A self-training semi-supervised machine learning method for predictive mapping of soil classes with limited sample data

SciPy 1.0: fundamental algorithms for scientific computing in Python

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Digital soil mapping and GlobalSoilMap. Main advances and ways forward

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Influence of meteorological conditions on PM2.5 concentrations across China: A review of methodology and mechanism

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Comparison of conditioned Latin hypercube and feature space coverage sampling for predicting soil classes using simulation from soil maps

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Phenology-based classification of crop species and rotation types using fused MODIS and Landsat data: The comparison of a random-forest-based model and a decision-rule-based model

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Predicting soil organic carbon content in croplands using crop rotation and Fourier transform decomposed variables

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Digital soil mapping algorithms and covariates for soil organic carbon mapping and their implications: A review

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Sampling design optimization for soil mapping with random forest

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Digital mapping of soil properties using multiple machine learning in a semi-arid region, central Iran

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Random forest as a generic framework for predictive modeling of spatial and spatio-temporal variables

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Digital mapping of soil carbon fractions with machine learning

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A semi-supervised generative framework with deep learning features for high-resolution remote sensing image scene classification

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Self-training for multi-target regression with tree ensembles

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Specific Land Cover Class Mapping by Semi-Supervised Weighted Support Vector Machines

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An overview and comparison of machine-learning techniques for classification purposes in digital soil mapping

(2016) Brandon Heung et al.   GEODERMA

Semantic Annotation of High-Resolution Satellite Images via Weakly Supervised Learning

(2016) Xiwen Yao et al.   IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING

Semi-supervised hyperspectral classification from a small number of training samples using a co-training approach

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A comparative assessment of support vector regression, artificial neural networks, and random forests for predicting and mapping soil organic carbon stocks across an Afromontane landscape

(2015) Kennedy Were et al.   ECOLOGICAL INDICATORS

Predictive soil mapping with limited sample data

(2015) A. X. Zhu et al.   EUROPEAN JOURNAL OF SOIL SCIENCE

Machine learning for predicting soil classes in three semi-arid landscapes

(2015) Colby W. Brungard et al.   GEODERMA

Object Detection in Optical Remote Sensing Images Based on Weakly Supervised Learning and High-Level Feature Learning

(2015) Junwei Han et al.   IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING

Mapping attributes of Canada’s forests at moderate resolution through kNN and MODIS imagery

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From plots to landscape: A k-NN-based method for estimating stand-level merchantable volume in the Province of Québec, Canada

(2014) P. Y. Bernier et al.   FORESTRY CHRONICLE

Digital mapping of soil properties in Canadian managed forests at 250m of resolution using the k-nearest neighbor method

(2014) Nicolas Mansuy et al.   GEODERMA

Using model averaging to combine soil property rasters from legacy soil maps and from point data

(2014) Brendan P. Malone et al.   GEODERMA

Soil classification using visible/near-infrared diffuse reflectance spectra from multiple depths

(2014) G.M. Vasques et al.   GEODERMA

Can γ-radiometrics predict soil textural data and stoniness in different parent materials? A comparison of two machine-learning methods

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Predictive soil parent material mapping at a regional-scale: A Random Forest approach

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Self-labeled techniques for semi-supervised learning: taxonomy, software and empirical study

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Soil Series Mapping By Knowledge Discovery from an Ohio County Soil Map

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Spatial prediction of USDA- great soil groups in the arid Zarand region, Iran: comparing logistic regression approaches to predict diagnostic horizons and soil types

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Improving regional soil carbon inventories: Combining the IPCC carbon inventory method with regression kriging

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Sampling for validation of digital soil maps

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Analysis and prediction of soil properties using local regression-kriging

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Streamflow changes and its influencing factors in the mainstream of the Songhua River basin, Northeast China over the past 50 years

(2010) Chiyuan Miao et al.   Environmental Earth Sciences

Spatial prediction of soil classes using digital terrain analysis and multinomial logistic regression modeling integrated in GIS: Examples from Vestfold County, Norway

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Updating the 1:50,000 Dutch soil map using legacy soil data: A multinomial logistic regression approach

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Construction of membership functions for predictive soil mapping under fuzzy logic

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Soil type classification and estimation of soil properties using support vector machines

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Quantification of spatial gradation of slope positions

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An approach to computing topographic wetness index based on maximum downslope gradient

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Digital Soil Map of the World

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Supervised Classification of Agricultural Land Cover Using a Modified k-NN Technique (MNN) and Landsat Remote Sensing Imagery

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Instance selection and classification tree analysis for large spatial datasets in digital soil mapping

(2008) Karsten Schmidt et al.   GEODERMA

Soil organic carbon concentrations and stocks on Barro Colorado Island — Digital soil mapping using Random Forests analysis

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Implementation and evaluation of existing knowledge for digital soil mapping in Senegal

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A multiple regression approach to assess the spatial distribution of Soil Organic Carbon (SOC) at the regional scale (Flanders, Belgium)

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