Abstract

PyGRASS is an object-oriented Python Application Programming Interface (API) for Geographic Resources Analysis Support System (GRASS) Geographic Information System (GIS), a powerful open source GIS widely used in academia, commercial settings and governmental agencies. We present the architecture of the PyGRASS library, covering interfaces to GRASS modules, vector and raster data, with a focus on the new capabilities that it provides to GRASS users and developers. Our design concept of the module interface allows the direct linking of inputs and outputs of GRASS modules to create process chains, including compatibility checks, process control and error handling. The module interface was designed to be easily extended to work with remote processing services (Web Processing Service (WPS), Web Service Definition Language (WSDL)/Simple Object Access Protocol (SOAP)). The new object-oriented Python programming API introduces an abstract layer that opens the possibility to use and access transparently the efficient raster and vector functions of GRASS that are implemented in C. The design goal was to provide an easy to use, but powerful, Python interface for users and developers who are not familiar with the programming language C and with the GRASS C-API. We demonstrate the capabilities, scalability and performance of PyGRASS with several dedicated tests and benchmarks. We compare and discuss the results of the benchmarks with dedicated C implementations.

Highlights

  • Geographic Information Systems (GIS) have the capabilityto integrate heterogeneous digital data, giving the opportunity to public administration, industry and research to provide basic and advanced data analysis and modeling for a wide range of disciplines [1]

  • Scalability and performance of PyGRASS

  • The Geographic Resources Analysis Support System (GRASS) 7 development version used for the benchmark has the revision number r54812

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Summary

Introduction

Geographic Information Systems (GIS) have the capabilityto integrate heterogeneous digital data, giving the opportunity to public administration, industry and research to provide basic and advanced data analysis and modeling for a wide range of disciplines [1]. Written in C, and a large number of GIS functions and modules [2]. GRASS provides a large number of models and algorithms that, after substantial testing and trouble shooting, have proven to be very reliable. Its capabilities to process geographical information have been testified by many research and technical papers [3,4,5,6,7,8,9,10,11,12,13,14]

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