- Changed report date in CI report for cane supply to "2026-02-04".
- Updated output file naming convention for agronomic support report to reflect new report date.
- Enhanced map creation functions to allow customizable legend positions and improved layout settings.
- Adjusted widths for map arrangements to ensure better visual representation.
- Fixed minor issues in ggplot aesthetics for clearer legend positioning and improved readability.
- Corrected field size unit from hectares to acres in KPI summary generation.
- Improved safe_log function to include timestamps and conditional logging
- Added diagnostic messages for field visualization processing
- Updated CI map rendering parameters for consistency
- Refined raster mapping functions in report_utils for clarity
- Added .png files to .gitignore
- Implemented `run_spectral_extraction.py` to batch extract spectral indices (NDVI, BSI, NDWI) from 4-band TIFF files, saving results in a structured CSV format.
- Created `spectral_features.py` for calculating various spectral indices, including NDVI, BSI, NDWI, CI_green, CI_red, GNDVI, SAVI, and EVI2.
- Added Jupyter notebook `02_season_normalization_analysis.ipynb` for analyzing season-length normalization, comparing ESA and Angata spectral indices, and visualizing growth patterns.
- Included functions for computing season age, plotting trajectories, and performing peak and amplitude analysis.
- Updated `create_CI_map` and `create_CI_diff_map` functions to enforce a 1:1 aspect ratio for consistent map sizing.
- Modified `ci_plot` function to adjust widths of arranged maps for better layout.
- Changed raster merging method in `aggregate_per_field_mosaics_to_farm_level` from `mosaic` to `merge` for improved handling of field data.
- Introduced `test_kpi_validation.R` script to validate the structure of KPI RDS files, ensuring expected KPIs are present.
- Added `test_overview_maps_aggregation.R` script to test the aggregation pipeline for overview maps, including loading field mosaics, creating a farm-level mosaic, and generating visualizations.
Timon
