred to as drones, are an emerging technology that has changed the way many industries conduct business. Precision agriculture is one industry that has consistently been predicted to be a major locus of i...
The application of lidar data to assist with forest inventory is common around the world. However, the determination of tree species is still somewhat elusive. Lidar data collected using UAS (uncrewed aircraft systems) platforms offer high density po...
The emergence of affordable unmanned aerial systems (UAS) creates new opportunities to study fire behavior and ecosystem pattern—process relationships. A rotor-wing UAS hovering above a fire provides a static, scalable sensing platform that can...
Wildfire shapes vegetation assemblages in Mediterranean ecosystems, such as those in the state of California, United States. Successful restorative management of forests in-line with ecologically beneficial fire regimes relies on a thorough understan...
With an increase in the frequency and severity of wildfires across the globe and resultant changes to long-established fire regimes, the mapping of fire severity is a vital part of monitoring ecosystem resilience and recovery. The emergence of unoccu...
Interest in the use of unmanned aerial systems (UAS) to estimate the aboveground biomass (AGB) of vegetation in agricultural and non-agricultural settings is growing rapidly but there is no standardized methodology for planning, collecting and analyz...
Deriving crop information from remotely sensed data is an important strategy for precision agriculture. Small unmanned aerial systems (UAS) have emerged in recent years as a versatile remote sensing tool that can provide precisely-timed, fine-grained...
Adaptive modulation received significant attention for underwater acoustic (UA) communication systems with the aim of increasing the system efficiency. It is challenging to attain a high data rate in UA communication, as UA channels vary fast, along...
This paper investigates the risk quantification for Unmanned Aircraft (UA) in urban environments, focusing on the safety of ground people. An assessment methodology is proposed to quantify the flying risk, which indicates the ground fatalities result...
In the context of COVID-19, the efforts undertaken for epidemic control have imposed limitations on the multifaceted development of China. This manuscript utilizes Baidu migration data from 2019 to 2023 to classify the current developmental status of...
Unmanned Aircraft Systems (UASs) have undergone rapid development over recent years, but have also became vulnerable to security attacks and the volatile external environment. Ensuring that the performance of UASs is safe and secure no matter how the...
Thanks to sensor developments, unmanned aircraft system (UAS) are the most promising modern technologies used to collect imagery datasets that can be utilized to develop agricultural applications in these days. UAS imagery datasets can grow exponenti...
Small unmanned aircraft systems (sUASs) have emerged as promising platforms for the purpose of crash scene reconstruction through structure-from-motion (SfM) photogrammetry. However, auto crashes tend to occur under adverse weather conditions that us...
SmallUnmanned Aerial Systems (sUAS) have seen rapid adoption thanks to advances in endurance, communications, autonomy, and manufacturing costs, yet most testing remains focused on GPS-supported, above-ground operations. This study introduces new tes...
The ‘Returning Farmland to Forest Program’ (RFFP) in China has become an essential factor in land cover changes and forest transition, especially in terms of the ecological processes between two adjacent ecosystems. However, accurately de...
Structural traits of vegetation, derived from the three-dimensional distribution of plant elements, are closely linked to ecosystem functions such as productivity and habitat provision. While extensively studied in forest ecosystems, these traits rem...
Measuring, monitoring, and managing biodiversity across agricultural regions depends on methods that can combine high-resolution mapping of landscape patterns with local biodiversity observations. This study explores the potential to monitor biodiver...
The short-rotation coppice (SRC) culture of trees provides a sustainable form of renewable biomass energy, while simultaneously sequestering carbon and contributing to the regional carbon feedstock balance. To understand the role of SRC in carbon fee...
Advances in unmanned aerial systems (UASs) have increased the potential of remote sensing to overcome scale issues for soil moisture (SM) quantification. Regardless, optical imagery is acquired using various sensors and platforms, resulting in simple...
Rapid estimation of above-ground biomass (AGB) with high accuracy is essential for monitoring crop growth status and predicting crop yield. Recently, remote sensing techniques using unmanned aerial systems (UASs) have exhibited great potential in obt...
Many public safety agencies in the US have initiated a UAS-based procedure to document and map crash scenes. In addition to significantly reducing the time taken to document evidence as well as ensuring first responder safety, UAS-based mapping reduc...
This study utilized unmanned aerial systems (UAS) and terrestrial laser scanners (TLS) to develop a 3D numerical model of slope anchors and conduct a comprehensive analysis. Initial data were collected using a UAS with 4 K resolution, followed by a s...
