This research presents a novel approach for estimating soil organic carbon (SOC) content in agricultural soils using a photocatalytic Chemical Oxygen Demand (PeCOD) analyzer integrated with Geographic Information System (GIS) technology for spatial analysis. The PeCOD method, which relies on photochemical oxidation of organic carbon, demonstrated an uncanny correlation between its values and SOC content, making it a quick and accurate way to estimate SOC levels. Finer materials, such as clayey soils, demonstrated higher SOC content compared to coarser ones and decreased with increasing soil depth. GIS georeferencing enabled precise mapping of SOC distribution and identification of hotspot areas with high SOC content. This study highlights the significance of soil texture and depth on SOC distribution and emphasizes its significance within geological context when studying soil properties. Research results have practical ramifications for sustainable agriculture, climate change mitigation and soil health management - providing farmers and land managers with strategies that increase carbon sequestration while simultaneously improving soil health. Integrating PeCOD analyzer technology with GIS technology offers promising avenues for advanced soil carbon monitoring practices that promote climate-smart agricultural practices.