SmartCane/README.md
Timon 4cd62ab82e Enhance report utility functions and add validation scripts
- 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.
2026-02-11 14:32:36 +01:00

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Markdown

# SmartCane - Agricultural Intelligence Platform
A multi-stage satellite imagery processing system for crop health analysis and harvest predictions in sugarcane farming operations.
## Overview
SmartCane processes 4-band satellite imagery (RGB + NIR) into actionable crop health insights using a sophisticated data pipeline spanning Python, R, and PHP. The system integrates satellite data from Planet Labs with field-level analysis, automated reporting, and harvest forecasting.
### Core Features
- **Weekly Satellite Monitoring**: 4-band GeoTIFF imagery acquisition and processing
- **Chlorophyll Index (CI) Analysis**: Crop health assessment with multi-temporal smoothing
- **Field-Level KPI Calculation**: Uniformity metrics, gap detection, weed risk assessment
- **Harvest Forecasting**: ML-powered yield predictions with growth trajectory analysis
- **Automated Reporting**: Weekly Word/HTML reports with field-specific alerts and recommendations
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**Last Updated**: February 2026
**Maintained By**: Resilience BV
**Repository**: https://github.com/TimonWeitkamp/smartcane_experimental_area