A web-based strategy to reuse grids in geographic modeling

•Grids are the basic unit for producing geospatial data and environmental modeling.•Two challenges are identified in reusing gridding algorithms and grid data.•An algorithm reuse method was proposed to shield algorithm execution differences.•Data reuse method was proposed to shield structural differences and speed querying. Grids are essential for the production of geospatial data and environmental modeling. Over many years of research, numerous grids have been designed and developed. Reusing grids can reduce usage costs. However, there are still factors that impede grid reusability. Gridding algorithms are difficult to share and reuse on another device because most gridding algorithms have certain requirements for the devices’ operating system (Windows or Linux) and runtime environment (Python, C++, or C#). Additionally, grid data are organized into various formats by the gridding algorithms, and parsing schemes need to be customized prior to using the data based on the rules governing the data organization. However, data customization tasks are difficult to replicate. This article presents a web-based grids reusability strategy to mitigate the problems encountered when reusing gridding algorithms and grid data. To reuse gridding algorithms, a service-oriented gridding algorithm encapsulation method is studied. Based on this encapsulation method, heterogeneous gridding algorithm programs can be invoked as standard web services regardless of a device’s operating environment. Moreover, a grid data wrapping method is also studied in this strategy to assists algorithm users with parsing grid data in a unified manner and more easily access grid data on the web. Finally, a web-based prototype system is established to demonstrate the strategy’s effectiveness and viability reusability.