3D change detection – Approaches and applications

TLDR: This paper reviews the recent developments and applications of 3D CD using remote sensing and close-range data, in support of both academia and industry researchers who seek for solutions in detecting and analyzing 3D dynamics of various objects of interest.

Abstract: Due to the unprecedented technology development of sensors, platforms and algorithms for 3D data acquisition and generation, 3D spaceborne, airborne and close-range data, in the form of image based, Light Detection and Ranging (LiDAR) based point clouds, Digital Elevation Models (DEM) and 3D city models, become more accessible than ever before Change detection (CD) or time-series data analysis in 3D has gained great attention due to its capability of providing volumetric dynamics to facilitate more applications and provide more accurate results The state-of-the-art CD reviews aim to provide a comprehensive synthesis and to simplify the taxonomy of the traditional remote sensing CD techniques, which mainly sit within the boundary of 2D image/spectrum analysis, largely ignoring the particularities of 3D aspects of the data The inclusion of 3D data for change detection (termed 3D CD), not only provides a source with different modality for analysis, but also transcends the border of traditional top-view 2D pixel/object-based analysis to highly detailed, oblique view or voxel-based geometric analysis This paper reviews the recent developments and applications of 3D CD using remote sensing and close-range data, in support of both academia and industry researchers who seek for solutions in detecting and analyzing 3D dynamics of various objects of interest We first describe the general considerations of 3D CD problems in different processing stages and identify CD types based on the information used, being the geometric comparison and geometric-spectral analysis We then summarize relevant works and practices in urban, environment, ecology and civil applications, etc Given the broad spectrum of applications and different types of 3D data, we discuss important issues in 3D CD methods Finally, we present concluding remarks in algorithmic aspects of 3D CD

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Table 4. Examples of 3D CD applications

Figure 1. Different geometric comparison methods. (a) Height difference, distances are computed vertically. (b) Euclidean distances, distances are computed in the surface normal direction. (c) projection-based inter-correlation method, the geometric difference is computed by projecting image on to the object, and then back project to image as ; the differences are given by measuring the differences between and .

Table 3. An overview of the current 3D change detection methods

Table 5. Recommendations on data co-registration (ordered by priority)

Table 1. Overview of the differences between 3D and 2D CD problems

Table 2. Key considerations in a 3D CD task