The increase in the availability of high-resolution lidar and other point cloud datasets has given rise to the use of this data for detecting change in the environment over time. Continual improvements in airborne technology and the miniaturization of the requisite sensors has cultivated a nimble new branch of the industry that provides cost-effective data collection services virtually on demand. This ability to employ temporal analysis of the geospatial landscape has applications in forestry, agriculture, mining, urban planning, civil engineering, and many other fields.

In this presentation, we will use Global Mapper Pro to explore two scenarios in which change has occurred at different scales, and subsequently, we will consider two different procedures for identifying this change.