Ready for Immediate Use
The prompt and effective way to decision making
Enabling Rapid Implementation of Applications
Enabling rapid implementation of applications
Data often requires extensive processing before it can be utilized in processes. Analysis ready data (ARD) can be used immediately in analysis tools and models and turned into insights without further delay. Extensive processing steps such as calibration, correction, or classification are already taken care of. ARD can also serve as input for higher-level processing, skipping several steps and focusing on custom-specific formats and parameters.
Utility Network Data for 3D Analysis, Modeling and Visualization
Utility companies need to regularly analyze their networks and model specific impacts on network stability, risk identification and optimization of asset management activities for inspection, repair, and replacement.
Our high-definition LiDAR data is the ideal source to accurately construct a digital 3D representation of utility’s infrastructure. Assets such as poles and wires can be accurately built and visualized in their real-world location to centimeter precision. Once constructed, these spatially accurate 3D vectors can be attributed with a host of data ranging from the utility’s design and planning data to analytic results such as vegetation encroachment.
Available vector layers include:
Forest Structure and Tree Attributes for Monitoring, Inventory, and Management
Forest observations are vital for understanding the ecosystem and natural resources of our planet. However, measuring the forest structure characteristics at a large-scale is a major challenge for forestry managers, especially in complex and dense forests.
VeriDaaS’ high-resolution GML offers an unusual solution that works particularly well in densely vegetated forests. Its unique acquisition geometry with up to 30 oblique looks facilitates the visibility through the foliage and makes it the ideal system for constructing a realistic and precise 3D digital twin of forests.
We provide LiDAR data segmented into individual tree polygons that are attributed with the tree’s height and crown size. Additional attributes, ranging from tree health to fall-in potential, can be determined and coupled to polygons. The data also supports canopy surface models (CSM) and canopy height models (CHM).
Forest observations are vital for understanding the ecosystem and natural resources of our planet. However, measuring the forest structure characteristics at a large-scale is a major challenge for forestry managers, especially in complex and dense forests.
VeriDaaS’ high-resolution GML offers an unusual solution that works particularly well in densely vegetated forests. Its unique acquisition geometry with up to 30 oblique looks facilitates the visibility through the foliage and makes it the ideal system for constructing a realistic and precise 3D digital twin of forests.
We provide LiDAR data segmented into individual tree polygons that are attributed with the tree’s height and crown size. Additional attributes, ranging from tree health to fall-in potential, can be determined and coupled to polygons. The data also supports canopy surface models (CSM) and canopy height models (CHM).
