The integration of Big Data and Geographic Information Systems (GIS) has contributed significantly to the improvement of the analysis and management of environmental systems. This convergence gives additional profound and accurate information about environmental issues that are crucial for decision-making and policies within the field of environmental science. This scoping review aims to systematically explore and map the current literature on integrating Big Data and GIS within environmental science. The primary objective is to pinpoint topics and study approaches to gain a thorough insight into how these technologies are utilized to tackle different environmental issues. The research papers were chosen based on their emphasis on using Big Data and GIS in settings; those without environmental relevance or integration of both technologies were not considered. A rigorous two-stage screening method was used. Titles and abstracts were first screened, followed by the full text evaluation for relevance and alignment with the inclusion criteria. The review covered 32 research projects, revealing a significant rise in the adoption of Big Data and GIS in the field of environmental science since 2017—especially noticeable in the United States and China. Findings indicate six key thematic areas—water resource management, biodiversity conservation, pollution monitoring, climate change impact assessment, disaster management, and urban planning. Methodologies such as machine learning, spatiotemporal analysis, and real-time data integration are central to these applications. This integration offers a robust approach to managing environmental complexity, driving informed decision-making, and advancing environmental research.