7 skills found
OpenGeoVis / PVGeo🌍 Python package of VTK-based algorithms to analyze geoscientific data and models
softwareunderground / SubsurfaceCore data exchange library for subsurface science and engineering
MiraGeoscience / Geoh5pyPython API for geoh5, an open file format for geoscientific data.
swisstopo / Swissgeol Viewer Suiteswissgeol.ch gives you insight in geoscientific data - above and below the surface
pygeo / Pycmbspython based geoscientific and climate data analyis and model benchmarking tool
xiekangwhu / CWSC Deep Residual NetworkSoil moisture storage capacity (SMSC) links the atmosphere and terrestrial ecosystems, which is required as spatial parameters for geoscientific models, but there are currently no available parameter datasets of SMSC on a global scale especially for hydrological models. Here, we produce a dataset of SMSC parameter for global hydrological models. Parameter calibration of three commonly used monthly water balance models provides the labels for the deep residual network. Calibration on the global grids can significantly reduce parameter discontinuities compared to calibration on individual catchments. The global SMSC is reconstructed at 0.5° resolution by integrating 15 types of meteorological, topographic, and runoff data based on a deep residual network. SMSC products are validated with spatial distribution against root zone depth datasets and validated in terms of simulation efficiency on global grids and 20 catchments from different climatic regions, respectively. We provide the global SMSC parameter dataset as a benchmark for geoscientific modelling by users.
Tari91 / Locating Mineral Deposits Using Deep Learning On Geophysical DataMineral Deposits Detection Suite applies deep learning to predict mineral deposits using synthetic geophysical data. It integrates data simulation, CNN-based modeling, and Excel export, delivering a precise and efficient framework for geoscientific analysis and mineral exploration research.
