63 Results Found

The need to maintain soil health and produce more food worldwide has increased, and soil analysis is essential for its management. Although spectroscopy has emerged as an important tool, it is important to focus primarily on predictive modeling proce...

This paper proposes a method based on key parameter monitoring and a backpropagation neural network to standardize LIBS spectra, named KPBP. By monitoring the laser output energy and the plasma flame morphology and using the backpropagation neural ne...

Proximal sensing offers a novel means for determination of the heavy metal concentration in soil, facilitating low cost and rapid analysis over large areas. In this respect, spectral data and model variables play an important role. Thus far, no attem...

Depending on the band position on the electromagnetic spectrum, optical and electronic characteristics, sensors collect the reflected energy by the Earth’s surface and the atmosphere. Currently, the availability of the new generation of medium...

In this study, we examined the potential of vis-NIR reflectance spectroscopy, coupled with partial least squares regression (PLSR) analysis, for the evaluation and prediction of soil water retention at field capacity (FC) and permanent wilting point...

The detection of available Cr(VI) in soil is critical due to its high uptake by plants, which enables it to enter the food chain and pose significant health risks to humans. Traditional detection methods are often time-consuming and labor-intensive,...

Carbon sequestration in soils under agricultural use can contribute to climate change mitigation. Spatial–temporal soil organic carbon (SOC) monitoring requires more efficient data acquisition. This study aims to evaluate the potential of spect...

Soil organic matter (SOM) and total nitrogen (TN) are critical indicators for assessing soil fertility. Although laboratory chemical analysis methods can accurately measure their contents, these techniques are time-consuming and labor-intensive. Spec...

Soil nitrate nitrogen (NO3−-N) is a key indicator of agricultural non-point source pollution. The ultraviolet (UV) dual-wavelength method is widely used for NO3−-N detection, but interference from complex soil organic matter affects its a...

In this study, a regression model of paddy soil properties using diffuse reflectance spectroscopy was developed to replace chemical soil analysis as a more efficient alternative. Soil samples were collected and analyzed from saltwater paddy fields lo...

Rapid and green detection of soil nutrients is essential for soil fertility and plant growth. However, traditional methods cannot meet the needs of rapid detection, and the reagents easily cause environmental pollution. Hence, we proposed a multivari...

Cadmium (Cd) pollution in soil is a serious threat to food security and human health, while, currently, the most widely used detection methods cannot accurately reflect the content of heavy metals in soil. Soil heavy metal detection combined with mic...

Chromium is not only an essential trace element for the growth and development of living organisms; it is also a heavy metal pollutant. Excessive chromium in farmland soil will not only cause harm to crops, but could also constitute a serious threat...

Adequate soil information to adapt fertilizer plans and support farmers’ yield ambitions is either hard to obtain or expensive, as it often requires soil sampling and analyses in a lab. AgroCares has developed two services, i.e., the Scanner an...

Energy-dispersive X-ray fluorescence spectrometry (EDXRF) is a rapid and inexpensive method for soil analysis; however, analytical results are influenced by particle size effects and spectral interferences. The objective of this study was to optimise...

Clay minerals play an important role in shrinking–swelling of soils and off–road vehicle mobility mainly due to the presence of smectites including montmorillonites. Since soils are composed of different minerals intimately mixed, an accu...

The aim of this study was to determine the extent to which Sentinel-2 Normalised Difference Vegetation Index (NDVI) reflects soil moisture conditions, and whether this product offers an improvement over Landsat-8. Based on drought exposure, cloud-fre...

Soil salinity due to irrigation diversion affects regional agriculture, and the development of soil composition estimation models for the dynamic monitoring of regional salinity is important for salinity control. In this study, we evaluated the perfo...

Reflectance spectroscopy for soil property prediction is a non-invasive, fast, and cost-effective alternative to the standard laboratory analytical procedures. Soil spectroscopy has been under study for decades now with limited application outside re...

Developing rapid and non-destructive methods for chlorophyll estimation over large spatial areas is a topic of much interest, as it would provide an indirect measure of plant photosynthetic response, be useful in monitoring soil nitrogen content, and...

Soil organic matter is an important component that reflects soil fertility and promotes plant growth. The soil of typical Chinese tea plantations was used as the research object in this work, and by combining soil hyperspectral data and image texture...

Rapid detection of soil nutrient elements is beneficial to the evaluation of crop yield, and it’s of great significance in agricultural production. The aim of this work was to compare the detection ability of single-pulse (SP) and collinear double-pu...

The emergence of new-generation hyperspectral satellites offers more potential for mapping soil properties. This study presents the first assessment of EnMAP (Environmental Mapping and Analysis Program) hyperspectral imagery for soil organic matter (...

Studying efficient and accurate soil heavy-metal detection technology is of great significance to establishing a modern system for monitoring soil pollution, early warning and risk assessment, which contributes to the continuous improvement of soil q...

Laboratory spectroscopy has proved its reliability for estimating soil organic carbon (SOC) by exploiting the relationship between electromagnetic radiation and key spectral features of organic carbon located in the VIS-NIR-SWIR (350–2500 nm) r...

