GIS Integrated LiDAR Mapping and Its Applications

Lidar (light detection and ranging) is an optical remote-sensing technique that employs laser light to densely sample the earth's surface, yielding highly accurate x, y, z measurements. Lidar, which is mainly used in airborne laser mapping applications, is gaining popularity as a low-cost compared to traditional surveying techniques such as photogrammetry. Lidar generates massive point cloud datasets that can be managed, visualized, and analyzed. A collection vehicle (aircraft, helicopter, vehicle, and tripod), laser scanner system, GPS (Global Positioning System), and INS are the main hardware requirements of a lidar system (inertial navigation system). The lidar system's roll, pitch, and heading are measured by an INS system.

To calculate the range distance between the sensor and the target, the receivers record the precise time from when the laser pulse left the system to when it is returned. When these distance measurements are combined with positional information (GPS and INS), they are transformed into measurements of actual three-dimensional points of the reflective target in object space. After the lidar data collection survey, the point data is post-processed into highly precise georeferenced x, y, z coordinates by analyzing the laser time range, laser scan angle, GPS stance, and INS data.

Lidar Pulse Returns

Laser pulses transmitted by a lidar system reflect from objects on and above the surface of the ground, such as plants, buildings, and bridges. One laser pulse emission can return to the lidar sensor as one or several returns. Any emitted laser pulse that collides with multiple reflection surfaces on its way to the ground is separated into as many returns as there are reflective surfaces. The first laser pulse returned is the most substantial and will be linked with the largest feature in the landscape, such as a treetop or the top of a tower. The first return could also symbolize the ground, so in that case, the lidar system will detect only one return. Multiple returns can identify the elevations of different objects within the laser footprint of an incoming laser pulse. The intermediate returns can be used for vegetation structure, and the last return is used for bare-earth terrain concepts.

Point cloud

Point cloud data is spatially organized lidar data that have been post-processed. The initial point clouds are vast collections of 3D elevation points with x, y, and z coordinates.  After the initial lidar point cloud is post-processed, the specific surface features that the laser encounters are labeled. Point cloud data consists of elevations for the land surface, buildings, forest canopy, highway overpasses, etc that the laser beam experiences during the survey.

Airborne Lidar

The system for airborne lidar is equipped in either a fixed-wing aircraft or a helicopter. The infrared laser energy is transmitted and returned to the moving airborne lidar sensor. Airborne sensors are classified into two types: topographic and bathymetric.

Topographic lidar

Surface models obtained from topographic lidar are being used in a variety of applications, including forestry, hydrology, geomorphology, urban planning, environmental studies, coastal engineering, survey evaluation, and volumetric estimations.

Bathymetric lidar

Bathymetric lidar is a type of water-penetrating airborne acquisition. The majority of bathymetric lidar systems capture elevation and water depth at the same time, resulting in an airborne lidar survey of the land-water interface. The infrared light has reflected the aircraft from the land and water surface during a bathymetric lidar survey, while the additional green laser travels through the water column. Water depths and shoreline elevations are determined using analyses of the two distinct pulses. Bathymetric data is critical near coastlines, harbors, and near shores. Bathymetric data can also be used to detect objects on the ocean bottom.

Terrestrial lidar

Terrestrial lidar accumulates very dense and extremely accurate points, allowing for precise object identification. To name a few applications, these dense point clouds could be used to control facilities, conduct highway and rail surveys, and even generate 3d city models for architecture and spaces.

Mobile Lidar

The gathering of lidar point clouds from a moving platform is known as mobile lidar. Any number of lidar sensors positioned on a moving vehicle can be used in mobile lidar systems. These systems can be installed on automobiles, trains, and even boats. As with airborne lidar systems, mobile systems generally have included a lidar sensor, cameras, GPS (Global Positioning System), and an INS (inertial navigation system). Mobile lidar data is used to evaluate road infrastructure and identify encroaching overhead wires, light poles, and road signs near highways or rail lines.

Applications

• Archaeology: LiDAR can be used in conjunction with drone technology to quickly develop interactive 3D models of archaeological sites. These LiDAR models have the potential to reveal previously undiscovered objects or structures, resulting in new findings.
• Transport Parking: Parking garages and open-air parking lots have started to use LiDAR sensors to count vehicles entering the center and calculate empty parking spaces. These systems necessitate algorithms capable of identifying vehicles of varying shapes and sizes.

• Video Games: LiDAR is used by video game developers to build 3D modes in their games. Analyzing real-world structures and objects enables games set in actual locations to have accurately reproduced surroundings for players to experience.
• Automatic Vehicles: LiDAR sensors can be installed on automated driving vehicles to provide 360-degree exposure and high observation accuracy. Systematic monitoring of the environment around the vehicle provides the data required by the vehicle's processing unit to recognize and securely navigate around obstacles.
• Forest Management: LIDAR is broadly used in the forestry sector to plan and manage forest operations. It is used to determine the vertical structure of the forest canopy, as well as to calculate and grasp canopy bulk density and canopy base height. LIDAR is also used in the forestry sector to estimate root spread by measuring peak height.
• Management of Forest Fires: LIDAR is now becoming incredibly popular in the management of forest fires. The fire department's approach to fire management is shifting from reactive to proactive. The use of LIDAR images to monitor potential fire areas is known as fuel mapping.

• Management of Parks and Tourist industry: The Park and tourism area are planned using LIDAR DEM. A high-accuracy land surface model aids in determining the best location for a playground, trees, and a running track. Park management is a major business, and LIDAR technology is crucial to its success. The park's potential growth will benefit from a 3D image generated by LIDAR technology.
• Building Information Model: GIS is a powerful tool in the energy and utility industries for planning, coordinating, and subsequent expansion of growth. The effective management of energy systems is a difficult task. GIS has tremendous potential for facility planning, architecture, and maintenance. Furthermore, it provides better services at a lower cost.
• Solar Energy: Solar energy is becoming incredibly popular for heating and electricity generation. Solar panels absorb heat from sunlight and convert it to heat or electricity energy. There have been some minimum standards for installing a solar panel that can be identified using LIDAR data.
• Environmental Assessment: Micro topography data derived from LIDAR data is used in environmental assessments. Environmental assessments are performed to protect plants and the ecosystem. Remote sensing and surface information (LIDAR) is being used to identify areas impacted by human activity.

Summary

At SATPALDA, we can integrate LiDAR data with other data sets, including orthophotos, multispectral, hyperspectral, and panchromatic imagery. We can combine LiDAR with GIS data and other survey information to generate complex geomorphic-structure mapping products. LiDAR point clouds can be used to derive a wide variety of geospatial deliverables such as Intensity images, break lines, Digital Terrian Models, Digital Elevation Models, Digital Surface Models, Triangular, irregular Networks, Vegetation layer for analysis, and 3-D Models.