Sustainable Agricultural Planning via Temperature Trend Analysis: A Candlestick and Fractal Approach

This paper introduces a novel approach to temperature trend analysis utilizing Japanese candlestick representations combined with fractal analysis, specifically aimed at enhancing agricultural planning in Ukraine. The study leverages open-source data from the Copernicus Climate Data Store, focusing on the Kyiv Oblast region for 2022-2023. This research seeks to identify and predict temperature trends more accurately than traditional methods by transforming hourly temperature data into candlestick representations and applying fractal analysis techniques. The methodology aggregates temperature data into fractals composed of multiple candles, enabling systematic trend detection and confirmation of trend reversals. The results demonstrate the method’s capability to capture global temperature trends while avoiding local extrema, offering valuable insights for agricultural decision-making. The paper discusses the implications of these findings for optimizing planting and harvesting schedules in the context of Ukraine’s changing climate and ongoing war-related challenges. This approach presents a promising tool for farmers to better align their activities with evolving temperature patterns, potentially enhancing agricultural productivity and resilience amid climatic and geopolitical uncertainties.