Improper use of land resources may result in severe soil salinization. Timely monitoring and early warning of soil salinity is in urgent need for sustainable development. This paper addresses the possibility and potential of Advanced Land Imager (ALI...

Near-Infrared Spectroscopy is a cost-effective and environmentally friendly technique that could represent an alternative to conventional soil analysis methods, including total organic carbon (TOC). Soil fertility and quality are usually measured by...

The recent developments in the performance and miniaturization of uncrewed aircraft systems (UAS) and multispectral imaging sensors provide new tools for the assessment of the spatial and temporal variability of soil properties at sub-meter resolutio...

This study investigated the abilities of pre-processing, feature selection and machine-learning methods for the spectroscopic diagnosis of soil arsenic contamination. The spectral data were pre-processed by using Savitzky-Golay smoothing, first and s...

Old and abandoned mines are testimonials of ancient industrial activities, and as such, they are able to convey environmental concerns. A multidisciplinary approach combining ground measurements—i.e., portable X-ray fluorescence and optical spe...

Tectona grandis Linn., also known as teak, is a highly valued species with adaptability to a wide range of climatic conditions and high tolerance to soil variations, making it an attractive option for both commercial and conservation purposes. In thi...

The characterization of vineyard soil is a key issue for crop management, which directly affects the quality and yield of grapes. However, traditional laboratory analysis of soil properties is tedious and both time and cost consuming, which is not su...

Soil nitrogen (N) is a crucial nutrient for agricultural productivity and ecosystem health. The accurate and timely assessment of total soil N is essential for evaluating soil health. This study aimed to determine the impact of bootstrapping techniqu...

The possibility of quantitative inversion of salinized soil moisture content (SMC) from Zhuhai-1 hyperspectral imagery and the application effect of fractional order differentially optimized spectral indices were discussed, which provided new researc...

The fusion of Raman and visible–near-infrared (VIS–NIR) spectroscopy provides a promising pathway for rapid and non-destructive soil analysis. However, conventional fusion strategies often fail to properly balance modality discrepancies a...

Synergistic applications of multi-resolution satellite data have been of a great interest among user communities for the development of an improved and more effective operational monitoring system of natural resources, including vegetation and soil....

Heat stress (HS) and water stress (WS) pose severe threats to viticulture, and effective management solutions to counter their effects on grapevine performance must be examined. In this study, we evaluated the physiological and spectral responses of...

An increasing demand for full spatio-temporal coverage of soil information drives the growing use of soil spectroscopy. Soil spectroscopy application performed under laboratory conditions or in-field studies in semi-arid areas have shown promising re...

This paper examines the climate change impact on the spatiotemporal soil salinity dynamics during the last 30 years (1987–2017) in the arid landscape. The state of Kuwait, located at the northwest Arabian Peninsula, was selected as a pilot stud...

Current challenges in collecting and analyzing subway vibration data include the absence of standardized data collection methods, limitations in data analysis techniques, and an unclear understanding of the effects of geological conditions on vibrati...

We propose a dynamic monitoring and precision fertilization decision system for agricultural soil nutrients, integrating UAV remote sensing and GIS technologies to address the limitations of traditional soil nutrient assessment methods. The proposed...

Slope uncertainty predominantly originates from the imperfect analysis model and the inaccuracy and imprecision of the observations. The strength reduction method (SRM) is widely used to attain the safety factor (SF) of the slopes, which is similar t...

After the M = 7.0 Haiti earthquake in 2010, many teams completed seismic risk studies in Port-au-Prince to better understand why this not extraordinarily strong event had induced one of the most severe earthquake disasters in history (at least in the...

Tea Anthracnose (TA), caused by fungi of the genus Colletotrichum, is one of the major threats to global tea production. UAV remote sensing has been explored for non-destructive and high-efficiency monitoring of diseases in tea plantations. However,...

Remote sensing data has been widely used for various Earth Observation (EO) missions such as land use and cover classification, weather forecasting, agricultural management, and environmental monitoring. Most existing remote-sensing-data-based models...

Hyperspectral detection of the change rate of organic matter content in agricultural remote sensing requires a high signal-to-noise ratio (SNR). However, due to the large number and efficiency limitation of the components, it is difficult to improve...

Geophysical surveys are widely used to reconstruct subsoil seismo-stratigraphic structures with a non-invasive approach. In this study the geophysical surveys were carried out with the aim to characterise the San Giorgio Cathedral in Ragusa (Italy) a...

Vs30, the average shear wave velocity in the uppermost 30 m, is a critical parameter in seismic hazard analysis. In the Philippines, the Refraction Microtremor (ReMi) survey is the standard method for Vs30 Estimation. This study evaluates the efficie...

Vibration assessment of upland crop machinery under development is essential because high vibrational exposures affect machine efficiency, service life of components, degradation of the working environment, and cause health risks to the operator. It...

Cotton is a vital economic crop in global agriculture and the textile industry, contributing significantly to food security, industrial competitiveness, and sustainable development. Traditional technologies such as spectral imaging and machine learni...