belg

belg computes Boltzmann entropy (configurational entropy) for landscape gradients in R to quantify spatial pattern complexity in ecological and environmental datasets.

Key Features:

• Entropy calculations (relative and absolute): Computes both relative and absolute Boltzmann entropy for landscape gradients using hierarchy-based and aggregation-based methods that respectively consider hierarchical structure and aggregated spatial units.
• Raster and missing-data handling: Processes input raster data with missing (NA) values and provides procedures to adjust entropy calculations for incomplete datasets.
• Implementation: Executes computational routines via an efficient C++ backend integrated into R for improved performance.

Scientific Applications:

• Landscape complexity analysis: Quantifies the complexity and organization of landscape mosaics using Boltzmann/configurational entropy metrics.
• Landscape-gradient change detection: Quantifies changes in landscape gradients relevant to habitat fragmentation, land-use change, and biodiversity conservation studies.
• Thermodynamic interpretation of ecosystems: Provides empirical measures to support thermodynamic perspectives on spatial ecological dynamics.

Methodology:

Computes relative and absolute Boltzmann entropy via hierarchy-based and aggregation-based methods, handles raster inputs with NA values and adjustments for missing data, and implements computations in C++ integrated within R.