Timon
4cd62ab82e
- 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.
1.1 KiB
1.1 KiB
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
Last Updated: February 2026
Maintained By: Resilience BV
Repository: https://github.com/TimonWeitkamp/smartcane_experimental_area