Prediction of the concentration of cadmium in agricultural soil in the Czech Republic using legacy data, preferential sampling, Sentinel-2, Landsat-8, and ensemble models.
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L. Borůvka | O. Drábek | V. Tejnecký | K. John | V. Khosravi | P. Agyeman | N. Kebonye | P. C. Agyeman
[1] R. Vašát,et al. Prediction of the concentration of antimony in agricultural soil using data fusion, terrain attributes combined with regression kriging. , 2022, Environmental pollution.
[2] D. Chakraborty,et al. Comparison of bagging, boosting and stacking algorithms for surface soil moisture mapping using optical-thermal-microwave remote sensing synergies , 2022, CATENA.
[3] Delin Li,et al. Estimating the heavy metal contents in farmland soil from hyperspectral images based on Stacked AdaBoost ensemble learning , 2022, Ecological Indicators.
[4] A. Sharififar. Accuracy and uncertainty of geostatistical models versus machine learning for digital mapping of soil calcium and potassium , 2022, Environmental Monitoring and Assessment.
[5] L. Rambaud,et al. Cadmium exposure in adults across Europe: Results from the HBM4EU Aligned Studies survey 2014-2020. , 2022, International journal of hygiene and environmental health.
[6] R. Vašát,et al. Combination of enrichment factor and positive matrix factorization in the estimation of potentially toxic element source distribution in agricultural soil , 2022, Environmental Geochemistry and Health.
[7] A. Gholizadeh,et al. Soil toxic elements determination using integration of Sentinel-2 and Landsat-8 images: Effect of fusion techniques on model performance. , 2022, Environmental Pollution.
[8] R. Vašát,et al. Using spectral indices and terrain attribute datasets and their combination in the prediction of cadmium content in agricultural soil , 2022, Comput. Electron. Agric..
[9] International Conference on Electrical, Computer and Energy Technologies (ICECET 2021) , 2021, 2021 International Conference on Electrical, Computer and Energy Technologies (ICECET).
[10] R. Vašát,et al. Using an ensemble model coupled with portable X-ray fluorescence and visible near-infrared spectroscopy to explore the viability of mapping and estimating arsenic in an agricultural soil. , 2021, The Science of the total environment.
[11] Cheng-Zhi Qin,et al. Hybridization of cokriging and gaussian process regression modelling techniques in mapping soil sulphur , 2021 .
[12] R. McDowell,et al. Do soil cadmium concentrations decline after phosphate fertiliser application is stopped: A comparison of long-term pasture trials in New Zealand? , 2021, The Science of the total environment.
[13] E. Smolders,et al. Trace metal accumulation in agricultural soils from mineral phosphate fertiliser applications in European long‐term field trials , 2021, European Journal of Soil Science.
[14] R. Singh,et al. Impact of Cadmium Pollution on Food Safety and Human Health , 2021 .
[15] J. Clapp. Explaining Growing Glyphosate Use: The Political Economy of Herbicide-Dependent Agriculture , 2021 .
[16] Manman Fan,et al. Machine learning-based source identification and spatial prediction of heavy metals in soil in a rapid urbanization area, eastern China , 2020 .
[17] Xiuliang Jin,et al. Improving Soil Thickness Estimations Based on Multiple Environmental Variables with Stacking Ensemble Methods , 2020, Remote. Sens..
[18] A. Bispo,et al. Mass balance approach to assess the impact of cadmium decrease in mineral phosphate fertilizers on health risk: The case-study of French agricultural soils. , 2020, The Science of the total environment.
[19] A. Lausch,et al. Prediction of soil organic carbon and the C:N ratio on a national scale using machine learning and satellite data: A comparison between Sentinel-2, Sentinel-3 and Landsat-8 images. , 2020, The Science of the total environment.
[20] S. Fahad,et al. Alleviation of Cadmium Adverse Effects by Improving Nutrients Uptake in Bitter Gourd through Cadmium Tolerant Rhizobacteria , 2020, Environments.
[21] Tran Minh Tung,et al. Heavy metal contamination prediction using ensemble model: Case study of Bay sedimentation, Australia. , 2020, Journal of hazardous materials.
[22] M. Thomsen,et al. The new fertilizer regulation: A starting point for cadmium control in European arable soils? , 2020, The Science of the total environment.
[23] Q. Du,et al. Estimating the distribution trend of soil heavy metals in mining area from HyMap airborne hyperspectral imagery based on ensemble learning. , 2020, Journal of hazardous materials.
[24] Daniel C W Tsang,et al. Metal contamination and bioremediation of agricultural soils for food safety and sustainability , 2020, Nature Reviews Earth & Environment.
