Python for Geosciences
Python for Geosciences – Articles
The aim of this notebook is to explore thebuild Scikit-GStat library and to build a piezometric map based on a variography study and on the building of a kriging model. Finally, the results of the kriging estimation are compared with other standard interpolation techniques and the benefits of geostatistics are discussed.
Recently, several (hydro-)geological datasets and API have been developed and published to facilitate the public access to the subsurface knowledge of France (e.g. geological properties, hydraulic head fluctuations, groundwater quality). The aim of this article is to present some of these web-services to describe the hydrogeological context of a region of interest.
There is an increasing interest in utilizing shallow ground and groundwater as a source for geothermal heating and cooling. Augmented geothermal utilization entails a higher density of installations and potential competition among adjacent systems. This article presents a methodology to define the appropriate distance that should be kept between existing and future installations of different power to protect existing installations and optimally manage the urban thermal use of shallow groundwater.
Introduction to the Google Earth Engine Python API: data catalog exploration, static and interactive mapping
Within the last decade, a huge amount of geospatial data, such as satellite data or the output of large scale models have become freely available from multiple national agencies. In this post, we explore the Google Earth Engine Python API which gives the possibility to manipulate these datasets in a Python environment.
The thermal impact assessment is a crucial step in a geothermal project. Particularly in regards of geothermal energy planning. In this article we explore three analytical solutions which can help to estimate the thermal impact caused by groundwater heat pump systems.
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