LiDAR technology plays a significant role in Geospatial technology. Like other GIS, GPS, and Remote Sensing, it is also embellished with buzz technologies like big data, AI, ML, IoT, and AR. This technology is known for its massive data, i.e., millions of points, which is also called a point cloud. Thanks to the latest advancement in computing, data handling and sensor technology in increasing resolving power and decreasing weight (size), which is enabling us to mount a sensor in a variety of platforms, carriers, and collecting highly detailed data with ease, and at a very significant size on our hard disks. In this paper, the author attempted to discuss data flow right from data collection until it is used at real ground scenarios using big data concepts, how the aspect and nature of LiDAR data points and its attributes are used to handle this data using principles and concepts of big data for processing and creating outputs. Compare other remote sensing images with the LiDAR outputs such as intensity images, digital elevation model, digital house model, vegetation, and bare earth. Compare and contrast LiDAR data and other types of data in Big data processing scenarios. Concepts related to transformations from LiDAR points to outputs through lossless data processing technique with acceptable quality. Data reading methods and point-cloud handling techniques are discussed. Furthermore, the data flow from the sensor to processing software and final usability in GIS software is illustrated. Finally, future scenarios of BIG data as per the LiDAR technology related to various 3D city modeling applications are also discussed.
Volume 12 | Issue 2
Pages: 2502-2509
DOI: 10.5373/JARDCS/V12I2/S20201298