Integration of Big Data, Electronic Information, and GIS in Atmospheric Monitoring
Abstract
Monitoring of the atmosphere is experiencing a paradigm shift due to a combination of big data, electronic information technologies, and geographic information systems (GIS). Conventional methods of monitoring, which are largely based on sparse fixed-site stations, usually experience spatial constraints, limited time responsiveness, and challenges in integrating multiple sources. This paper provides a systematic review of how the joint evolution of dense sensing networks, real-time communication systems, big-data analytics, and geospatial platforms is transforming existing atmospheric observation systems into smarter and decision-oriented structures. The paper first presents the technological background of integrated atmospheric monitoring, such as heterogeneous data sources, sensor and communication infrastructure, and GIS-based spatial intelligence. It then examines key processes of data preprocessing and quality control, multi-source fusion, spatiotemporal modeling, visualization, and uncertainty-conscious interpretation. Significant application areas are also examined, among which are urban air quality control, regional pollution monitoring, emergency response, and public health assessment. The current limitations are also critically assessed in the review (including data heterogeneity, unstable calibration, scale and location issues, interoperability, propagation of uncertainties, and poor model interpretability). Based on this assessment, future trends are determined to include explainable artificial intelligence, edge intelligence, digital twin platforms, and more standardized and resilient monitoring architectures. The originality of this review is its integrated approach, which does not consider big data, electronic information, and GIS as independent technical solutions, but rather views them as complementary components and pillars of next-generation atmospheric monitoring. The review serves as a systematic source for the development of more accurate, adaptive, and governance-oriented atmospheric monitoring systems.