Speaker
Description
Fortran's dominance in high-performance computing (e.g., climate modeling, finite element analysis, reactive transport in porous media) is hindered by its lack of native support for geospatial data operations. Fortran Numerical libraries often rely on cumbersome custom I/O routines for reading, writing, and reprojecting spatial data. This work presents a solution: the development and implementation of Fortran bindings with modern interfaces to the foundational geospatial libraries PROJ (library for coordinate transformation) and GDAL (library to read geospatial data) Their practical application is demonstrated through integration into ATALIB, a geostatistical library implemented in modern Fortran. This integration decouples ATALIB's computational core from its I/O limitations, enabling direct access to data from cloud storage, web services, and hundreds of formats via GDAL, with precise spatial coordinate and transformation ensured by PROJ. A case study on a large 2D kriging operation benchmarks the new implementation against a legacy version, quantifying significant gains in interoperability and processing efficiency. The development of Fortran bindings to the geospatial libraries GDAL and PROJ is a transformative strategy that allows the Fortran community to improve the interoperability of decades of performance optimized code without compromising computational efficiency.
