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The increasing availability of three-dimensional point clouds, including both airborne laser scanning and digital aerial photogrammetry, allow for the derivation of forest inventory information with a high level of attribute accuracy and spatial detail. When available at two points in time, point cloud datasets offer a rich source of information for detailed analysis of change in forest structure.

Existing research across a broad range of forest types has demonstrated that those analyses can be performed using different approaches, levels of detail, or source data. By reviewing the relevant findings, we highlight the potential that bi- and multi-temporal point clouds have for enhanced analysis of forest growth. We divide the existing approaches into two broad categories— – approaches that focus on estimating change based on …