seegSDM_synthetic_data: Synthetic data for demonstrating the seegSDM package

In SEEG-Oxford/seegSDM: Streamlined Functions for Species Distribution Modelling in the SEEG Research Group

Description

A set of artificial data for demonstrating and testing the seegSDM R package.

Usage

data(occurrence)
data(evaluation)
data(covariates)
data(consensus)
data(template)
data(admin)

Format

occurrence: a dataframe giving occurrence data for a hypothetical disease (columns UniqueID, Admin, Year, x, y and Area - as required by checkOccurrence).

evaluation: a matrix with three columns, giving (projected) lat longs of sites which have been surveyed for the hypothetical disease (x and y) and a binary code of whether or not it was present (PA).

covariates: a RasterBrick with three layers, each giving the value of a covariate to be used in predicting the distribution of the hypothetical disease across a synthetic landscape. The first two covariates (codecov_a and cov_b) are continuous and the third (cov_c) is discrete.

consensus: a RasterLayer giving the evidence consensus for the disease at regional level in the synthetic landscape. The evidence consensus values are a score ranging from -100 to 100 descrinbing the level of certainty of presence or absence of the disease at a regional level. A score of -100 denotes absolute certainty of disease absence and 100 denotes absolute certainty of presence. A score of 0 denotes complete uncertainty as to whether the disease is present or absent.

template: a RasterLayer acting as a template and land-sea mask for the synthetic landscape.

admin: a RasterBrick with 4 layers giving regional codes for admin levels 0 to 3 for the synthetic landscape.

Source

These objects were all generated using the script gen_fake_data.R which can be downloaded at https://github.com/SEEG-Oxford/seegSDM/tree/master/fake_data.

SEEG-Oxford/seegSDM documentation built on May 9, 2019, 11:08 a.m.