[25] Benjamin M. Butler,et al. Meta-analysis of heavy metal effects on soil enzyme activities. , 2020, The Science of the total environment.
[26] Yones Khaledian,et al. Selecting appropriate machine learning methods for digital soil mapping , 2020, Applied Mathematical Modelling.
[27] Ming Xu,et al. Conventional and digital soil mapping in Iran: Past, present, and future , 2020 .
[28] Elif Sertel,et al. Soil salinity analysis of Urmia Lake Basin using Landsat-8 OLI and Sentinel-2A based spectral indices and electrical conductivity measurements , 2020 .
[29] Thorsten Behrens,et al. Improving the Spatial Prediction of Soil Organic Carbon Content in Two Contrasting Climatic Regions by Stacking Machine Learning Models and Rescanning Covariate Space , 2020, Remote. Sens..
[30] Yi Wang,et al. Machine learning-based detection of soil salinity in an arid desert region, Northwest China: A comparison between Landsat-8 OLI and Sentinel-2 MSI. , 2020, The Science of the total environment.
[31] C. Zou,et al. Health risk assessment associated with heavy metal accumulation in wheat after long-term phosphorus fertilizer application. , 2020, Environmental pollution.
[32] S. Ayoubi,et al. Digital mapping of soil organic carbon using ensemble learning model in Mollisols of Hyrcanian forests, northern Iran , 2020 .
[33] M. Trifuoggi,et al. Human health risk from consumption of two common crops grown in polluted soils. , 2019, The Science of the total environment.
[34] F. Zhao,et al. Cadmium contamination in agricultural soils of China and the impact on food safety. , 2019, Environmental pollution.
[35] Zhe Zhu,et al. Current status of Landsat program, science, and applications , 2019, Remote Sensing of Environment.
[36] Emilien Aldana-Jague,et al. Assessing the Performance of UAS-Compatible Multispectral and Hyperspectral Sensors for Soil Organic Carbon Prediction , 2019, Sustainability.
[37] Matthieu Molinier,et al. Comparison of Sentinel-2 and Landsat 8 imagery for forest variable prediction in boreal region , 2019, Remote Sensing of Environment.
[38] Dominique Arrouays,et al. Merging country, continental and global predictions of soil texture: Lessons from ensemble modelling in France , 2019, Geoderma.
[39] Andrea E. Ulrich. Cadmium governance in Europe's phosphate fertilizers: Not so fast? , 2019, The Science of the total environment.
[40] F. D. Ardejani,et al. Monitoring soil lead and zinc contents via combination of spectroscopy with extreme learning machine and other data mining methods , 2018 .
[41] Ruobing Wang,et al. Significantly Improving the Prediction of Molecular Atomization Energies by an Ensemble of Machine Learning Algorithms and Rescanning Input Space: A Stacked Generalization Approach , 2018 .
[42] K. Oost,et al. An assessment of the global impact of 21st century land use change on soil erosion , 2017, Nature Communications.
[43] A. Johari,et al. Reliability analysis of a vertical cut in unsaturated soils using sequential Gaussian simulation , 2017 .
[44] Sabine Grunwald,et al. Evaluating the effect of remote sensing image spatial resolution on soil exchangeable potassium prediction models in smallholder farm settings. , 2017, Journal of environmental management.
[45] Xiangnan Liu,et al. Extraction of Rice Heavy Metal Stress Signal Features Based on Long Time Series Leaf Area Index Data Using Ensemble Empirical Mode Decomposition , 2017, International journal of environmental research and public health.
[46] M. Rautiainen,et al. Comparison of Sentinel-2 and Landsat 8 in the estimation of boreal forest canopy cover and leaf area index , 2017 .
[47] Shanqin Wang,et al. Methods for estimating leaf nitrogen concentration of winter oilseed rape (Brassica napus L.) using in situ leaf spectroscopy. , 2016 .
[48] L. Bornn,et al. The positive effects of population-based preferential sampling in environmental epidemiology. , 2016, Biostatistics.
[49] Onisimo Mutanga,et al. Discriminating Rangeland Management Practices Using Simulated HyspIRI, Landsat 8 OLI, Sentinel 2 MSI, and VENµS Spectral Data , 2016, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[50] Elif Sertel,et al. ASSESSMENT OF CLASSIFICATION ACCURACIES OF SENTINEL-2 AND LANDSAT-8 DATA FOR LAND COVER / USE MAPPING , 2016 .
[51] Pierre Soille,et al. Assessment of the Added-Value of Sentinel-2 for Detecting Built-up Areas , 2016, Remote. Sens..
