Various Approaches for Predicting Land Cover in Mountain Areas

DOI10.1080/03610910601096379zbMath1113.62142arXiv0705.0418OpenAlexW3102507698WikidataQ58201396 ScholiaQ58201396MaRDI QIDQ3447062

Laurence Cornez, Nathalie Villa, Maria T. Camacho Olmedo, Louis Ferré, Martin Paegelow, Pascal Sarda, Frédéric Ferraty

Publication date: 28 June 2007

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/0705.0418

zbMATH Keywords

predictionclassificationcomparisonmultilayer perceptronpolychotomous regression modeling

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Applications of statistics to environmental and related topics (62P12) Geostatistics (86A32) Neural nets and related approaches to inference from stochastic processes (62M45)

Uses Software

• R
• Neural Network Toolbox

Cites Work

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• Functional approaches for predicting land use with the temporal evolution of coarse resolution remote sensing data
• Polychotomous Regression
• Stochastic Neural Networks With Applications to Nonlinear Time Series

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