Search Results for "raw"

Welcome to the GeoGig project, exploring the use of distributed management of spatial data. GeoGig draws inspiration from Git, but adapts its core concepts to handle versioning of geospatial data. Users are able to import raw geospatial data (currently from Shapefiles, PostGIS or SpatiaLite) in to a repository where every change to the data is tracked. These changes can be viewed in a history, reverted to older versions, branched in to sandboxed areas, merged back in, and pushed to remote repositories.

...The program "Fielddata Mgr", is customized for the Rick survey department, in such that it supports up to 9 chiefs, each having their own folder in one location, 2 supervisers, each with a PC on the network, and access to a main server. Each day, the .RAW file is copied to the appropriate chiefs folder and when Fielddata Mgr is run, or the reload button is clicked, all .RAW files are listed along with a long list of all job folders existing in a designated location, and a short list of frequently accessed jobs that are selected from within the long list. When a .RAW file is selected, the contents are read, interpreted, and the results displayed within the program window. ...

UPDATE March 14, 2018 Repository and tracking officially moved to github. https://github.com/opticks-org/opticks Sourceforge mailing lists are still in use. Opticks is an open source remote sensing application and development framework.

...Use this URL to get to the GeoGig downloads: https://sourceforge.net/p/geogig Welcome to the GeoGit project, exploring the use of distributed management of spatial data. GeoGit draws inspiration from Git, but adapts its core concepts to handle versioning of geospatial data. Users are able to import raw geospatial data (currently from Shapefiles, PostGIS or SpatiaLite) in to a repository where every change to the data is tracked. These changes can be viewed in a history, reverted to older versions, branched in to sandboxed areas, merged back in, and pushed to remote repositories.

A new algorithm for extracting roof tops was developed. Using the assumption that roof tops are planar in construction, a new approach was developed using volume of point clouds to determine whether a cluster contains planar points. This approach yields very promising results and with attention applied to its weaknesses, should provide another algorithm which can rival currently available roof top detection methods.