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Diffuse reflectance spectroscopy for estimating soil properties: A technology for the 21st century
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/ldr.2887openalex-snapshot
The cost‐efficiency and reliability of two methods for soil organic C accounting
inferredcites →https://doi.org/10.1007/978-0-387-84858-7openalex-snapshot
The Elements of Statistical Learning: Data Mining, Inference, and Prediction
inferredcites →https://doi.org/10.1007/s10705-019-10041-0openalex-snapshot
Soil carbon simulation confounded by different pool initialisation
inferredcites →https://doi.org/10.1007/s11104-007-9489-9openalex-snapshot
Near infrared reflectance spectroscopy compared with soil clay and organic matter content for estimating within-field variation in N uptake in cereals
inferredcites →https://doi.org/10.1016/0584-8539(90)80069-bopenalex-snapshot
Multivariate calibration
inferredcites →https://doi.org/10.1016/j.aca.2018.04.004openalex-snapshot
Near infrared spectroscopy: A mature analytical technique with new perspectives – A review
inferredcites →https://doi.org/10.1016/j.agsy.2016.07.001openalex-snapshot
Soil sensing: A new paradigm for agriculture
inferredcites →https://doi.org/10.1016/j.earscirev.2016.01.012openalex-snapshot
A global spectral library to characterize the world's soil
inferredcites →https://doi.org/10.1016/j.geoderma.2005.01.001openalex-snapshot
Validation requirements for diffuse reflectance soil characterization models with a case study of VNIR soil C prediction in Montana
inferredcites →https://doi.org/10.1016/j.geoderma.2005.03.007openalex-snapshot
Visible, near infrared, mid infrared or combined diffuse reflectance spectroscopy for simultaneous assessment of various soil properties
inferredcites →https://doi.org/10.1016/j.geoderma.2005.04.025openalex-snapshot
Global soil characterization with VNIR diffuse reflectance spectroscopy
inferredcites →https://doi.org/10.1016/j.geoderma.2009.12.021openalex-snapshot
Spiking of NIR regional models using samples from target sites: Effect of model size on prediction accuracy
inferredcites →https://doi.org/10.1016/j.geoderma.2009.12.025openalex-snapshot
Using data mining to model and interpret soil diffuse reflectance spectra
inferredcites →https://doi.org/10.1016/j.geoderma.2011.09.008openalex-snapshot
Removing the effect of soil moisture from NIR diffuse reflectance spectra for the prediction of soil organic carbon
inferredcites →https://doi.org/10.1016/j.geoderma.2012.12.014openalex-snapshot
The spectrum-based learner: A new local approach for modeling soil vis–NIR spectra of complex datasets
inferredcites →https://doi.org/10.1016/j.geoderma.2015.06.023openalex-snapshot
Mapping of soil properties and land degradation risk in Africa using MODIS reflectance
inferredcites →https://doi.org/10.1016/j.geoderma.2015.11.016openalex-snapshot
Baseline estimates of soil organic carbon by proximal sensing: Comparing design-based, model-assisted and model-based inference
inferredcites →https://doi.org/10.1016/j.geoderma.2020.114616openalex-snapshot
Combination of Convolutional Neural Networks and Recurrent Neural Networks for predicting soil properties using Vis–NIR spectroscopy
inferredcites →https://doi.org/10.1016/j.geoderma.2021.115069openalex-snapshot
Use of composite samples and NIR spectroscopy to detect changes in SOC contents
inferredcites →https://doi.org/10.1016/j.geoderma.2021.115071openalex-snapshot
Prediction of various soil properties for a national spatial dataset of Scottish soils based on four different chemometric approaches: A comparison of near infrared and mid-infrared spectroscopy
inferredcites →https://doi.org/10.1016/j.geoderma.2021.115366openalex-snapshot
Soil properties: Their prediction and feature extraction from the LUCAS spectral library using deep convolutional neural networks
inferredcites →https://doi.org/10.1016/j.isprsjprs.2022.04.009openalex-snapshot
Deep transfer learning of global spectra for local soil carbon monitoring
inferredcites →https://doi.org/10.1016/j.jhazmat.2014.11.006openalex-snapshot
Response to “Visible and near-infrared reflectance spectroscopy is of limited practical use to monitor soil contamination by heavy metals” by Philippe C. Baveye
inferredcites →https://doi.org/10.1016/j.jhazmat.2014.11.043openalex-snapshot
Visible and near-infrared reflectance spectroscopy is of limited practical use to monitor soil contamination by heavy metals
inferredcites →https://doi.org/10.1016/j.spasta.2022.100639openalex-snapshot
Spatial statistics and soil mapping: A blossoming partnership under pressure
inferredcites →https://doi.org/10.1016/j.still.2015.07.008openalex-snapshot
Do we really need large spectral libraries for local scale SOC assessment with NIR spectroscopy?
