Comparison of Geographical Information System approaches for programming with Projected Coordinate System code numbers

Geographic Information System (GIS) tasks often require a sound understanding of Projected Coordinate Systems (PCS). While these systems are straightforward for geomatics experts, it present challenges for beginners, software developers, and those unfamiliar with GIS. The budding Software developers cannot accomplish the task of implementing geoprocessing tool efficiently without knowing the EPSG code. To address this, in this article, python codes are written as an approach for extracting geoprocessing automation code from datasets using ArcGIS 10.3 python window. This approach involves identifying the coordinate system’s name and extracting the EPSG code from the dataset as properties. This method simplifies the process and empowers developers with the tools it needs to carry out geoprocessing tasks. In practical testing, our Python script, as written effectively, processed data samples generated from a point feature class, serving as a vector dataset. This method proved superior to the traditional approach, shown in Figure 6, which involves manual selection of layer attributes through right-click actions and is better suited for expert users. For developers, having immediate access to EPSG code numbers streamlines the creation of Python code for geoprocessing tasks. This approach not only simplifies geoprocessing but also enhances accessibility for GIS novices and software developers, making it a valuable base for the users who are at beginner level.