CspStandSegmentation 0.2.1

New Features and Enhancements

Replaced R distance calculation function with a C++ implementation for faster computation in fds

Added semantic segmentation support to the forest inventory function, allowing users to filter points by classification (e.g., stem-only points) for more accurate DBH estimation.

Flexible tree identification: The forest_inventory() function now supports custom TreeID column names through the tree_id_col parameter
Added non_tree_id parameter to specify which values represent non-tree elements (can be a vector)

Significantly optimized circle fitting algorithm with vectorized distance calculations
Implemented weighted point sampling based on local point density for better convergence
Reduced iterations to 500 and added early stopping criteria (30 angular segments)
Completely rewrote core forest_inventory() logic to use data.table instead of loops and foreach parallelization
Improved readability with helper functions: .fit_circle(), .fit_circles(), .spline_predict()
Eliminated parallelization overhead for single-core efficiency

Improved height normalization: Better handling of Z-coordinates when reference height (Zref) is available
Enhanced quality control: Added validation checks for unrealistic circle diameters and center positions
Robust data types: Fixed data.frame structure issues by converting merged results properly
Better error handling: Added validation for stem segmentation parameters and semantic column existence

Fixed spline prediction height (now uses 1.3 + 0.5*increment for better accuracy)
Corrected data.frame structure in inventory output
Fixed cosmetic issues and improved code formatting
Resolved issues with NA value handling in RANSAC circle fitting