inferredcites →https://doi.org/10.1016/s0065-2113(10)07005-7openalex-snapshot
Visible and Near Infrared Spectroscopy in Soil Science
inferredcites →https://doi.org/10.1016/s0169-7439(01)00155-1openalex-snapshot
PLS-regression: a basic tool of chemometrics
inferredcites →https://doi.org/10.1021/acs.est.7b00889openalex-snapshot
Novel Proximal Sensing for Monitoring Soil Organic C Stocks and Condition
inferredcites →https://doi.org/10.1021/es504272xopenalex-snapshot
In Situ Measurements of Organic Carbon in Soil Profiles Using vis-NIR Spectroscopy on the Qinghai–Tibet Plateau
inferredcites →https://doi.org/10.1029/2009jf001645openalex-snapshot
Mapping iron oxides and the color of Australian soil using visible–near‐infrared reflectance spectra
inferredcites →https://doi.org/10.1029/2011jf001977openalex-snapshot
Fine-resolution multiscale mapping of clay minerals in Australian soils measured with near infrared spectra
inferredcites →https://doi.org/10.1029/jb095ib08p12653openalex-snapshot
High spectral resolution reflectance spectroscopy of minerals
inferredcites →https://doi.org/10.1038/d41586-022-00858-1openalex-snapshot
Breaking into the black box of artificial intelligence
inferredcites →https://doi.org/10.1038/s41598-020-80486-9openalex-snapshot
Automated spectroscopic modelling with optimised convolutional neural networks
inferredcites →https://doi.org/10.1038/s41598-021-96772-zopenalex-snapshot
Wavelet geographically weighted regression for spectroscopic modelling of soil properties
inferredcites →https://doi.org/10.1038/s42256-020-00265-zopenalex-snapshot
Concept whitening for interpretable image recognition
inferredcites →https://doi.org/10.1071/ea97144openalex-snapshot
Can mid infrared diffuse reflectance analysis replace soil extractions?
inferredcites →https://doi.org/10.1071/sr14366openalex-snapshot
The Australian three-dimensional soil grid: Australia’s contribution to the GlobalSoilMap project
inferredcites →https://doi.org/10.1071/sr9910049openalex-snapshot
Diffuse reflectance infrared fourier transform (DRIFT) spectroscopy in soil studies
inferredcites →https://doi.org/10.1071/sr9950621openalex-snapshot
Characterization and analysis of soils using mid-infrared partial least-squares .1. Correlations with XRF-determined major-element composition
inferredcites →https://doi.org/10.1080/05704928.2013.811081openalex-snapshot
The Performance of Visible, Near-, and Mid-Infrared Reflectance Spectroscopy for Prediction of Soil Physical, Chemical, and Biological Properties
inferredcites →https://doi.org/10.1080/05704929608000571openalex-snapshot
Interpretive Spectroscopy for Near Infrared
inferredcites →https://doi.org/10.1080/14697688.2019.1626475openalex-snapshot
The Art of Statistics: Learning from Data
inferredcites →https://doi.org/10.1097/00010694-196508000-00009openalex-snapshot
REFLECTION OF RADIANT ENERGY FROM SOILS
inferredcites →https://doi.org/10.1111/ejss.12129openalex-snapshot
Assessment of soil organic carbon at local scale with spiked NIR calibrations: effects of selection and extra‐weighting on the spiking subset
inferredcites →https://doi.org/10.1111/ejss.12237openalex-snapshot
Soil organic carbon and its fractions estimated by visible–near infrared transfer functions
inferredcites →https://doi.org/10.1111/ejss.12239openalex-snapshot
Accounting for the effects of water and the environment on proximally sensed vis– NIR soil spectra and their calibrations
inferredcites →https://doi.org/10.1111/ejss.12362openalex-snapshot
Prediction of soil organic and inorganic carbon at different moisture contents with dry ground VNIR : a comparative study of different approaches
inferredcites →https://doi.org/10.1111/ejss.12490openalex-snapshot
rs‐local data‐mines information from spectral libraries to improve local calibrations
inferredcites →https://doi.org/10.1111/ejss.12752openalex-snapshot
