Mahmut Onur Karslioglu

Regional vertical total electron content (VTEC) modeling together with satellite and receiver differential code biases (DCBs) using semi-parametric multivariate adaptive regression B-splines (SP-BMARS)

There are various global and regional methods that have been proposed for the modeling of ionospheric vertical total electron content (VTEC). Global distribution of VTEC is usually modeled by spherical harmonic expansions, while tensor products of compactly supported univariate B-splines can be used for regional modeling. In these empirical parametric models, the coefficients of the basis functions as well as differential code biases (DCBs) of satellites and receivers can be treated as unknown parameters which can be estimated from geometry-free linear combinations of global positioning system observables. In this work we propose a new semi-parametric multivariate adaptive regression B-splines (SP-BMARS) method for the regional modeling of VTEC together with satellite and receiver DCBs, where the parametric part of the model is related to the DCBs as fixed parameters and the non-parametric part adaptively models the spatio-temporal distribution of VTEC. The latter is based on multivariate adaptive regression B-splines which is a non-parametric modeling technique making use of compactly supported B-spline basis functions that are generated from the observations automatically. This algorithm takes advantage of an adaptive scale-by-scale model building strategy that searches for best-fitting B-splines to the data at each scale. The VTEC maps generated from the proposed method are compared numerically and visually with the global ionosphere maps (GIMs) which are provided by the Center for Orbit Determination in Europe (CODE). The VTEC values from SP-BMARS and CODE GIMs are also compared with VTEC values obtained through calibration using local ionospheric model. The estimated satellite and receiver DCBs from the SP-BMARS model are compared with the CODE distributed DCBs. The results show that the SP-BMARS algorithm can be used to estimate satellite and receiver DCBs while adaptively and flexibly modeling the daily regional VTEC.

A new differential geometric method to rectify digital images of the Earth's surface using isothermal coordinates

A new method to rectify monoscopic digital images and generate orthoimages of the Earths surface is described. It replaces the standard procedure, which transfers the perspective projection of a frame photograph to an orthographic projection of pixels onto a reference plane using corresponding corrections. Instead, the perspective forward projection is kept but every pixel is vertically mapped along the surface normal onto a curved reference surface, for example, the ellipsoid of the World Geodetic System 1984 under the condition that a precise enough surface elevation model is available. The gained ellipsoidal coordinates (latitude, longitude and height) of each pixel are then transformed into isothermal coordinates like the Universal Transverse Mercator coordinates. Their differential geometric characteristics allow mapping every pixel to a reference plane producing, after some interpolation between irregularly spaced pixels, a photomap with the same geometric properties as any other topographic map. The suitability of the method is demonstrated by two photomaps from Ankara, Turkey, which are compared to high-quality topographic maps whereby the average position errors are about 2-3 pixels.

Lidar for Biomass Estimation

Great attention has been paid to biomass estimation in recent years because biomass can simply be converted to carbon storage which is very important to understand the carbon cycle in the environment. Biomass is typically defined as the oven-dry mass of the above ground portion of a group of trees in forestry (Brown, 1997, 2002; Bartolot and Wynne, 2005; Momba and Bux, 2010). However there are a few studies about below ground biomass estimation. Conventionally, it is estimated using measurements which are recorded on the ground. On the other hand, the large number of studies have confirmed that Lidar as a kind of active remote sensing system is able to estimate biomass properly (Popescu, 2007). Hence time-consuming field works can be avoided and unavailable regions become accessible using a relatively low cost and automated Lidar system. (Nelson et al., 2004; Drake et al., 2002, 2003; Popescu et al., 2003, 2004). Traditional remote sensing systems detect vegetation cover using active and passive optical imaging sensors (Moorthy et al., 2011). Passive systems depend on the variability in vegetation spectral responses from the visible and near-infrared spectral regions. Widely accepted algorithms such as the Normalized Difference Vegetation Index (NDVI) have been empirically correlated to structural parameters (Jonckheere et al., 2006; Solberg et al., 2009; Morsdorf et al., 2004, 2006) such as Leaf Area Index (LAI) of canopy-level. On the contrary to passive optical imaging sensors, which are only capable of providing detailed measurements of horizontal distributions in vegetation canopies, Lidar systems can produce more accurate data in both the horizontal and vertical dimensions (Lim et al., 2003). Lidarbased instruments from space-borne, airborne, and terrestrial platforms provide a direct means of measuring forest characteristics which were unachievable previously by passive remote sensing imagery. Developments in remote sensing technologies, in particular laser scanning techniques, have led to innovative methods and models in the estimation of forest inventories in terms of efficiency and scales (Hudak et al., 2008; Tomppo et al., 2002; Tomppo and Halme, 2004; Zhao et al., 2009; Koch, 2010; Yu et al., 2011). Lidar experiments and researches within the remote sensing community are now focusing to develop robust methodologies. These methods and models employ very precise 3D point cloud data (Omasa et al., 2007) to direct process and retrieve vegetation structural attributes which are validated by in situ measurements of vegetation biophysical parameters (Maas et al., 2008; Cote et al., 2011). Laser scanning systems have been used to extract various kinds of parameters, such as tree height, crown size, diameter at breast height (dbh), canopy density, crown volume, and tree

