Soil Organic Carbon (SOC) is a useful representative of soil fertility and an essential parameter in controlling the dynamics various agrochemicals soil. texture also used to calculate soil's ability retain water for plant growth. SOC are thus important parameters agricultural soils need be regularly monitored. Optical satellite remote sensing offers potential frequent surveys over large areas. In addition, recently-operated Sentinel-2 missions provide free imagery. This study compared...

Abstract Demands of aquatic products are increasing dramatically during past decades. Also quality assurance has gradually received more attention by both producers and consumers. Thus, fish exploring all possible approaches for improving the productivity profitability. Monitoring state behaviour cultivation may help to improve profitability also reduce threat severe loss because disease stress incidents. It is necessary evaluate measure in accurate, fast objective way meeting different...

The lands near mining industries in the Czech Republic are subjected to soil pollution with heavy metals. Excessive metal concentrations soils not only dramatically impact quality, but also due their persistent nature and indefinite biological half-lives, potentially toxic metals can accumulate food chain eventually endanger human health. Monitoring spatial information of these elements require a large number samples cumbersome time-consuming laboratory measurements. A faster method has been...

Chlorophyll-a (Chl-a) and Total Suspended Solids (TSS) are both key indicators of the biophysical status inland waters, their continued monitoring is essential. Existing conventional methods (e.g., in situ monitoring) have shown that they impractical due to time space limitations. The recently operated Sentinel-2A satellite offers potential higher temporal, spatial, spectral resolution images with no cost for water quality parameters waters. main aim this study was develop a semi-empirical...

The optimum rate and application timing of Nitrogen (N) fertilizer are crucial in achieving a high yield rice cultivation; however, conventional laboratory testing plant nutrients is time-consuming expensive. To develop site-specific spatial variable method to overcome the limitations traditional techniques, especially fields under double-cropping system, this study focused on relationship between Soil Plant Analysis Development (SPAD) chlorophyll meter readings N content leaves during...

Soil degradation includes a number of processes, ranging from soil erosion to contamination, which reduce the capability work as base for vegetation roots. Methods quantify due contamination on large area with proper domain are needed and must be studied developed. Proximal remote sensing techniques essential tools, well-suited surveying areas, monitoring at high temporal spatial interval. Recently developed forthcoming satellites also dedicated land provide inimitable data streams, have...

There is a need to update soil maps and monitor organic carbon (SOC) in the upper horizons or plough layer for enabling decision support land management, while complying with several policies, especially those favoring storage. This review paper dedicated satellite-based spectral approaches SOC assessment that have been achieved from satellite sensors, study scales geographical contexts past decade. Most relying on pure models carried out since 2019 dealt temperate croplands Europe, China...

In order to monitor Potentially Toxic Elements (PTEs) in anthropogenic soils on brown coal mining dumpsites, a large number of samples and cumbersome, time-consuming laboratory measurements are required. Due its rapidity, convenience accuracy, reflectance spectroscopy within the Visible-Near Infrared (Vis-NIR) region has been used predict soil constituents. This study evaluated suitability Vis-NIR (350–2500 nm) for predicting PTEs concentration, using collected dumpsites Czech Republic....

The main aim of this study was to develop a new objective method for evaluating the impacts different diets on live fish skin using image-based features. In total, one-hundred and sixty rainbow trout (Oncorhynchus mykiss) were fed either fish-meal based diet (80 fish) or 100% plant-based photographed consumer-grade digital camera. Twenty-three colour features four texture extracted. Four classification methods used evaluate including Random forest (RF), Support vector machine (SVM), Logistic...

Soil organic carbon (SOC) is a variable of vital environmental significance in terms soil quality and function, global food security, climate change mitigation. Estimation its content prediction accuracy on broader scale remain crucial. Although, spectroscopy under proximal sensing remains one the best approaches to accurately predict SOC, however, limitation estimate SOC larger spatial concern. Therefore, for an efficient quantification content, faster less costly techniques are needed,...

Soil organic carbon (SOC) distribution and interaction with light is influenced by soil texture parameters (clay, silt sand), which makes SOC prediction complicated, especially in samples considerable pedological variability. Hence, understanding the relationship between important within context of using remote sensing data. The main objective this study was to find impact on performance local models that were developed Sentinel-2 (S2) multispectral CASI/SASI (CS) hyperspectral airborne data...

Successful determination of soil texture using reflectance spectroscopy across Visible and Near-Infrared (VNIR, 400–1200 nm) Short-Wave-Infrared (SWIR, 1200–2500 ranges depends largely on the selection a suitable data mining algorithm. The objective this research was to explore whether new Memory-Based Learning (MBL) method performs better than other methods, namely: Partial Least Squares Regression (PLSR), Support Vector Machine (SVMR) Boosted Trees (BRT). For purpose, we chose (contents...

Weeds are among the most harmful abiotic factors in agriculture, triggering significant yield loss worldwide. Remote sensing can detect and map presence of weeds various spectral, spatial, temporal resolutions. This review aims to show current future trends UAV applications weed detection crop field. study systematically searched original articles published from 1 January 2016 18 June 2021 databases Scopus, ScienceDirect, Commonwealth Agricultural Bureaux (CAB) Direct, Web Science (WoS)...

The monitoring and quantification of soil carbon provide a better understanding atmosphere dynamics. Visible-near-infrared-short-wave infrared (VIS-NIR-SWIR) reflectance spectroscopy can quantitatively estimate content more rapidly cost-effectively compared to traditional laboratory analysis. However, effective estimation using great extent depends on the selection suitable preprocessing sequence data-mining algorithm. Many efforts have been dedicated comparison conventional chemometric...

Soil contamination by potentially toxic elements (PTEs) is intensifying under increasing industrialization. Thus, the ability to efficiently delineate contaminated sites crucial. Visible–near infrared (vis–NIR: 350–2500 nm) and X-ray fluorescence (XRF: 0.02–41.08 keV) spectroscopic techniques have attracted tremendous attention for assessment of PTEs. Recently, application fused vis–NIR XRF spectroscopy, which based on complementary effect data fusion, also increasing. Moreover, different...

Abstract Precision fish farming is an emerging concept in aquaculture research and industry, which combines new technologies data processing methods to enable data-based decision making farming. The based on the automated monitoring of fish, infrastructure, environment ideally by contactless methods. identification individual same species within cultivated group critical for individualized treatment, biomass estimation state determination. A few studies have shown that body patterns can be...

Our study investigates the capability of environmental mapping and analysis program (EnMAP) scenes simulated using EnMAP end-to-end simulator software (EeteS) based on AISA Eagle airborne data to predict chlorophyll-a (Chl-a) total suspended solids (TSS) as two most crucial water quality indicators. Three machine learning (ML) approaches (principal component regression(PCR), partial least square regression (PLSR) random forest (RF)) were employed establish links between image spectra...