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Yayın A precision estimation method for volumetric changes(IEEE, 2019-06) Akça, Mehmet Devrim; Stylianidis, Efstratios; Gruen, Armin W.; Altan, Mehmet Orhan; Hofer, Martin; Smagas, Konstantinos; Sanchez Martin, Victor; Walli, Andreas; Jimeno, Elisa; Garcia, AlejandroEarth surface changes are often computed by comparing the sequences of digital elevation models (DEMs) so called the DEM of difference (DoD) method. We present an operational DEM generation, co-registration and DoD comparison software in which the surface changes are quantified in metric units of volume. A practical method, which is based on the law of error propagation, is developed to estimate the theoretical precisions of volumetric changes. The proposed pipeline can estimate the change of object volumes (in terms of loss and gain) together with their precision numbers. Change of the forest volume in a fire effected region in a test site is analyzed for the validation. The method can be used for various change detection applications related to forestry as well as other topics such as earthworks, geomorphology, mining, and urbanization.Yayın Stochastic surface mesh reconstruction(International Society for Photogrammetry and Remote Sensing, 2018-05-30) Özendi, Mustafa; Akça, Mehmet Devrim; Topan, HüseyinA generic and practical methodology is presented for 3D surface mesh reconstruction from the terrestrial laser scanner (TLS) derived point clouds. It has two main steps. The first step deals with developing an anisotropic point error model, which is capable of computing the theoretical precisions of 3D coordinates of each individual point in the point cloud. The magnitude and direction of the errors are represented in the form of error ellipsoids. The following second step is focused on the stochastic surface mesh reconstruction. It exploits the previously determined error ellipsoids by computing a point-wise quality measure, which takes into account the semi-diagonal axis length of the error ellipsoid. The points only with the least errors are used in the surface triangulation. The remaining ones are automatically discarded.Yayın Laboratory flume experiment with a coded structured light system(International Society for Photogrammetry and Remote Sensing, 2012) Akça, Mehmet Devrim; Seybold, HansjorgThe topography of inland deltas is influenced chiefly by the water-sediment balance in distributary channels and local evaporation and seepage rates. In a previous study, a reduced complexity model has been applied to simulate the process of inland delta formation. Results have been compared with the Okavango Delta, Botswana and with a laboratory experiment. Both in the macro scale and the micro scale cases, high quality digital elevation models (DEM) are essential. This work elaborates the laboratory experiment where an artificial inland delta is generated on laboratory scale and its topography is measured using a Breuckmann 3D scanner. The space-time evolution of the inland delta is monitored in the consecutive DEM layers. Regarding the 1.0m x 1.0m x 0.3m size of the working area, better than 100 micron precision is achieved which gives a relative precision of 1/10 000. The entire 3D modelling workflow is presented in terms of scanning, co-registration, surface generation, editing, and visualization steps. The co-registered high resolution topographic data allows us to analyse the stratigraphy patterns of the experiment and gain quantitative insight into the spatio-temporal evolution of the delta formation process.Yayın Photogrammetric monitoring of an artificially generated shallow landslide(Wiley-Blackwell, 2013-06) Akça, Mehmet DevrimAn artificial rainfall event was applied to a forested slope in Ruedlingen, northern Switzerland. The experiment triggered a landslide which resulted in mobilising about 130m3 of debris. The event was monitored by a photogrammetric network of four cameras, operating at 5 to 8 frames per second, in order to quantify spatial and temporal changes by tracking tennis balls pegged into the ground. Image measurements were performed using automated image matching methods, implemented through a software package developed in-house. Three-dimensional coordinates of the target points were estimated by running a customised type of bundle adjustment, achieving a positioning precision of +/- 1 center dot 8cm.Yayın Photogrammetric deformation monitoring of the second Bosphorus Bridge in Istanbul(International Society for Photogrammetry and Remote Sensing, 2014) Avşar, Özgür; Akça, Mehmet Devrim; Altan, Mehmet OrhanImproving the efficiency of bridge inspection and minimizing the impact of dynamic load on the long term deterioration of the bridge structure reduces maintenance and upkeep costs whilst also improving bridge longevity and safety. This paper presents the results of an on-going project whose ultimate goal is the real-time photogrammetric monitoring the structural deformations of the second Bosphorus Bridge of Istanbul.Yayın An emprical point error model for TLS derived point clouds(International Society for Photogrammetry and Remote Sensing, 2016) Özendi, Mustafa; Akça, Mehmet Devrim; Topan, HüseyinThe random error pattern of point clouds has significant effect on the quality of final 3D model. The magnitude and distribution of random errors should be modelled numerically. This work aims at developing such an anisotropic point error model, specifically for the terrestrial laser scanner (TLS) acquired 3D point clouds. A priori precisions of basic TLS observations, which are the range, horizontal angle and vertical angle, are determined by predefined and practical measurement configurations, performed at real-world test environments. A priori precision of horizontal (??) and vertical (??) angles are constant for each point of a data set, and can directly be determined through the repetitive scanning of the same environment. In our practical tests, precisions of the horizontal and vertical angles were found as ??=±36.6 and ??=±17.8, respectively. On the other hand, a priori precision of the range observation (??) is assumed to be a function of range, incidence angle of the incoming laser ray, and reflectivity of object surface. Hence, it is a variable, and computed for each point individually by employing an empirically developed formula varying as ??