CostAreaR

CostAreaR is an open-source software package for the R programming language that provides tools for analyzing the relationship between sampling cost and the area covered in spatial surveys. The package is designed for researchers and practitioners in ecology, geography, and environmental management who need to plan cost-efficient field campaigns or remote sensing assessments. CostAreaR offers methods to define cost components such as labor, equipment, travel, and data processing, and to compute cost-area curves that show how increasing the surveyed area affects total cost and information gain. It supports input from both vector and raster data, integrates with the sf and raster ecosystems, and can simulate cost scenarios through Monte Carlo approaches to quantify uncertainty.

Core capabilities include constructing cost-area curves from proposed survey designs, optimizing sampling plans under budget or area constraints, and producing plots and summary statistics for decision-making. The design emphasizes reproducibility, with functions that return tidy data frames suitable for downstream analysis and reporting, and with clear parameter settings and documentation.

Typical use cases include planning wildlife occupancy surveys, insect trap networks, or air quality monitoring grids where cost constraints are critical. CostAreaR is intended to complement existing spatial analysis work in R and can be extended via standard R package development practices, enabling researchers to tailor models to specific contexts.

Development and licensing details are usually documented in its project page and vignette, with ongoing updates by contributors in the open-source ecosystem. The project aims to provide a lightweight, modular framework for cost-aware spatial planning and analysis.