Robust soil mapping at the farm scale with vis–NIR spectroscopy
inferredcites →https://doi.org/10.1111/ejss.13137openalex-snapshot
Statistical modelling of measurement error in wet chemistry soil data
inferredcites →https://doi.org/10.1111/ejss.13192openalex-snapshot
Estimating soil chemical properties by diffuse reflectance spectroscopy: Promise versus reality
inferredcites →https://doi.org/10.1111/ejss.13202openalex-snapshot
The cost‐effectiveness of reflectance spectroscopy for estimating soil organic carbon
inferredcites →https://doi.org/10.1111/ejss.13220openalex-snapshot
Modelling soil water retention and water‐holding capacity with visible–near‐infrared spectra and machine learning
inferredcites →https://doi.org/10.1111/j.1365-2389.2009.01121.xopenalex-snapshot
Improved analysis and modelling of soil diffuse reflectance spectra using wavelets
inferredcites →https://doi.org/10.1111/j.1365-2389.2010.01283.xopenalex-snapshot
Near‐infrared spectroscopy for within‐field soil characterization: small local calibrations compared with national libraries spiked with local samples
inferredcites →https://doi.org/10.1111/j.1365-2389.2012.01495.xopenalex-snapshot
Predicting soil properties from the Australian soil visible–near infrared spectroscopic database
inferredcites →https://doi.org/10.1111/j.1475-2743.2011.00337.xopenalex-snapshot
Optical sensing and chemometric analysis of soil organic carbon – a cost effective alternative to conventional laboratory methods?
inferredcites →https://doi.org/10.1111/j.2044-8317.1957.tb00179.xopenalex-snapshot
THE RELATIONS OF THE NEWER MULTIVARIATE STATISTICAL METHODS TO FACTOR ANALYSIS
inferredcites →https://doi.org/10.1126/scirobotics.aay7120openalex-snapshot
XAI—Explainable artificial intelligence
inferredcites →https://doi.org/10.1137/0905052openalex-snapshot
The Collinearity Problem in Linear Regression. The Partial Least Squares (PLS) Approach to Generalized Inverses
inferredcites →https://doi.org/10.1255/jnirs.1233openalex-snapshot
Using Variable Selection and Wavelets to Exploit the Full Potential of Visible–Near Infrared Spectra for Predicting Soil Properties
inferredcites →https://doi.org/10.1255/jnirs.399openalex-snapshot
204 Years of near Infrared Technology: 1800–2003
inferredcites →https://doi.org/10.1371/journal.pone.0066409openalex-snapshot
Prediction of Soil Organic Carbon at the European Scale by Visible and Near InfraRed Reflectance Spectroscopy
inferredcites →https://doi.org/10.2135/cropsci1991.0011183x003100020049xopenalex-snapshot
Population Definition, Sample Selection, and Calibration Procedures for Near Infrared Reflectance Spectroscopy
inferredcites →https://doi.org/10.2136/sssaj1995.03615995005900020014xopenalex-snapshot
Near‐Infrared Analysis as a Rapid Method to Simultaneously Evaluate Several Soil Properties
inferredcites →https://doi.org/10.2136/sssaj2002.7220openalex-snapshot
Moisture Effects on Soil Reflectance
inferredcites →https://doi.org/10.2136/sssaj2002.9880openalex-snapshot
Development of Reflectance Spectral Libraries for Characterization of Soil Properties
inferredcites →https://doi.org/10.2136/sssaj2017.10.0361openalex-snapshot
Predicting Physical and Chemical Properties of US Soils with a Mid‐Infrared Reflectance Spectral Library
inferredcites →https://doi.org/10.3390/s18093169openalex-snapshot
Transfer Learning for Soil Spectroscopy Based on Convolutional Neural Networks and Its Application in Soil Clay Content Mapping Using Hyperspectral Imagery
inferredcites →https://doi.org/10.5194/bg-18-5185-2021openalex-snapshot
Assessing the response of soil carbon in Australia to changing inputs and climate using a consistent modelling framework
inferredcites →https://doi.org/10.5194/soil-4-101-2018openalex-snapshot
Proximal sensing for soil carbon accounting
inferredcites →https://doi.org/10.5194/soil-4-259-2018openalex-snapshot
