Manuscript Topics

Environmental protection has been the worldwide issue of the utmost concern, covering all walks of life. The traditional solutions to this issue rely on manual measurement and statistics. During the practical implement, these solutions expose the defects of chaotic data, information lag, and low efficiency, and their availability is further reduced in the current era of rapid urbanization which requires heavier workload and higher requirements on environmental protection. The emerging technology of Geographic Information System (GIS) facilitates the collection and analysis of spatial, high-dimension, and time-series data related to the environment. Supported by massive and up-to-date data from GIS, the environmental system can be modeled more accurately. The integration of GIS with different modeling methods enables the government and enterprises to conduct comprehensive research that includes environmental inspection, prediction, assessment, planning, decision-making, and so on. However, current studies mainly focus on GIS-based models for a particular area in a specific condition, thus having poor portability in terms of space and time. In addition, GIS is not fully used and its application just rests on inputting/outputting data to/from models. This is caused by the limited spatial data analysis of GIS and the potential incompatibility between the modeling methods and GIS. At the same time, the spatial data from GIS feature large quantities, diverse species, and different characteristics, making it hard to thoroughly mine the environmental information and achieve the maximum effect. Therefore, we produce a special issue titled “Geographic information systems in environmental protection” to encourage researchers to contribute to enhancing the level of environmental inspection and management by fully using the spatial data from GIS. We are looking for original research articles as well as comprehensive review articles addressing the recent advances and/or challenges in GIS-based analysis, modeling and algorithm for environmental protection, including but not limited to:

• GIS-based inspection of pollution sources
• GIS-based simulation and prediction of emission
• Emergency preparedness and response to environmental pollution
• Spatial data-driven optimal planning and decision-making for environmental protection
• GIS-based intelligent management for resisting and controlling environmental pollution
• Spatial analysis on the impacts of COVID-19 on environmental sectors
• Data visualization and mapping for environmental protection

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