An interactive program for GPS-based dynamic orbit determination of small satellites

This work introduces a near real-time dynamic orbit determination program for small satellites. A quality check of orbit data on ground is important for satellites with GPS positioning that is only available at discrete time epochs because of the limited power-supply onboard, so that space-borne GPS receivers are switched on/off intermittently, or because of possible malfunctioning of GPS receivers. The method of parameter estimation with space-borne GPS position fixes as observations is based on an extended Gauss-Markoff model which corresponds to a Bayesian least-square estimation with informative priors for the parameter vector. Such an approach in context with a dynamic model determines a best-fitting satellite orbit and allows detecting outliers or bridging of data gaps where GPS measurements are missing. It can also estimate other important parameters such as the satellites drag or radiation pressure coefficients. Observations and parameters are dynamically managed by a database management system. The attached program is written in Visual Basic 5, C/C++ and runs on MS Windows 95/NT or later.

Airborne laser scanning data for snow covered biomass estimation

Airborne laser scanning provides reliable terrain data in terms of 3D coordinates. High resolutions Digital Terrain Models (DTM) are in use for many applications, including change detection of surfaces. Also the estimation of the snow depth by making use of Airborne Laser Scanning (ALS) data acquired in summer and winter is a subject of current investigations. However estimating snow depth seems problematic in vegetation covered areas. This work focuses on the investigation of the snow depth estimation using snow covered vegetation effect. In this aspect a method based on segmentation filter is proposed for snow depth calculation in vegetation covered area by using ALS data. The method demonstrates the performance of the segmentation filter with respect to the adaptability on the vegetated snow covered area. Additionally the influence of the snow covered biomass on the snow depth model is also investigated.Airborne laser scanning provides reliable terrain data in terms of 3D coordinates. High resolutions Digital Terrain Models (DTM) are in use for many applications, including change detection of surfaces. Also the estimation of the snow depth by making use of Airborne Laser Scanning (ALS) data acquired in summer and winter is a subject of current investigations. However estimating snow depth seems problematic in vegetation covered areas. This work focuses on the investigation of the snow depth estimation using snow covered vegetation effect. In this aspect a method based on segmentation filter is proposed for snow depth calculation in vegetation covered area by using ALS data. The method demonstrates the performance of the segmentation filter with respect to the adaptability on the vegetated snow covered area. Additionally the influence of the snow covered biomass on the snow depth model is also investigated.

Near real time orbit detemination of BILSAT-1

Reduced dynamic models combined with GPS-Observations on board the satellites within an extended Kalman Filtering algorithm increases the accuracy of near real time orbit determination.

Updating Fortran programs and other legacy code to an interactive window platform

This paper introduces a hybrid method to update legacy programs, thus combining the visual interactivity of window programs with the qualities of legacy code. Because migration from C, Fortran or Pascal to another programming language is very time-consuming and error-prone, it can be more beneficial to integrate legacy executable files into a visual interactive window shell. Such a shell program is described in this work. Its main part is a multi-file manager with an executable file as the main building block and MyFile as the base class of the resulting UML model. The window shell chosen here runs under the Microsoft Windows 9x/NT/2k/XP operating systems, and the program language to implement the designed shell is Visual Basic. The final shell program was tested with different types of executable files for earth satellite orbit determination, tidal acceleration computation and deformation analysis.

Regional spatio - temporal modeling of the ionospheric Vertical Total Electron Content (VTEC) using Multivariate Adaptive Regression B‒Splines (BMARS)

Spatio‒temporal Regional modeling of the ionosphere in terms of the vertical total electron content (VTEC) is accomplished using a non‒parametric Multivariate Adaptive Regression B‒ Spline (BMARS) algorithm on the basis of Global Positioning System (GPS) observations. The basis functions are constructed as compactly supported tensor products of quadratic B‒Splines which are derived from the observations automatically. A smooth approximation is achieved by scale‒by‒scale model building strategy which searches for best fitting B Spline to the data at each scale. The real data set processed is gathered from ground based GPS stations in Europe and falls within the time interval of the geomagnetic storm on 15 February, 2011. The result of BMARS modeling apparently demonstrates the efficiency and the potential of the method. It is also compared both numerically and visually with a well‒known global and regional VTEC modeling based on spherical harmonics and B‒Splines respectively.

Toward automatic parameter tuning in segmentation method for airborne laser scanning data filtering

Digital terrain model generation (DTM) is one of the main applications of Airborne Laser Scanning (ALS) data which are recorded as the set of 3D point clouds. Processing the large amount of point clouds with manual classification (filtering) methods is very time consuming. Subsequently it needs automatic or semi-automatic algorithms for extracting bare earth by producing DTM. Numerous kinds of filtering methods are developed to extract DTM from point clouds.

GPS-Based Real-Time Orbit Determination of Low Earth Orbit Satellites Using Robust Unscented Kalman Filter

AbstractIn this research, a novel algorithm for real-time orbit determination (RTOD) is presented using the robust unscented Kalman filter (RUKF) with global positioning system (GPS) group and phas...