Displaying 1 to 8 from 8 results

geoserver - Official GeoServer repository

  •    Java

GeoServer is an open source software server written in Java that allows users to share and edit geospatial data. Designed for interoperability, it publishes data from any major spatial data source using open standards. Being a community-driven project, GeoServer is developed, tested, and supported by a diverse group of individuals and organizations from around the world.

DotOGC

  •    CSharp

.NET OGC Service (WMS, WFS, WPS, CSW, ...)




gsky - Distributed Scalable Geospatial Data Server

  •    Go

GSKY was developed at NCI and is a scalable, distributed server which presents a new approach for geospatial data discovery and delivery using OGC standards. The most recent release is here. The quickest way to try out GSKY is via GSKY docker image.

Tempus - C++ framework to develop multimodal path planning requests

  •    

This is the main git repository for sources of Tempus, a framework for multimodal route planning. Clone this repo with the --recursive option (or use git submodule init && git submodule update after cloning it), then head over to the README of each submodule for instructions.

raven - Hydrological modeling and calibration WPS services

  •    Python

Raven is an open source server project offering hydrological modeling and analysis capabilities through the Web Processing Service (WPS) standard. Raven processes can be embedded in a graphical user interface or accessed directly from a programming environment. From Python, birdy WPSClient provides a user-friendly python interface to Raven's WPS processes. Raven was made to help scientists run hydrological modeling experiments with climate change projections. It includes four lumped daily hydrological models (GR4J-CN, HBV-EC, HMETS, MOHYSE) that can be run in multi-model experiments. Meteorological input variables as well as streamflow and storage outputs use the netCDF format. Raven bundles model calibration processes, time series analysis (with xarray), hydrological indicators and frequency analysis (using xclim). On top of this, a database of pre-calibrated model parameters over North America is available to perform model regionalization, allowing simulations in watersheds with no streamflow observations. The properties of custom watersheds can be extracted from a Digital Elevation Model and a land-use database.

gis4wrf - QGIS toolkit 🧰 for pre- and post-processing 🔨, visualizing 🔍, and running simulations 💻 in the Weather Research and Forecasting (WRF) model 🌀

  •    Python

GIS4WRF is a free and open source QGIS plug-in to help researchers and practitioners with their Advanced Research Weather Research and Forecasting modelling workflows. GIS4WRF can be used to pre-process input data, run simulations, and visualize or post-process results. We offer MPI-enabled pre-built binary distributions for Windows, macOS and Linux through WRF-CMake. For information on how to install GIS4WRF, or check out the main documentation and tutorials, please refer to the GIS4WRF website. If you use GIS4WRF in a published work, please cite both the paper (https://doi.org/10.1016/j.envsoft.2018.10.018), and the specific version of GIS4WRF you are using (https://doi.org/10.5281/zenodo.1288569).







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