Spatial uncertainty propagation analysis with the spup R package

Research output: Contribution to journalArticleAcademicpeer-review

3 Citations (Scopus)

Abstract

Many environmental and geographical models, such as those used in land degradation, agroecological and climate studies, make use of spatially distributed inputs that are known imperfectly. The R package spup provides functions for examining the uncertainty propagation from input data and model parameters onto model outputs via the environmental model. The functions include uncertainty model specification, stochastic simulation and propagation of uncertainty using Monte Carlo (MC) techniques. Uncertain variables are described by probability distributions. Both numerical and categorical data types are handled. The package also accommodates spatial auto-correlation within a variable and cross-correlation between variables. The MC realizations may be used as input to the environmental models written in or called from R. This article provides theoretical background and three worked examples that guide users through the application of spup.

Original languageEnglish
Pages (from-to)180-199
Number of pages20
JournalR Journal
Volume10
Issue number2
DOIs
Publication statusPublished - Dec 2018

Fingerprint

Dive into the research topics of 'Spatial uncertainty propagation analysis with the spup R package'. Together they form a unique fingerprint.

Cite this