An example C# application to display STAC information.
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This code may be used to create a STAC client using C#. STAC is a specification for transferring metadata in JSON format between a STAC server and a STAC client. The metadata describes spatio-temporal data such as satellite imagery. While other examples of STAC clients are written in JavaScript, this STAC client is written in C#.
The goals of this project are to:
- discover problems with STAC JSON generated by STAC servers
- find bugs in the DotNetStac library
- explore limitations of the STAC specification with respect to non-browser clients
This client must be built using Microsoft's Visual Studio. Clone this repository using git (or download the zip), open the StacCommand.sln with Visual Studio and build the project.
Once you've built the StacCommand executable, you can execute staccommand.exe:
C:\>staccommand.exe
usage:
staccommand <stac Uri>
Using a STAC URI for input:
C:\>StacCommand.exe https://earthengine-stac.storage.googleapis.com/catalog/catalog.json
STAC URI: https://earthengine-stac.storage.googleapis.com/catalog/catalog.json
Catalog ID:GEE_catalog
Description: List of all rasters and vectors present in the [Google Earth Engine Catalog](https://developers.google.com/earth-engine/datasets/).
STAC Version: 1.0.0-beta.2
AAFC/ACI: Starting in 2009, the Earth Observation Team of the Science and Technology
Branch (STB) at Agriculture and Agri-Food Canada (AAFC) began the process
of generating annual crop type digital maps. Focusing on the Prairie
Provinces in 2009 and 2010, a Decision Tree (DT) based methodology was
applied using optical (Landsat-5, AWiFS, DMC) and radar (Radarsat-2) based
satellite images. Beginning with the 2011 growing season, this activity has
been extended to other provinces in support of a national crop inventory.
To date this approach can consistently deliver a crop inventory that meets
the overall target accuracy of at least 85% at a final spatial resolution of
30m (56m in 2009 and 2010).
AHN/AHN2_05M_INT: The AHN DEM is a 0.5m DEM covering the Netherlands. It was generated from LIDAR data taken in the spring between 2007 and 2012.
It contains ground level samples with all other items above ground (such as buildings, bridges, trees etc.) removed. This version is interpolated; the areas where objects have been removed are filled with interpolated values. The point cloud was converted to a 0.5m grid using a squared inverse distance weighting method.
Note: This dataset does not include a small number of tiles listed in the manifest that are only available at a lower resolution.
See the open issues for a list of proposed features (and known issues).
Contributions are what make the open source community such an amazing place to be learn, inspire, and create. Any contributions you make are greatly appreciated.
- Fork the Project
- Create your Feature Branch (
git checkout -b feature/AmazingFeature) - Commit your Changes (
git commit -m 'Add some AmazingFeature') - Push to the Branch (
git push origin feature/AmazingFeature) - Open a Pull Request
Distributed under the MIT License. See LICENSE for more information.
Brent Fraser - @GeoAnalyticInc - [email protected]
Project Link: https://github.com/GeoAnalytic-code/daas-catclient
A portion of this work was generously supported through the GeoConnections programme, part of Canada's Spatial Data Infrastructure.