[52] Fangbai Li,et al. Using ensemble models to identify and apportion heavy metal pollution sources in agricultural soils on a local scale. , 2015, Environmental pollution.
[53] P. Rudnai,et al. Exposure determinants of cadmium in European mothers and their children. , 2015, Environmental research.
[54] R. Chaney. How Does Contamination of Rice Soils with Cd and Zn Cause High Incidence of Human Cd Disease in Subsistence Rice Farmers , 2015, Current Pollution Reports.
[55] Matthias J. R. Speich,et al. Application of bivariate mapping for hydrological classification and analysis of temporal change and scale effects in Switzerland , 2015 .
[56] G. Gupta,et al. Plant Growth Promoting Rhizobacteria (PGPR): Current and Future Prospects for Development of Sustainable Agriculture , 2015 .
[57] Budiman Minasny,et al. Using model averaging to combine soil property rasters from legacy soil maps and from point data , 2014 .
[58] R. Casa,et al. Estimation of soil properties at the field scale from satellite data: a comparison between spatial and non‐spatial techniques , 2014 .
[59] Sabine Grunwald,et al. Multi‐scale Modeling of Soil Series Using Remote Sensing in a Wetland Ecosystem , 2012 .
[60] Michael E. Schaepman,et al. Sentinels for science: potential of Sentinel-1, -2, and -3 missions for scientific observations of ocean, cryosphere, and land , 2012 .
[61] Lei Tian,et al. Development of a low-cost agricultural remote sensing system based on an autonomous unmanned aerial vehicle (UAV) , 2011 .
[62] Jane A. Plant,et al. Cadmium levels in Europe: implications for human health , 2010, Environmental geochemistry and health.
[63] E. Ben-Dor,et al. Estimation of Soil Properties by Orbital and Laboratory Reflectance Means and its Relation with Soil Classification , 2009 .
[64] R. Kerry,et al. Determining the effect of asymmetric data on the variogram. I. Underlying asymmetry , 2007, Comput. Geosci..
[65] G. Reinds,et al. European Critical Loads of Cadmium, Lead and Mercury and their Exceedances , 2007 .
[66] Xuexia Chen,et al. Using lidar and effective LAI data to evaluate IKONOS and Landsat 7 ETM+ vegetation cover estimates in a ponderosa pine forest , 2004 .
[67] D. Opitz,et al. Popular Ensemble Methods: An Empirical Study , 1999, J. Artif. Intell. Res..
[68] B. E. Trumbo,et al. A Theory for Coloring Bivariate Statistical Maps , 1981 .
[69] C. Willmott. ON THE VALIDATION OF MODELS , 1981 .
[70] Yue Zhang,et al. Comparison of the use of Landsat 8, Sentinel-2, and Gaofen-2 images for mapping soil pH in Dehui, northeastern China , 2022, Ecol. Informatics.
[71] N. E. Silvero,et al. Soil variability and quantification based on Sentinel-2 and Landsat-8 bare soil images: A comparison , 2021 .
[72] Leandro dos Santos Coelho,et al. Ensemble approach based on bagging, boosting and stacking for short-term prediction in agribusiness time series , 2020, Appl. Soft Comput..
[73] J. Othman,et al. Selected Research Issues in the Malaysian Agricultural Sector (Isu-isu Penyelidikan Terpilih di dalam Sektor pertanian Malavsia) , 2014 .
[74] B. J. Alloway,et al. Heavy Metals and Metalloids as Micronutrients for Plants and Animals , 2013 .
[75] Alireza Mesdaghinia,et al. Effect of fertilizer application on soil heavy metal concentration , 2010, Environmental monitoring and assessment.
[76] D. Bindi,et al. Soil Dynamics and Earthquake Engineering , 2008 .
[77] Roberto Canullo,et al. Manual on methods and criteria for harmonized sampling, assessment, monitoring and analysis of the effects of air pollution on forests. Part VIII, Assessment of Ground Vegetation. Expert Panel on Ground Vegetation Assessment, UN-ECE, ICP-Forests. , 2007 .
[78] M. A. Herrador,et al. Uncertainty evaluation from Monte-Carlo simulations by using Crystal-Ball software , 2005 .
[79] Leo Breiman,et al. Stacked regressions , 2004, Machine Learning.
[80] D. Sauerbeck,et al. Changing Metal Cycles and Human Health , 1984, Dahlem Workshop Reports, Life Sciences Research Report.
[81] High-resolution agriculture soil property maps from digital soil mapping methods, Czech Republic , 2022, CATENA.