Spatial assessments of soil organic carbon for stakeholder decision-making – a case study from Kenya
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Measuring in Situ Soil Carbon Stocks at Scale: A Study Using a Novel Handheld Visnir Probe
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The Influence of the Location of Arable Land Incorporating Its Roughness on the Optimal Time When the Land Reaches its Mean Diurnal Blue-Sky Albedo Value Incorporating
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Novel Insights on Multivariate Modelling of Agricultural Soil Organic Carbon and Total Nitrogen from Diverse Ft-Nir Spectral Dataset
inferred← citeshttps://doi.org/10.2139/ssrn.4844779openalex-extracted
Enhancing Soil Profile Analysis with Global Soil Spectral Libraries and Laboratory Hyperspectral Imaging
inferred← citeshttps://doi.org/10.1002/jpln.70116openalex-snapshot
Infrared Spectroscopic Predictions of Soil Properties for Agricultural Monitoring: Statistical and Soil Spectroscopic Considerations
inferred← citeshttps://doi.org/10.1002/saj2.70034openalex-snapshot
Soil organic carbon measurements influence FT‐NIR model training in calcareous soils of Saskatchewan
inferred← citeshttps://doi.org/10.1002/saj2.70147openalex-snapshot
Application of calibration transfer techniques between different mid‐infrared spectrometers/modules to improve accuracy in estimating soil properties
inferred← citeshttps://doi.org/10.1007/978-981-97-7762-4_8openalex-snapshot
Deep Learning: A Catalyst for Sustainable Agriculture Transformation
inferred← citeshttps://doi.org/10.1007/s10333-026-01095-2openalex-snapshot
Vis-NIR spectroscopy for rapid soil carbon and nitrogen estimation in humid tropical landscape
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Mixed metal oxides derived from carbonate intercalated Mg−Al layered double hydroxide: role of the calcination on modifying the optical, electrical and dielectric properties
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Spatial Prediction of Soil Attributes from PRISMA Hyperspectral Imagery Using Wrapper Feature Selection and Ensemble Modeling
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Soil Organic Carbon Fractionation Assessment in Areas with High Fire Activity Using Diffuse Spectroscopy and Tree-Based Machine Learning Algorithms
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Effective spectral pre-processing methods enhance accuracy of soil property prediction by NIR spectroscopy
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Development of Neural Networks and Performance Appraisal of Supervised Learning Models for Predicting Organic Carbon in Soils Under Different Cropping Systems
inferred← citeshttps://doi.org/10.1007/s44211-025-00746-4openalex-snapshot
Quantification techniques of soil organic carbon: an appraisal
inferred← citeshttps://doi.org/10.1016/bs.agron.2026.03.009openalex-snapshot
Visible near infrared reflectance spectroscopy—Integral for soil information and research in the digital age
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Rethinking local spectral modelling: From per-query refitting to model libraries
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Application of portable VNIR and MIR spectroscopy for the analysis of physicochemical sediment characteristics and stratigraphy in drill cores of Holocene overbank deposits in Central Europe
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Spectroscopy-based models outperform pedotransfer functions for estimating soil hydraulic properties
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Mid-Infrared spectroscopy for soil organic carbon estimation. Part I: Global review and meta-analysis
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Machine learning prediction of soil carbon fractions using bulk-soil and fraction-specific MIR spectra: Is physical fractionation necessary?
