With over 20 years of experience in advanced spatial analytics, we are trailblazers in utilising remote sensing information, including high-resolution LiDAR and imagery. Our dedicated team combines unparalleled domain knowledge in algorithm development with the latest high-performance computing technologies.

As our technology and algorithms are all developed in-house, we have the ability to customise solutions for our clients. Some of the products that we offer include:

- LiDAR Classification ( ground, culverts, vegetation, buildings, powerlines etc.)
- Asset Identification/Extraction from aerial and mobile data (road corridor assets, city planning)
- AiRAP Star Rating Road Safety Assessments
- Oversize Vehicle Route Clearance/Swept Path Analysis and Transport Modelling (wind turbines, road trains)
- Ground and topographical surveys
- Calculation of forest carbon storage and sequestration
- Hydrology ( Hydrological modelling, hydro-enforced DEM)
- Vegetation Analysis (canopy height model, change detection, tree stratification)
- Habitat Conservation (Malleefowl mound identification)
- Bridge and other vertical clearances
- Building Footprints

LiDAR (Light Detection And Ranging) is an active remote sensing method where a sensor emits and captures short wavelengths of light to measure objects in high resolution. Anditi uses LiDAR from sources as diverse as fixed-wing airplanes, drones, cars, backpacks, and tripods.

You can provide us with your own data or we will acquire the required data for your project using our own units or through our industry leading capture partners, then analyse, assess and quality check the data and extract valuable tailored solutions for your needs.

Big Data describes large sets of diverse data ‒ structured, unstructured, and semi-structured ‒ that are continuously generated at high speed and in high volumes. Many companies now use this data to uncover meaningful insights and improve their decision-making, but they can’t store and process it using traditional data storage and processing units.

Big Data analytics is the process of finding patterns, trends, and relationships in massive datasets that can’t be discovered with traditional data management techniques and tools. In the application of Big Spatial Data sets, Anditi works with data derived from thousands of kilometres of road and Local government areas to provide solutions in an accurate, timely and cost-effective way. Traditionally would take a suit of manual labour and money.

Spatial data analysis refers to a set of techniques designed to find patterns, detect anomalies, or test hypotheses and theories, based on spatial data. - Michael F. Goodchild

Anditi’s 3D Web Portal allows your LiDAR dataset and imagery to be accessed from any location with an internet connection, democratising data and allowing customers the ability to provide different access levels across internal and external stakeholders. Our intuitive and easy to use portal has been designed to import/export multiple file types, enable measurements and annotations, and work seamlessly with other geospatial software, providing a powerful and user-friendly tool for accessing and viewing spatial data.  The cloud-based nature of the portal means it is scalable for any data size or number of users with no need to download software or impact internal system.

Sure! You can test out RoadViewer for free using our sample data. Simply register at portal.anditi.com. Your freemium projects will have a feature limit, but you can purchase a data plan on a per-project basis to unlock the full RoadViewer experience.

Digital Terrain Modelling (DTM) is a topographic model of the bare Earth that can be manipulated by computer programs.
The data files contain elevation data in digital format that relates to a rectangular grid. Vegetation, buildings and other cultural features are removed digitally- leaving just the underlying terrain. DTMs are used especially in civil engineering, geodesy & surveying, geophysics, geography and remote sensing.

The DTM is created by merging point clouds (points collected by LIDAR), bare ground (land surface without vegetation) and digital models of relief maps or representations of the earth's surface. This results in a light detection and ranging (LIDAR) image from which points can be extracted using field measurements or remote sensing methods such as radar interferometry or stereoscopic photogrammetry.

The DTM is processed to create a DEM, which displays height information for each point in space based on its x-y location on an XYZ coordinate system.

Terrain modelling can be used in many industries and fields, including surveying, urban planning, natural and built features augmentation, power lines, land use planning and geology. It is used especially in civil engineering and, geodesy & surveying.

LiDAR delivers a massive point cloud with elevation values. But height can come from the top of buildings, tree canopy, powerlines, and other features. A DSM captures the natural and built features on the Earth’s surface.
A DSM is useful in 3D modeling for telecommunications, urban planning and aviation. Because objects extrude from the Earth, this is particularly useful in these examples:Digital Surface Model (DSM) – Extruding features are tree canopy
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‍RUNWAY APPROACH ZONE ENCROACHMENT: In aviation, DSMs can determine runway obstructions in the approach zone.
‍VEGETATION MANAGEMENT: Along a transmission line, DSMs can see where and how much vegetation is encroaching.
‍VIEW OBSTRUCTION: Urban planners use DSM to check how a proposed building would affect the viewshed of residents and businesses.

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