Scholarly record

MONITORING CROP PHENOLOGY USING HIGH-RESOLUTION SATELLITE IMAGERY: SOFIA REGION, BULGARIA

Yana Lipiyska, Tsvetelina Atanasova-Evdenova, Adrian Yordanov

Abstract

Accurate monitoring of crop phenology is essential for yield estimation, growing season modeling, and climate adaptation in agriculture. While freely available satellite archives provide broad spatial coverage, their temporal frequency is often insufficient for capturing the rapid phenological transitions characteristic of crops. This study addresses that gap through a multitemporal analysis of the Normalized Difference Vegetation Index (NDVI) derived from a time series of 119 PlanetScope satellite images at 3 m spatial resolution, acquired over five agricultural parcels near Elin Pelin, Sofia Region, Bulgaria, during the 2025 growing season. The primary objective is to assess biological productivity through the Integral Vegetation Index (AUC - Area Under Curve), serving as a proxy for total biomass accumulation. Four crop types are studied - barley, wheat, sunflower, and maize, with continuous phenological coverage from March to October, capturing both winter and summer crop cycles. Special emphasis is placed on analyzing the senescence slope, the decline phase following peak vegetation, which identifies the rate of chlorophyll degradation and crop response to summer heat stress. Key phenological indicators include green-up date, peak NDVI timing, senescence onset, and growing season duration. Results reveal distinguishable NDVI trajectories among crop types, with winter crops. Image processing was performed in Python, with spatial analysis and visualization conducted in QGIS, enabling discrimination of within-field variability at 3 m resolution. The findings provide a quantitative phenological baseline for Sofia Region's agricultural zone, demonstrating the added value of high-frequency commercial Earth observation data for fine-scale crop monitoring and climate-resilient decision-making.

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