inferred← citeshttps://doi.org/10.1016/j.xinn.2025.100839openalex-snapshot
Spectroscopic solutions for generating new global soil information
inferred← citeshttps://doi.org/10.1029/2024rg000836openalex-snapshot
Monitoring and Modeling the Soil‐Plant System Toward Understanding Soil Health
inferred← citeshttps://doi.org/10.1039/d3va00046jopenalex-snapshot
Large-scale measurement of soil organic carbon using compact near-infrared spectrophotometers: effect of soil sample preparation and the use of local modelling
inferred← citeshttps://doi.org/10.1080/00224561.2025.2528348openalex-snapshot
Estimation of soil organic carbon as a function of soil pretreatment and spectral features of radiometers within the visible and near-infrared spectra
inferred← citeshttps://doi.org/10.1080/00380768.2025.2558584openalex-snapshot
Predictive performance of mid-infrared FTIR spectroscopy and machine learning models for soil property estimation in Japan
inferred← citeshttps://doi.org/10.1080/01431161.2025.2593571openalex-snapshot
Determination of soil organic carbon and nutrients by diffuse spectrorradiometry in the Cerrado Mineiro region, Brazil: evaluation of strategies for calibration of hyperspectral models
inferred← citeshttps://doi.org/10.1080/01431161.2026.2686305openalex-snapshot
Advances in spectroscopic and machine learning approaches for estimating soil organic carbon and nitrogen: a comprehensive review
inferred← citeshttps://doi.org/10.1080/10095020.2024.2343021openalex-snapshot
Predicting soil nutrients with PRISMA hyperspectral data at the field scale: the Handan (south of Hebei Province) test cases
inferred← citeshttps://doi.org/10.1080/10106049.2026.2656536openalex-snapshot
Advancing soil property prediction: integration of Vis-NIR sensors' data and machine learning models for rapid and accurate analysis
inferred← citeshttps://doi.org/10.1080/17583004.2024.2410812openalex-snapshot
Towards a modular, multi-ecosystem monitoring, reporting and verification (MRV) framework for soil organic carbon stock change assessment
inferred← citeshttps://doi.org/10.1109/iatmsi68868.2026.11465991openalex-snapshot
Multi-Strategy Fused Transformer-CNN with PSO-Driven Optimization for Soil Properties Estimation from Hyperspectral Data
inferred← citeshttps://doi.org/10.1109/jstars.2023.3269078openalex-snapshot
Identification and Evolution of Soil Organic Carbon Density Caused by Coastal Rapid Siltation Based on Imaging Spectroscopy
inferred← citeshttps://doi.org/10.1111/ejss.13358openalex-snapshot
Diffuse reflectance spectroscopy ( DRS ) for rapid soil testing and soil quality assessment in smallholder farms
inferred← citeshttps://doi.org/10.1111/ejss.13394openalex-snapshot
Optimised use of data fusion and memory‐based learning with an Austrian soil library for predictions with infrared data
inferred← citeshttps://doi.org/10.1111/ejss.13438openalex-snapshot
Incorporating soil knowledge into machine‐learning prediction of soil properties from soil spectra
inferred← citeshttps://doi.org/10.1111/ejss.13508openalex-snapshot
Prediction of nitrogen, active carbon, and organic carbon‐to‐clay ratio in agricultural soils by in‐situ spectroscopy
inferred← citeshttps://doi.org/10.1111/ejss.70080openalex-snapshot
Artificial intelligence in soil science
inferred← citeshttps://doi.org/10.1111/ejss.70319openalex-snapshot
Organic Carbon and Texture Control Moisture Dependence of Soil Shortwave Infrared Reflectance
inferred← citeshttps://doi.org/10.1111/sum.12952openalex-snapshot
The use of visible and near‐infrared spectroscopy for in‐situ characterization of agricultural soil fertility: A proposition of best practice by comparing scanning positions and spectrometers
inferred← citeshttps://doi.org/10.1111/sum.70101openalex-snapshot
Assessing Soil Degradation in Agricultural Landscapes of Semi‐Arid Tropics Using Proximal and Remote Sensing‐Based Diffuse Reflectance Spectroscopy
inferred← citeshttps://doi.org/10.1134/s1064229323601841openalex-snapshot
Vis-NIR Spectroscopy for Soil Organic Carbon Assessment: A Meta-Analysis
inferred← citeshttps://doi.org/10.1177/27551857241266855openalex-snapshot
Effects of Sample Handling on Visible and Near-Infrared Soil Reflectance
inferred← citeshttps://doi.org/10.1186/s13595-025-01309-3openalex-snapshot
