Editing Photogrammetry (section)

== Integration==

Photogrammetric data can be complemented with range data from other techniques.  Photogrammetry is more accurate in the x and y direction while range data are generally more accurate in the z direction {{Citation needed|date=January 2019}}.  This range data can be supplied by techniques like [[LiDAR]], laser scanners (using [[time of flight]], triangulation or [[interferometry]]), [[Structured-light 3D scanner|white-light digitizer]]s and any other technique that scans an area and returns x, y, z coordinates for multiple discrete points (commonly called "[[point clouds]]").  Photos can clearly define the edges of buildings when the point cloud footprint can not.  It is beneficial to incorporate the advantages of both systems and integrate them to create a better product.

A 3D visualization can be created by georeferencing the aerial photos<ref>[https://37.128.144.2:8443/sitepreview/http/magazine.cmedia.nl/GEO-Informatics_4_2014/index.html#/32/ A. Sechin. Digital Photogrammetric Systems: Trends and Developments. GeoInformatics. #4, 2014, pp. 32-34] {{Webarchive|url=https://web.archive.org/web/20160421184605/https://37.128.144.2:8443/sitepreview/http/magazine.cmedia.nl/GEO-Informatics_4_2014/index.html#/32/ |date=2016-04-21 }}.</ref><ref>{{cite journal | pmc = 3348797 | pmid=22574014 | doi=10.3390/s90402320 | volume=9 | issue=4 | title=An integrated photogrammetric and spatial database management system for producing fully structured data using aerial and remote sensing images | journal= Sensors| pages=2320–33 | last1 = Ahmadi | first1 = FF | last2 = Ebadi | first2 = H| year=2009 | bibcode=2009Senso...9.2320A | doi-access=free }}</ref> and LiDAR data in the same reference frame, [[image rectification|orthorectifying]] the aerial photos, and then draping the orthorectified images on top of the LiDAR grid. It is also possible to create digital terrain models and thus 3D visualisations using pairs (or multiples) of aerial photographs or satellite (e.g. [[SPOT satellite]] imagery). Techniques such as adaptive least squares stereo matching are then used to produce a dense array of correspondences which are transformed through a camera model to produce a dense array of x, y, z data which can be used to produce [[digital terrain model]] and [[Orthophoto|orthoimage]] products. Systems which use these techniques, e.g. the ITG system, were developed in the 1980s and 1990s but have since been supplanted by LiDAR and radar-based approaches, although these techniques may still be useful in deriving elevation models from old aerial photographs or satellite images.