Keywords—Laser scanner 3D, Least squares 3D surface matching, Radiometric data, Survey. Abstract— In this contribute we propose an application of a new algorithm for least squares matching of overlapping 3D surfaces that we sampled point by point using a terrestrial laser scanner. The studies on the absolute orientation of stereo models using DEMs as control information are known as DEM matching. The proposed method estimates the transformation parameters between two (or more) fully 3D surface patches and minimizes the Euclidean distances instead of Z-differences between the surfaces by least squares. The application in question is aimed, in the study of deformations of mountain areas, as well as test the TLS applied to a hilly area. For this purpose, it was also tested using the algorithm LS3D “Least squares 3D surface matching” that allows both the registration of point clouds produced by scans carried out without using targets but, overall, the estimate of deformations that in this case, compared to other methods, is done directly on the basis of the two data sets acquired in two different eras. I. INTRODUCTION AND STUDY AREA HE Faculty of Agriculture of the University "Mediterranea" of Reggio Calabria is built on a hill that offers a specific geomorphology. In fact, after the construction of the Faculty building some problems arose, regarding its stability, the possible deformations through time also because of poor vegetation. The Laboratory of Geomatics Engineering Faculty of the University "Mediterranea" of Reggio Calabria, used Terrestrial Laser Scanner for monitoring the hill, doing the scans after three years and examining the results obtained. Every era we made two scans, that we found to be sufficient to cover the entire study area. In photogrammetry, the problem statement of surface patch matching and its solution method was first addressed by Gruen (1985a) as a straight application of Least Squares Matching. The Least Squares Matching concept had been applied to many different types of measurement and feature extraction V. Barrile is with the DICEAM Department, Faculty of Engineering Mediterranean University of Reggio Calabria, Reggio Calabria 89100 IT (phone: +39-0965-875-301; e-mail: vincenzo.barrile@unirc.it). G. M. Meduri is with the DICEAM Department, Faculty of Engineering Mediterranean University of Reggio Calabria, Reggio Calabria 89100 IT (e- mail: giumed@libero.it). G. Bilotta was with the Department of Planning, IUAV University of Venice, Venice 30135 IT. She now collaborates with the DICEAM Department, Faculty of Engineering Mediterranean University of Reggio Calabria, Reggio Calabria 89100 IT (e-mail: giuliana.bilotta@gmail.com). problems due to its high level of flexibility and its powerful mathematical model. If 3D point clouds derived by any device or method represent an object surface, the problem should be defined as a surface matching problem instead of the 3D point cloud matching. This method, Least Squares 3D Surface Matching (LS3D), estimates the 3D transformation parameters between two or more fully 3D surface patches, minimizing the Euclidean distances between the surfaces by least squares. An observation equation is written for each surface element on the template surface patch, i.e. for each sampled point. The geometric relationship between the conjugate surface patches is defined as a 7-parameter 3D similarity transformation. This parameter space can be extended or reduced, as the situation demands it. The constant term of the adjustment is given by the observation vector whose elements are Euclidean distances between the template and search surface elements. An application of the Least Squares 3D algorithm for territorial monitoring and control V. Barrile, G. M. Meduri, and G. Bilotta T Fig. 1 study area Fig. 2 a view of the scanner INTERNATIONAL JOURNAL OF SYSTEMS APPLICATIONS, ENGINEERING & DEVELOPMENT Volume 8, 2014 ISSN: 2074-1308 18