Digital gradient sensing (DGS) is a non-contact and full-field optical measurement technique, which assesses mechanical behaviors of transparent materials or specular structures by measuring angular deflections of light rays. However, owing to the po...
In this paper, a comparative study of the mode-I fracture behaviors of two types of specimens with a V-notch defect under plane stress conditions was performed using the digital gradient sensing (DGS) method. First, two types of specimens (namely one...
The digital time delay integration (digital TDI) technology of the complementary metal-oxide-semiconductor (CMOS) image sensor has been widely adopted and developed in the optical remote sensing field. However, the details of targets that have low il...
Brain–computer interface (BCI) technology is currently a cutting-edge exploratory problem in the field of human–computer interaction. However, in experiments involving the implantation of electrodes into brain tissue, particularly high-sp...
Soil total nitrogen (STN) is a crucial component of the ecosystem’s nitrogen pool, and accurate prediction of STN content is essential for understanding global nitrogen cycling processes. This study utilized the measured STN content of 126 samp...
In this paper, we introduce a low-cost, expansible, and compatible measurement and control system for atomic force microscopes (AFM) based on a quartz tuning fork (QTF) self-sensing probe and frequency modulation, which is mainly composed of an embed...
In this work, a two-dimensional (2D) position-detection device using a single axis magnetic sensor combined with orthogonal gradient coils was designed and fabricated. The sensors used were an induction coil and a GMR spin-valve sensor GF807 from Sen...
In this article, the local spatial correlation of multiple remote sensing datasets, such as those from Sentinel-1, Sentinel-2, and digital surface models (DSMs), are linked to machine learning (ML) regression algorithms for flash floodwater depth ret...
Deep neural networks have been widely used in detection tasks based on optical remote sensing images. However, in recent studies, deep neural networks have been shown to be vulnerable to adversarial examples. Adversarial examples are threatening in b...
The Three-River Source Region (TRSR) is vital to the ecological security of China. However, the impact of global warming on the dynamics of vegetation along the elevation gradient in the TRSR remains unclear. Accordingly, we used multi-source remote...
Soil moisture (SM) profoundly influences crop growth, yield, soil temperature regulation, and ecological balance maintenance and plays a pivotal role in water resources management and regulation. The focal objective of this investigation is to identi...
Remote sensing data are increasingly being used in digital archaeology for the potential non-invasive detection of archaeological remains. The purpose of this research is to evaluate the capability of standalone (LiDAR and aerial photogrammetry) and...
Protected areas (PAs) need to be assessed systematically according to biodiversity values and threats in order to support decision-making processes. For this, PAs can be characterized according to their species, ecosystems and threats, but such infor...
Comparing algorithms are crucial for enhancing the accuracy of remote sensing estimations of forest biomass in regions with high heterogeneity. Herein, Sentinel 2A, Sentinel 1A, Landsat 8 OLI, and Digital Elevation Model (DEM) were selected as data s...
This work presents an experimental evaluation of a high-speed analog-to-digital conversion method based on passive reference waveform crossings combined with time-to-digital converter (TDC) time-tagging. Unlike conventional level-crossing event-drive...
Natural soil and rock materials and the associated artificial materials have cracks, fractures, or contacts and possibly produce rock fragments or particles during geological, environmental, and stress conditions. Based on color gradient distribution...
Cotton growth monitoring can provide macroscopic information for cotton field management. In this paper, we utilised UAV multispectral remote sensing to monitor cotton growth and constructed a Comprehensive Growth Index (CGI) by combining cotton mult...
Estimation of forest above-ground biomass (AGB) using multi-source remote sensing data is an important method to improve the accuracy of the estimate. However, selecting remote sensing factors that can effectively improve the accuracy of forest AGB e...
Inspired by the natural skeletal muscles, this paper presents a novel shape memory alloy-based artificial muscle matrix (AMM) with advantages of a large output force and displacement, flexibility, and compactness. According to the composition of the...
Digital elevation models (DEMs), which can provide an accurate description of planetary surface elevation changes, play an important role in scientific tasks such as long-distance path planning, terrain analysis, and planetary surface reconstruction....
Temperature is a key driver of microbial metabolism, yet non-invasive methods for quantifying microbially generated heat in complex environments remain limited. Here, we present a low-cost digital temperature sensing system integrated into an Arduino...
Using a geographic transect in Central Mexico, with an elevation/climate gradient, but uniformity in socio-economic conditions among study sites, this study evaluates the applicability of three widely-used remote sensing (RS) products to link weather...
This observation-based and explainable approach demonstrates the applicability of multi-source remote sensing for flood assessment in data-scarce regions, offering a robust scientific basis for flood management and spatial planning in monsoon-affecte...
The nonlinear radiation distortions (NRD) among multimodal remote sensing images bring enormous challenges to image registration. The traditional feature-based registration methods commonly use the image intensity or gradient information to detect an...
Automatic building extraction from high-resolution remotely sensed data is a major area of interest for an extensive range of fields (e.g., urban planning, environmental risk management) but challenging due to urban morphology complexity. Among the d...