Integrated modelling approaches for estimating total organic carbon, total nitrogen, total phosphorus, and ash content in forest floor samples using ATR-FTIR spectroscopy
inferred← citeshttps://doi.org/10.1371/journal.pone.0296545openalex-snapshot
Open Soil Spectral Library (OSSL): Building reproducible soil calibration models through open development and community engagement
inferred← citeshttps://doi.org/10.1590/1807-1929/agriambi.v30n3e295260openalex-snapshot
Application of diffuse reflectance spectroscopy (NIR) related to soil electrical conductivity
inferred← citeshttps://doi.org/10.1590/1983-21252023v36n320rcopenalex-snapshot
Estimate of carbon stock in the soil via diffuse reflectance spectroscopy (vis/nir) air and orbital remote sensing
inferred← citeshttps://doi.org/10.17475/kastorman.2047416openalex-snapshot
Prediction of Soil Infiltration Rate From Soil Color Parameters in a Brown Forest Soil of Transitional Climate Zone
inferred← citeshttps://doi.org/10.19047/0136-1694-2025-124-70-90openalex-snapshot
Contemporary approaches to studying the structure of soil organic matter
inferred← citeshttps://doi.org/10.2139/ssrn.4984618openalex-snapshot
Enhancing Soil Property Prediction with Mid-Infrared Spectra: Fine Grinding Not Always Needed
inferred← citeshttps://doi.org/10.2139/ssrn.5257901openalex-snapshot
Improve the Hyperspectral Prediction of Soil Organic Matter Through Dynamic Weight Allocation and the Number of Optimal Model Integrations
inferred← citeshttps://doi.org/10.2139/ssrn.5266751openalex-snapshot
Optimising Satellite-Based Soil Spectra Extraction for Predicting Agricultural Soil Carbon Content Across Europe
inferred← citeshttps://doi.org/10.2139/ssrn.5374765openalex-snapshot
A Novel Transfer Learning Strategy Using Soil Spectral Library with Cnn-Transformer Model
inferred← citeshttps://doi.org/10.2139/ssrn.5638533openalex-snapshot
General research on soil spectral modeling based on CNN-Transformer hybrid architecture and transfer learning
inferred← citeshttps://doi.org/10.2139/ssrn.6253032openalex-snapshot
Site-independent calibration of in situ low-cost spectrometer measurements: A farm model to predict soil organic carbon and soil moisture
inferred← citeshttps://doi.org/10.2139/ssrn.6874850openalex-snapshot
An original hyperspectral soil transfer strategy framework for global thinking
inferred← citeshttps://doi.org/10.2139/ssrn.7471121openalex-snapshot
Enhancing soil property prediction from in-situ kinematic NIR spectroscopy through two combinatorial ratio (CoRa) transformations: A comprehensive investigation
inferred← citeshttps://doi.org/10.22541/essoar.171804479.91646868/v1openalex-snapshot
Tracking Soil Health: Monitoring and Modeling the Soil-Plant System
inferred← citeshttps://doi.org/10.31857/s0032180x23600695openalex-snapshot
Vis-NIR Spectroscopy for Soil Organic Carbon Assessment: Meta-Analysis
inferred← citeshttps://doi.org/10.33545/2618060x.2024.v7.i4g.595openalex-snapshot
Diffusive reflectance spectroscopy for precise analysis of soils: An overview
inferred← citeshttps://doi.org/10.3390/agriculture13101975openalex-snapshot
Estimation of Total Nitrogen Content in Topsoil Based on Machine and Deep Learning Using Hyperspectral Imaging
inferred← citeshttps://doi.org/10.3390/agriculture14122145openalex-snapshot
Enhancing Regional Topsoil Total Nitrogen Mapping Through Differentiated Fusion of Ground Hyperspectral Data and Satellite Images Under Low Vegetation Cover
inferred← citeshttps://doi.org/10.3390/agronomy13071800openalex-snapshot
Advancing Soil Organic Carbon and Total Nitrogen Modelling in Peatlands: The Impact of Environmental Variable Resolution and vis-NIR Spectroscopy Integration
inferred← citeshttps://doi.org/10.3390/agronomy15071574openalex-snapshot
Estimating Soil Cd Contamination in Wheat Farmland Using Hyperspectral Data and Interpretable Stacking Ensemble Learning
inferred← citeshttps://doi.org/10.3390/app142411687openalex-snapshot
Spectral Data-Driven Prediction of Soil Properties Using LSTM-CNN-Attention Model
inferred← citeshttps://doi.org/10.3390/app15031522openalex-snapshot
Predicting Dye Formulations and Ultrasonic Pretreatment Power in Wood Staining with a SAT Fusion-Gated BiLSTM Model Optimized by Improved Dung Beetle Algorithm
