ANNOUNCEMENTS
Wheat yield in Uttar Pradesh, India’s leading wheat-producing state, is increasingly influenced by climate variability, particularly temperature dynamics during the Rabi season. This study analyses spatial and temporal trends in Growing Degree Days (GDD) across five crop years (2019–20 to 2023–24) and investigates their relationship with wheat yield. Using satellite datasets from Sentinel-2 and MODIS, combined with ERA5 climate reanalysis and district-wise yield statistics from DES, a comprehensive geospatial workflow was implemented via Google Earth Engine. NDVI-based wheat classification was performed using a Random Forest model, followed by GDD estimation to identify the number of days required to reach the 1800 GDD maturity threshold. Results show a consistent inverse correlation between GDD accumulation rate and yield: southern districts with faster GDD buildup recorded lower yields, while cooler northwestern regions with slower GDD accumulation exhibited higher productivity. Correlation analysis revealed a strong positive relationship (R² = 0.50–0.62) between GDD duration and yield, emphasizing the importance of thermal time in crop performance. The findings support the development of regionspecific adaptation strategies—such as adjusting sowing dates and variety selection—to improve wheat resilience under changing climatic conditions.
Keywords: Growing Degree Days (GDD), Sentinel-2, MODIS, ERA5 climate data, NDVI time series, crop phenology, Random Forest classification, spatial yield mapping.