Soil organic carbon (SOC) is a key property for evaluating soil quality. SOC is thus an important parameter of agricultural soils and needs to be regularly monitored. The aim of this study is to explore the potential of synthetic aperture radar (SAR)...
Recently, piezoresistive-type (PRT) pressure sensors have been gaining attention in variety of applications due to their simplicity, low cost, miniature size and ruggedness. The electrical behavior of a pressure sensor is highly dependent on the temp...
Empirically based approaches, like the Universal Soil Loss Equation (USLE), are appropriate for estimating mass movement attributed to rill erosion. USLE and its associates become widespread even in spatially extended studies in spite of its original...
Soil organic matter (SOM) plays pivotal roles in characterizing dryland structure and function; however, remotely sensed spatially-detailed SOM mapping in these regions remains a challenge. Various digital soil mapping approaches based on either sing...
The accurate prediction of soil organic carbon (SOC) is important for agriculture and land management. Methods using remote sensing data are helpful for estimating SOC in bare soils. To overcome the challenge of predicting SOC under vegetation cover,...
Point cloud filtering is a crucial step in most airborne light detection and ranging (LiDAR) applications. Many filtering algorithms have been proposed, but the filtering effect has some limitations in complex environments. To improve the filtering e...
Grassland ecosystems provide a range of services in semi-arid and arid regions. However, they have significantly declined due to overgrazing and desertification. In the current study, we employed Landsat time series data (TM, OLI, OLI-2) spanning fro...
Monitoring of river discharge is a key process for water resources management, soil and water conservation, climate change, water cycling, flood or drought warning, agriculture and transportation, especially for the sustainable development of rivers...
Snow and ice melting in the Upper Indus Basin (UIB) is crucial for regional water availability for mountainous communities. We analyzed glacier changes in the Astak catchment, UIB, from 2000 to 2020 using remote sensing techniques based on optical sa...
Diabetes mellitus is a widespread chronic metabolic disorder that requires regular blood glucose level surveillance. Current invasive techniques, such as finger-prick tests, often result in discomfort, leading to infrequent monitoring and potential h...
Annual mass balance is an important reflection of glacier status that is also very sensitive to climate fluctuations. However, there is no effective and universal albedo-based method for the reconstruction of annual mass balance due to the scarcity o...
Climate change and anthropopression significantly impact plant communities by leading to the spread of expansive and alien invasive plants, thus reducing their biodiversity. Due to significant elevation gradients, high-mountain plant communities in a...
Mangrove forests provide numerous valuable ecosystem services and can sequester a large volume of carbon that can help mitigate climate change impacts. Modeling mangrove carbon with robust and valid approaches is crucial to better understanding exist...
The aim of this study was to find strains in embedded reinforcement by monitoring surface deformations. Compared with analytical methods, application of the machine learning regression technique imparts a noteworthy reduction in modeling complexity c...
The Kravarsko area is located in a hilly region of northern Croatia, where numerous landslides endanger and damage houses, roads, water systems, and power lines. Nevertheless, natural hazard management plans are practically non-existent. Therefore, d...
The vegetation of the Qinghai–Tibet Plateau (QTP) is vital to the global climate change and ecological security of China. However, the impact of climate variation on the spatial pattern and zonal distribution of vegetation in the QTP remains unclear....
We utilized remote sensing and ground cover data to predict soil organic carbon (SOC) content across a vast geographic region. Employing a combination of machine learning and deep learning techniques, we developed a novel data fusion approach that in...
Spatial mapping of potential geothermal areas is an effective tool for a preliminary investigation and the development of a clean and renewable energy source around the globe. Specific locations within the Earth’s crust display some manifestations of...
Facial expression is an important way to reflect human emotions and it represents a dynamic deformation process. Analyzing facial movements is an effective means of understanding expressions. However, there is currently a lack of methods capable of a...
The mid-wave infrared (MWIR) spectral range can provide a larger bandwidth for optical sensing and communication when the near-infrared band becomes congested. This range of thermal signatures can provide more information for digital imaging and obje...
The alpine treeline, as an ecological transition zone between montane coniferous forests and alpine meadows (two ecosystem states), is a research hotspot of global ecology and climate change. Quantitative identification of its elevation range can eff...
Arid and semi-arid regions serve as crucial ecological barriers in China, making the spatiotemporal evolution of their ecological environmental quality (EEQ) scientifically significant. This study developed a Modified Remote Sensing Ecological Index...
Low-gradient agricultural areas prone to in-field flooding impact crop development and yield potential, resulting in financial losses. Early identification of the potential reduction in yield from excess water stress at the plot scale provides stakeh...
Satellite-based soil organic carbon content (SOC) mapping over wide regions is generally hampered by the low soil sampling density and the diversity of soil sampling periods. Some unfavorable topsoil conditions, such as high moisture, rugosity, the p...
Hyperspectral technology offers significant potential for non-invasive monitoring and prediction of morphological parameters in plants. In this study, UV−VIS−NIR−SWIR reflectance hyperspectral data were collected from Nicotiana taba...
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