Bathymetric surveying to gather information about depths and underwater terrain is increasingly important to the sciences of hydrology and geomorphology. Submerged terrain change detection, water level, and reservoir storage monitoring demand extensi...
Conventional measurement methods for above-ground biomass (AGB) are time-consuming, inaccurate, and labor-intensive. Unmanned aerial systems (UASs) have emerged as a promising solution, but a standardized procedure for UAS-based AGB estimation is lac...
The application of Unmanned Aircraft Systems (UAS) beneath the forest canopy provides a potentially valuable alternative to ground-based measurement techniques in areas of dense canopy cover and undergrowth. This research presents results from a stud...
Coastal tidal marshes are essential ecosystems for both economic and ecological reasons. They necessitate regular monitoring as the effects of climate change begin to be manifested in changes to marsh vegetation healthiness. Small unmanned aerial sys...
Science-based forest management requires quantitative estimation of forest attributes traditionally collected via sampled field plots in a forest inventory program. Three-dimensional (3D) remotely sensed data such as Light Detection and Ranging (lida...
This research advances millimeter-wave (mmWave) altimetry for unmanned aerial systems (UASs) by optimizing performance metrics within the constraints of inexpensive automotive radars. Leveraging the software-defined architecture, this study encompass...
Classifying bare earth (ground) points from Light Detection and Ranging (LiDAR) point clouds is well-established research in the forestry, topography, and urban domains using point clouds acquired by Airborne LiDAR System (ALS) at average point densi...
Precise altitude data are indispensable for flight navigation, particularly during the autonomous landing of unmanned aerial systems (UASs). Conventional light and barometric sensors employed for altitude estimation are limited by poor visibility and...
Unmanned Aircraft Systems (UAS) Traffic Management (UTM) is an active research subject as its proposed applications are increasing. UTM aims to enable a variety of UAS operations, including package delivery, infrastructure inspection, and emergency m...
The self-similar structure-based analysis of digital images offers many new practical possibilities. The fractal dimension is one of the most frequently measured parameters if we want to use image data in measurable analyses in metric spaces. In prac...
12 December 2024
In this paper, we introduce the Secured Real-Time Machine Communication Protocol (SRMCP), a novel industrial communication protocol designed to address the increasing demand for security and performance in Industry 4.0 environments. SRMCP integrates...
Introducing artificial intelligence techniques in agriculture offers new opportunities for improving crop management, such as in coffee plantations, which constitute a complex agroforestry environment. This paper presents a comparative study of three...
Forest structural attributes are key indicators for parameterization of forest growth models, which play key roles in understanding the biophysical processes and function of the forest ecosystem. In this study, UAS-based multispectral and RGB imageri...
Uncrewed aerial system (UAS) structure from motion (SfM) monitoring strategies for individual trees has rapidly expanded in the early 21st century. It has become common for studies to report accuracies for individual tree heights and DBH, along with...
Rising global temperatures tied to increases in greenhouse gas emissions are impacting high latitude regions, leading to changes in vegetation composition and feedbacks to climate through increased methane (CH4) emissions. In subarctic peatlands, per...
Land cover information extraction through object-based image analysis (OBIA) has become an important trend in remote sensing, thanks to the increasing availability of high-resolution imagery. Segmented objects have a large number of features that cau...
Digital aerial photogrammetric (DAP) techniques applied to unmanned aerial system (UAS) acquired imagery have the potential to offer timely and affordable data for monitoring and updating forest inventories. Development of methods for individual tree...
Recently, to address the multiple object tracking (MOT) problem, we harnessed the power of deep learning-based methods. The tracking-by-detection approach to multiple object tracking (MOT) involves two primary steps: object detection and data associa...
This study investigates the use of generative adversarial network (GAN)-based data augmentation to enhance data discretization for smoother drone input. The goal is to improve unmanned aerial vehicles’ (UAVs) performance and maneuverability by...
Aeolian transport affects beach and foredune pre-storm morphologies, which directly contribute to storm responses. However, significant spatiotemporal variation exists within beach-dune systems regarding how biotic and abiotic factors affect topograp...
The 5th Generation Mobile Communication (5G) plays a significant role in the Fourth Industrial Revolution (4IR), facilitating significant improvements and innovations in various fields. The 3rd Generation Partnership Project (3GPP) is currently stand...
This paper analyzes in detail how different loss functions influence the generalization abilities of a deep learning-based next frame prediction model for traffic scenes. Our prediction model is a convolutional long-short term memory (ConvLSTM) netwo...
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