Journal ArticleDOI
A high resolution map of soil types and physical properties for Cyprus: A digital soil mapping optimization
Corrado Camera,Z. Zomeni,Jay S. Noller,Andreas M. Zissimos,Irene C. Christoforou,Adriana Bruggeman +5 more
TLDR
In this paper, a multiple-trees classification technique, namely Random Forest (RF), was applied to extend predictions from 1:25,000 legacy soil surveys (including WRB soil groups, soil depth and soil texture classes) to the larger area of Cyprus.About:
This article is published in Geoderma.The article was published on 2017-01-01. It has received 87 citations till now. The article focuses on the topics: Soil map & Digital soil mapping.read more
Citations
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Journal ArticleDOI
Machine learning and soil sciences: a review aided by machine learning tools
TL;DR: A comprehensive review of the application of ML techniques in soil science aided by a ML algorithm (latent Dirichlet allocation) to find patterns in a large collection of text corpora finds research gaps and finds that the interpretability of the ML models is an important aspect to consider when applying advanced ML methods in order to improve knowledge and understanding of soil.
Journal ArticleDOI
High resolution mapping of soil organic carbon stocks using remote sensing variables in the semi-arid rangelands of eastern Australia
TL;DR: The use of high spatial resolution satellite data (seasonal fractional cover data; SFC) together with elevation, lithology, climatic data and observed soil data to map the spatial distribution of SOC at two soil depths in semi-arid rangelands of eastern Australia produces a more accurate and higher resolution digital SOC stock map compared with other available mapping products.
Journal ArticleDOI
Land Suitability Assessment and Agricultural Production Sustainability Using Machine Learning Models
TL;DR: In this article, the authors assess land suitability for two main crops (i.e., rain-fed wheat and barley) based on the Food and Agriculture Organization (FAO) "land suitability assessment framework" for 65 km2 of agricultural land in Iran.
Journal ArticleDOI
Regional soil organic carbon prediction model based on a discrete wavelet analysis of hyperspectral satellite data
Xiangtian Meng,Yilin Bao,Jiangui Liu,Huanjun Liu,Huanjun Liu,Xinle Zhang,Yu Zhang,Peng Wang,Haitao Tang,Fan-chang Kong +9 more
TL;DR: This study provides a highly robust and accurate method for predicting and mapping regional SOC contents and indicates that at a low decomposition scale, DWT can effectively eliminate the noise in satellite hyperspectral data, and the FDR combined withDWT can improve the SOC prediction accuracy significantly.
Journal ArticleDOI
Spatial variability of soil texture fractions and pH in a flood plain (case study from eastern Iran)
TL;DR: In this article, the distribution of soil texture fractions and pH was investigated in a flood plain with intensive wind erosion for an area of ~41,000ha in Zahak county of Sistan and Baluchestan province in eastern Iran.
References
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Journal ArticleDOI
Random Forests
TL;DR: Internal estimates monitor error, strength, and correlation and these are used to show the response to increasing the number of features used in the forest, and are also applicable to regression.
Journal ArticleDOI
Building Predictive Models in R Using the caret Package
TL;DR: The caret package, short for classification and regression training, contains numerous tools for developing predictive models using the rich set of models available in R to simplify model training and tuning across a wide variety of modeling techniques.
Journal ArticleDOI
Bias in random forest variable importance measures: Illustrations, sources and a solution
TL;DR: An alternative implementation of random forests is proposed, that provides unbiased variable selection in the individual classification trees, that can be used reliably for variable selection even in situations where the potential predictor variables vary in their scale of measurement or their number of categories.
Journal ArticleDOI
Gene selection and classification of microarray data using random forest
TL;DR: It is shown that random forest has comparable performance to other classification methods, including DLDA, KNN, and SVM, and that the new gene selection procedure yields very small sets of genes (often smaller than alternative methods) while preserving predictive accuracy.
Book
Principles of Geographical Information Systems for Land Resources Assessment
TL;DR: Geographical information systems Data structures for thematic maps Digital elevation models Data input, verification, storage, and output Methods of data analysis and spatial modelling Data quality, errors, and natural variation: sources of error Errors arising through processing.