Harvest Date Optimization Using Satellite Crop Phenology

Pinpoint optimal harvest windows from crop phenology trajectories. Klarety tracks NDVI progression and thermal accumulation from Sentinel-2 time-series to identify peak maturity dates and recommend harvest windows within 3-day precision. Reduces post-harvest losses and improves market timing for commodity producers.

Phenology-based harvest windows from satellite data

Klarety AI
Klarety AI chat composer interface

Harvest date recommendations from one AOI prompt

Klarety agents track NDVI phenology curves and return 3-day precision harvest window recommendations with confidence ranges.

Phenology - Sentinel-2
Klarety satellite analysis output

NDVI trajectory and thermal accumulation modeling

Agents model growing degree days from Sentinel-2 and thermal indices to identify peak maturity across field polygons.

GIS Output
Klarety AI map annotation overlay

Phenology outputs for precision farming GIS

Export maturity stage rasters and harvest window polygons for farm management and agronomy decision system integration.

NDVI phenology curve peak maturity detection

Klarety agents fit a double-logistic phenology curve to the Sentinel-2 NDVI time series for each field polygon, identify the inflection point marking peak NDVI, and estimate the senescence onset date as the harvest window. Growing degree day accumulation is cross-referenced to validate crop maturity stage. Output is a per-field harvest recommendation table with 3-day window and confidence score.

Klarety AIGet harvest window recommendations for your fields
analysis/harvest_phenology_optimizer.pyAgent code
output/harvest_window_report.mdOutput report

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