=±2a'12 mm for a FARO Focus X330 laser scanner. This procedure was followed by the computation of error ellipsoids of each point using the law of variance-covariance propagation. The direction and size of the error ellipsoids were computed by the principal components transformation. The usability and feasibility of the model was investigated in real world scenarios. These investigations validated the suitability and practicality of the proposed method.Yayın Co-registration of 3d point clouds by using an errors-in-variables model(Copernicus Gesellschaft MBH, 2012-08-25) Aydar, Umut; Altan, Mehmet Orhan; Akyılmaz, Orhan; Akça, Mehmet DevrimCo-registration of point clouds of partially scanned objects is the first step of the 3D modeling workflow. The aim of co-registration is to merge the overlapping point clouds by estimating the spatial transformation parameters. In the literature, one of the most popular methods is the ICP (Iterative Closest Point) algorithm and its variants. There exist the 3D least squares (LS) matching methods as well. In most of the co-registration methods, the stochastic properties of the search surfaces are usually omitted. This omission is expected to be minor and does not disturb the solution vector significantly. However, the a posteriori covariance matrix will be affected by the neglected uncertainty of the function values. This causes deterioration in the realistic precision estimates. In order to overcome this limitation, we propose a new method where the stochastic properties of both (template and search) surfaces are considered under an errors-in-variables (EIV) model. The experiments have been carried out using a close range laser scanning data set and the results of the conventional and EIV types of the ICP matching methods have been compared.Yayın Pre- and post-fire comparison of forest areas in 3D(Springer Berlin Heidelberg, 2019) Akça, Mehmet Devrim; Stylianidis, Efstratios; Poli, Daniela; Gruen, Armin W.; Altan, Mehmet Orhan; Hofer, Martin; Smagas, Konstantinos; Martin, Victor Sanchez; Walli, Andreas; Jimeno, Elisa; Garcia, AlejandroA satellite processing platform for high resolution forest assessment (FORSAT) was developed. It generates the digital surface models (DSMs) of the forest canopy by advanced processing of the very-high resolution (VHR) optical satellite imagery and automatically matches the pre- and post-fire DSMs for 3D change detection. The FORSAT software system can perform the following tasks: pre-processing, point measurement, orientation, quasi-epipolar image generation, image matching, DSM extraction, orthoimage generation, photogrammetric restitution either in mono-plotting mode or in stereo models, 3D surface matching, co-registration, comparison and change detection. It can thoroughly calculate the planimetric and volumetric changes between the epochs. It supports most of the VHR optical imagery commonly used for civil applications. Capabilities of FORSAT have been tested in two real forest fire cases, where the burned areas are located in Cyprus and Austria. The geometric characteristics of burned forest areas have been identified both in 2D plane and 3D volume dimensions, using pre- and post-fire optical image data from different sensors. The test studies showed that FORSAT is an operational software capable of providing spatial (3D) and temporal (4D) information for monitoring of forest fire areas and sustainable forest management. Beyond the wildfires, it can be used for many other forest information needs.Yayın Precursors of instability in a natural slope due to rainfall: a full-scale experiment(Springer Heidelberg, 2018-09) Askarinejad, Amin; Akça, Mehmet Devrim; Springman, Sarah MarcellaA full-scale landslide-triggering experiment was conducted on a natural sandy slope subjected to an artificial rainfall event, which resulted in mobilisation of 130m(3) of soil mass. Novel slope deformation sensors (SDSs) were applied to monitor the subsurface pre-failure movements and the precursors of the artificially triggered landslide. These fully automated sensors are more flexible than the conventional inclinometers by several orders of magnitude and therefore are able to detect fine movements (<1mm) of the soil mass reliably. Data from high-frequency measurements of the external bending work, indicating the transmitted energy from the surrounding soil to these sensors, pore water pressure at various depths, horizontal soil pressure and advanced surface monitoring techniques, contributed to an integrated analysis of the processes that led to triggering of the landslide. Precursors of movements were detected before the failure using the horizontal earth pressure measurements, as well as surface and subsurface movement records. The measurements showed accelerating increases of the horizontal earth pressure in the compression zone of the unstable area and external bending work applied to the slope deformation sensors. These data are compared to the pore water pressure and volumetric water content changes leading to failure.Yayın Total least squares registration of 3D surfaces(Copernicus GmbH, 2013-10-16) Aydar, Umut; Akça, Mehmet Devrim; Altan, Mehmet Orhan; Akyılmaz, OrhanCo-registration of point clouds of partially scanned objects is the first step of the 3D modeling workflow. The aim of coregistration is to merge the overlapping point clouds by estimating the spatial transformation parameters. In computer vision and photogrammetry domain one of the most popular methods is the ICP (Iterative Closest Point) algorithm and its variants. There exist the 3D Least Squares (LS) matching methods as well (Gruen and Akca, 2005). The co-registration methods commonly use the least squares (LS) estimation method in which the unknown transformation parameters of the (floating) search surface is functionally related to the observation of the (fixed) template surface. Here, the stochastic properties of the search surfaces are usually omitted. This omission is expected to be minor and does not disturb the solution vector significantly. However, the a posteriori covariance matrix will be affected by the neglected uncertainty of the function values of the search surface. . This causes deterioration in the realistic precision estimates. In order to overcome this limitation, we propose a method where the stochastic properties of both the observations and the parameters are considered under an errors-in-variables (EIV) model. The experiments have been carried out using diverse laser scanning data sets and the results of EIV with the ICP and the conventional LS matching methods have been compared.
