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March 29, 2026Remote Sensing2 citationsOpen Access

Harmonic Phenology Mapping: From Vegetation Indices to Field Delineation

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FPFilip PapićMMMario MilerDMDamir Medak

Key Points

  • The aim is to evaluate the impact of various vegetation indices on field delineation using harmonic phenology mapping.
  • Systematic evaluation of eleven vegetation indices in a fixed harmonic encoding pipeline.
  • Analysis of a one-year PlanetScope time series via annual sinusoidal regression.
  • Mapping of harmonic descriptors to HSV colour channels and segmentation with the Segment Anything Model.
  • Assessment of performance against official agricultural parcels for accuracy.
  • Soil-adjusted indices achieved better performance (F1 = 0.51–0.52) compared to standard ratios (NDVI: F1 = 0.49).
  • Pixel-wise scores remained high (F1 > 0.88 across all indices), suggesting reliable interior coverage.
  • Error analysis indicated that smaller parcels were prone to merging, while larger parcels experienced fragmentation.

Abstract

Operational agricultural monitoring in the Central European lowlands requires timely parcel boundaries; however, unmarked field edges produce minimal spectral contrast in single-date imagery. Previous works demonstrated that harmonic NDVI encoding enables zero-shot field delineation using foundational models, but the influence of the spectral index choice on temporal boundaries remained unquantified. This study systematically evaluates eleven vegetation indices—NDVI, GNDVI, NDRE, EVI, EVI2, SAVI, MSAVI, NDWI, CIg, CIre, and NDYVI—within a fixed harmonic phenology encoding pipeline. A one-year PlanetScope time series (15 × 15 km, Slavonija, Croatia) was decomposed via annual sinusoidal regression to extract per-pixel phase, amplitude, and mean parameters. These harmonic descriptors were mapped to HSV colour channels and segmented using the Segment Anything Model without fine-tuning. Official agricultural parcels (PAAFRD, 2025) provided ground truth for pixel-wise, object-wise, and size-stratified evaluation. Performance stratified into three tiers based on object-wise metrics. Soil-adjusted and enhanced-greenness indices (MSAVI, EVI, EVI2, and SAVI) achieved F1 = 0.51–0.52, and mIoU = 0.70–0.71, statistically outperforming standard ratio formulations (NDVI: F1 = 0.49) and chlorophyll indices (CIg, CIre: F1 = 0.45–0.47). Pixel-wise scores remained compressed (F1 > 0.88 across all indices), indicating consistent interior coverage but index-dependent boundary precision. Error analysis revealed scale-dependent patterns: merging dominated small parcels (<10,000 m2), while fragmentation increased with parcel size. Results demonstrate that spectral formulation is a systematic design factor in phenology-based delineation, with soil background correction and dynamic range compression improving seasonal trajectory separability. The harmonic parameters generated by this framework provide feature-ready input for crop classification, suggesting that integrated boundary extraction and crop mapping workflows merit further investigation.

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Cite This Study

Papić et al. (2026) studied this question.

synapsesocial.com/papers/69c8c22cde0f0f753b39c6edhttps://doi.org/10.3390/rs18071011
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