Code for edge-effect analysis of Ramsar protected areas

This repository contains Python scripts developed for spatial statistical analysis of aboveground biomass (AGB) in relation to forest edge distance. The workflow aims to investigate the relationship between biomass characteristics and spatial position relative to forest boundaries. The scripts implement a distance-based analytical framework using ESA Climate Change Initiative (CCI) Aboveground Biomass (AGB) and associated standard deviation (SD) datasets. A binary forest mask is derived from valid biomass observations, and Euclidean distance to forest edges is computed using raster-based geospatial operations. Subsequently, biomass (AGB), uncertainty (SD), and relative uncertainty (RU = SD/AGB) are aggregated across predefined distance intervals to characterize spatial gradients from forest edge to interior. The analysis quantifies how biomass-related variables vary as a function of distance from forest boundaries, providing a spatially explicit statistical characterization of edge effects.