load_meseta: Load the Meseta Iberica spatial action example

In multiscape: Multi-Action, Multi-Objective Spatial Planning

Load the Meseta Iberica spatial action example

Description

Load the complete inputs used by the introductory README tutorial. These earlier available data support an adaptation of the Meseta case study, not an exact reproduction of the final 2025 article.

Usage

load_meseta()

Details

The bundled inputs are redistributed under GPL-3.0. Their source and preparation notes are recorded in provenance.

The action identifiers in actions$id, action_costs$action and outcomes$action consistently use Afforestation, BAU, FarmReturn and Firesmart. The tables can be passed directly to add_actions() and add_effects(), without recoding identifiers. Scripts that explicitly select numeric action identifiers must use these names instead. Original identifiers remain available in provenance$action_id_lookup. All amounts, costs, targets, reference values and geometries are preserved. Planning-unit costs are retained; use include_pu_cost = FALSE in add_objective_min_cost() to count only action implementation costs. Maps are derived when loading, without storing additional copies of geometry in package data. Map columns use the names in actions$name; rows follow planning_units order, and row names contain planning-unit identifiers.

The five feature maps illustrate contrasting action scenarios (three species and two ecosystem-service features), not ecological importance. Missing outcome rows are displayed as zero, following the dataset convention. These maps describe inputs under each action, not optimized selections.

Value

A named list containing:

planning_units

An sf object with 11,109 planning units.

features

A catalogue of 155 features.

dist_features

The explicit comparison reference used in the tutorial.

actions

A catalogue of four management strategies, with readable character identifiers in id (also provided in name).

action_costs

Costs by planning unit and action.

outcomes

Outcomes by planning unit, action and feature.

targets

Representation targets for all features.

boundary

The supplied weighted spatial relation. Replacing it with a newly derived boundary can change the optimization problem.

provenance

Data sources and preparation notes. action_id_lookup records the original numeric source_id and the returned character id for each action.

maps

Ready-to-plot sf views: costs, DENMINO, CISJUNC, MLE, AGRICULTURE and ROS. Each view contains four strategy columns and geometry, so plot() displays the four action scenarios directly.

Examples

meseta <- load_meseta()
names(meseta)
meseta$actions
plot(meseta$maps$costs)
plot(meseta$maps$DENMINO)

multiscape documentation built on Oct. 12, 2026, 5:08 p.m.