What is a point cloud in the context of 3D modeling?

A point cloud refers to a collection of data points in a three-dimensional coordinate system. These points are typically generated by 3D scanners or LiDAR (Light Detection and Ranging) technologies, which capture the external shape and configuration of physical objects and landscapes. Each point in the cloud represents a position in space, often accompanied by additional information such as color or intensity, effectively creating a detailed representation of the scanned environment. This data is crucial for various applications, including GIS, architecture, and urban planning, as it allows for accurate modeling and analysis of real-world structures and terrains.

The other choices do not capture the specific definition of a point cloud. A collection of geographic data points, while somewhat related, is too vague and does not emphasize the three-dimensional aspect. A database for storing point data only fails to highlight the significant role of spatial data acquisition technologies. A visualization technique for 2D maps is unrelated to point clouds, which are inherently three-dimensional in nature. Understanding point clouds is essential in GIS and spatial analysis, making the concept foundational for grasping 3D modeling processes.