inferred← citeshttps://doi.org/10.3390/f17080954openalex-snapshot
Cross-Site Prediction of Soil Organic Carbon in Plantation Forests Using Vis-NIR Spectroscopy and Target-Spectrum-Guided Source-Domain Weighting
inferred← citeshttps://doi.org/10.3390/land11122178openalex-snapshot
Developing Management Practices in: “Living Labs” That Result in Healthy Soils for the Future, Contributing to Sustainable Development
inferred← citeshttps://doi.org/10.3390/land11122188openalex-snapshot
Prediction of Soil Erodibility by Diffuse Reflectance Spectroscopy in a Neotropical Dry Forest Biome
inferred← citeshttps://doi.org/10.3390/land12081580openalex-snapshot
Biochar as Soil Amendment: The Effect of Biochar on Soil Properties Using VIS-NIR Diffuse Reflectance Spectroscopy, Biochar Aging and Soil Microbiology—A Review
inferred← citeshttps://doi.org/10.3390/land13020154openalex-snapshot
Predicting Soil Properties for Agricultural Land in the Caucasus Mountains Using Mid-Infrared Spectroscopy
inferred← citeshttps://doi.org/10.3390/land13040517openalex-snapshot
Estimating the Soil Copper Content of Urban Land in a Megacity Using Piecewise Spectral Pretreatment
inferred← citeshttps://doi.org/10.3390/land13081279openalex-snapshot
Monitoring the Soil Copper of Urban Land with Visible and Near-Infrared Spectroscopy: Comparing Spectral, Compositional, and Spatial Similarities
inferred← citeshttps://doi.org/10.3390/land14091830openalex-snapshot
How Spectrally Nearby Samples Influence the Inversion of Soil Heavy Metal Copper
inferred← citeshttps://doi.org/10.3390/network3040021openalex-snapshot
Survey for Soil Sensing with IOT and Traditional Systems
inferred← citeshttps://doi.org/10.3390/rs14215442openalex-snapshot
Geostatistical Modelling of Soil Spatial Variability by Fusing Drone-Based Multispectral Data, Ground-Based Hyperspectral and Sample Data with Change of Support
inferred← citeshttps://doi.org/10.3390/rs15082053openalex-snapshot
Prediction of Soil Properties in a Field in Typical Black Soil Areas Using in situ MIR Spectra and Its Comparison with vis-NIR Spectra
inferred← citeshttps://doi.org/10.3390/s24092784openalex-snapshot
Predicting Soil Organic Matter, Available Nitrogen, Available Phosphorus and Available Potassium in a Black Soil Using a Nearby Hyperspectral Sensor System
inferred← citeshttps://doi.org/10.3390/s24113556openalex-snapshot
Prediction Accuracy of Soil Chemical Parameters by Field- and Laboratory-Obtained vis-NIR Spectra after External Parameter Orthogonalization
inferred← citeshttps://doi.org/10.3390/s26010195openalex-snapshot
A Novel Self-Attention Mechanism-Based Dynamic Ensemble Model for Soil Hyperspectral Prediction
inferred← citeshttps://doi.org/10.3390/s26061805openalex-snapshot
Low-Cost Portable Near-Infrared Spectroscopy for Predicting Soil Properties in Paddy Fields of Southeastern China
inferred← citeshttps://doi.org/10.3390/s26175657openalex-snapshot
Latent Conditional Diffusion-Based Data Augmentation for Small-Sample Hyperspectral Prediction of Forest Soil Organic Carbon
inferred← citeshttps://doi.org/10.3390/su16051903openalex-snapshot
Carbon Farming: Bridging Technology Development with Policy Goals
inferred← citeshttps://doi.org/10.4018/979-8-3693-8487-9.ch015openalex-snapshot
Bioinformatics in Monitoring and Enhancing Wastewater Treatment Processes
inferred← citeshttps://doi.org/10.47864/se552025p5275openalex-snapshot
Predicción de propiedades del suelo mediante espectroscopía Vis-NIR-MIR: avances recientes, oportunidades y desafíos
inferred← citeshttps://doi.org/10.5194/essd-18-219-2026openalex-snapshot
Austrian NIR soil spectral library for soil health assessments
inferred← citeshttps://doi.org/10.5194/essd-18-2507-2026openalex-snapshot
Soil information and soil property maps for the Kurdistan region, Dohuk governorate (Iraq)
inferred← citeshttps://doi.org/10.5194/soil-12-227-2026openalex-snapshot
On soil health and the pivotal role of sensing
inferred← citeshttps://doi.org/10.5194/soil-12-619-2026openalex-snapshot
Estimating soil carbon sequestration potential with mid-IR spectroscopy and explainable machine learning
inferred← citeshttps://doi.org/10.55419/wsl:32071openalex-snapshot
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