Methods for extracting e.g. trees from LMMS data are certainly under development at different research institutes, but cannot yet be viewed as well established. It is still notably considered challenging to successfully identify individual trees from part of a point cloud classified as sampling trees.
IQmulus integrates the latest research results in data processing and visualization into a Cloud-based platform for solving important real-life challenges in geospatial applications. New and emerging data acquisition techniques provide fast and efficient means for multi-dimensional spatial data collection. Such raw data is generally big, and includes point clouds and digital images, often enriched with other sensor and thematic data. IQmulus providing a platform to process massive amounts of geospatial big data and serving useful knowledge in a form of processing algorithms developed by the project. The platform is scalable in processing and storage capacity, and capable of handling the four Big Data aspects of variety, volume, velocity and analytics.
IQmulus has begun its Exploitation and Maintenance Period as of 1st November 2016.
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Presentation: Visualising Point Clouds and Surfaces on the IQmulus Project
HR Wallingford Exchange Forum, Howbery Park,19th July 2017
The IQmulus project addressed the challenge of taking geospatial point cloud and coverage data and interpreting it with functions such as interpolation, feature detection and change detection so that it could be more easily used for decision-making tasks. One key aspect of HR Wallingford’s role on the project was to investigate processing and visualising bathymetry datasets using the SeaZone holdings of bathymetry surveys. The purpose of this presentation is to describe and, where possible, demonstrate key visualisation applications developed at HR Wallingford.
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