LIDAR


Excel Geomatics has a team of highly qualified remote sensing LiDAR professionals with experiences in different domains. The group has developed several processes and algorithm to automate the process of LIDAR data classification and analysis. Various tools have been developed to undertake stringent quality checks to provide world-class quality data.
Excel Geomatics provides services in the following areas using Lidar data-

Bare Earth Edits and DTM

Editing of LiDAR cloud points is done to separate out ground surface features from other features. This is done first by running the tool to classify all the points into two general classes i.e. Ground and Non Ground. All the wrongly classified ground and non-ground points are then manually checked and modified into their proper classes. The aim of manual intervention is to improved the accuracy of classification and create a superior quality data representing the ‘Bare Earth’ or ‘DTM’

LiDAR Sub-classification

This is the process wherein Non-Ground LiDAR point clouds are classified into various categories depending upon client’s requirement. The sub-classification is done in two steps. In the first step, basic classification of LiDAR point clouds is done using different tools either available in the ‘LiDAR Processing Software’ or the ‘Tools Developed In-house.’ In the second step, each wrongly classified point cloud is verified and manipulated individually to classify the points in their respective correct category. The general classification schemes that are used for different purposes are

    i) Ground
    ii) Low Vegetation
    iii) High Vegetation
    iv) Water Bodies
    v) Residential Building
    vi) Commercial Building
    vii) Industrial Building
    viii) Bridge
    ix) Road/Highway
    x) Light Pole
    xi) Electrical Pole
    xii) Tower
    xiii) Shield Wire/Transmission Tower
    xiv) Transformer
    xv) Electrical Substation etc.

Hydrographic Reinforcement

LiDAR cloud points are scattered when they interact with water. As a result of when the height of Rivers or Lakes is extracted from LiDAR data, they don’t follow the natural rule of gravity. Height of the river doesn’t decrease in the downstream direction and also the lakes are not at constant height. Necessary modification is done in the data with the help of tools and manual intervention to ensure that-

    • Boundaries of Lakes/Ponds are at uniform elevation level
    • Rivers are having same altitude on both sides
    • Rivers are flowing in downstream direction for the entire length of the  River
    • Borders of river body is well defined

Hydrographic Reinforcement

Excel Geomatics provide two types of 3D mapping services using LiDAR data sets.

• 2D data captured from ortho image and then height assigned using LiDAR data. In this case mostly a single height is assigned to each polygon, except for river bodies, where height changes in both upstream and downstream directions.
Example- Maximum height of building extracted from LiDAR data after digitizing building footprint from ortho-rectified aerial imageries.

• Heads on digitization over the 3D LiDAR data to extract height information of each feature. In this case height is assigned to each node of the digitized feature.

Example- Digitization of transmission wire/shield wire on the top of LiDAR data in 3D view, to extract the height of wires. In this height for each node of the digitized wire is extracted from LiDAR data. Following table shows the list of general features being captured during 3D mapping using LiDAR data

Height Models & Contours

LiDAR cloud points are classified, modified and manually edited to create different types of height layers for different applications. Some of the major height layers produced for different clients is as follows-

• DTM- Digital Terrain Model represents the bare earth surface
• DHM- Digital Height Model represents the building height over the bare earth. It is a combination of Absolute building height and DTM
• Vegetation Model- This model represent the different categories of  vegetation height over the terrain
• DSM- Digital Surface Model represents terrain including buildings and vegetation
• Contours are generated from DTM. Different algorithms are applied on contours to smoothen them and make them presentable

Data Modeling, Analysis and Reporting

Once the different features are classified in LiDAR point clouds, they are analyzed to get requisite information. This data analysis is different for different features. Depending upon the requirement, different analysis is done and report is prepared.

These analyses include information on-

• Tree height
• Trunk diameter
• Volume of mineral/rock dump
• Cut and Fill Analysis
• Obstruction in the Fresnel zone
• Longitudinal and Transverse Section creation and analysis, etc.