Rahmi N. Çelik

Height transformation using regional geoids and GPS/levelling in Turkey

Abstract Transformation of ellipsoidal heights derived from the Global Positioning System (GPS) to orthometric heights using geoid models is investigated in the north and west parts of Turkey. Although the transformation depends on a simple relation between ellipsoidal h, orthometric H and geoid N heights, the accuracy of the resulting orthometric heights after transformation is crucial in geodetic and surveying applications. Various factors which affect this accuracy, such as measurement errors, datum inconsistencies and theoretical assumptions, are investigated in this study, while testing different methods in three test networks (Sakarya in the Northwest, Çankırı in the North and Izmir in the West). The study consists of three steps. In the first step the regional Turkey geoids TG99A, TG03 and the European gravimetric geoid EGG97 are tested comparing geoid heights derived from models and GPS/levelling at co–located benchmarks. In the second step, regional geoid models are combined with GPS/levelling using Least Squares Adjustment of height differences and corrector surface models. In this step, additionally, Variance Component Estimation (VCE) using Minimum Norm Quadratic Unbiased Estimation (MINQUE) approach is performed, in order to combine the height sets. In the last step, GPS/levelling surface type local geoids are determined and their performances are tested in transformation of GPS–heights. Finally, the resulting accuracies are compared and practical aspects of those approaches in deriving orthometric heights from GPS measurements in geodetic and surveying applications are discussed.

An Enhanced Real-Time Regional Ionospheric Model Using IGS Real-Time Service (IGS-RTS) Products

Recently, the International Global Navigation Satellite System (GNSS) Service (IGS) has launched the Real-Time Service (IGS-RTS). The RTS products enable real-time precise positioning applications. For single-frequency Real-Time Precise Point Positioning (RT-PPP), ionospheric delay mitigation is a major challenge. To overcome this challenge, we developed a Real-Time Regional Ionospheric Model (RT-RIM) over Europe using the RTS satellite orbits and clock products. The model has spatial and temporal resolution of 1° × 1° and 15 minutes, respectively. Global Positioning System (GPS) observations from 60 IGS and EUREF reference stations are processed using the Bernese 5·2 PPP module in order to extract the Real-Time Vertical Electron Content (RT-VTEC). The PPP convergence time and positioning accuracy using the RTS products is estimated and compared with dual frequency PPP and single-frequency PPP obtained through the combined rapid IGS Global Ionospheric Maps (IGS-GIM) over three consecutive days under high solar activity and one of them under active geomagnetic activity. The results show that the proposed model improves PPP accuracy and convergence time under the mid-latitude region about 40%, 55% and 40% for the horizontal, height and three-dimensional (3D) components respectively in comparison with the IGS-GIM.

Monitoring and Analysing Structural Movements with Precise Inclination Sensors

A multistorey high—rise building has been monitored using microradian precision inclination sensors and the structural movements have been analyzed as consequence of 40 days observation period. In the first step, the time series obtained from inclination sensors’ data were processed with Least Squares Spectral Analysis technique. In documenting the periodicity of the data, the correlation functions were also used as a straightforward way of evaluating the time series. Afterwards the results from the analysis were interpreted and linked to the other observed data such as temperature changes, wind load effects, population in the building and instant earthquake information in the observation period. Further on the results were compared with processed data from consecutive GPS campaigns processes. The study has shown that precise inclination sensors are efficient tools for continuously monitoring and investigating structural movements of large engineering structures.

An improved regional ionospheric model for single-frequency GNSS users

In this study, we develop a regional ionospheric model for single-frequency precise point positioning (PPP) users in Europe. GNSS observations from 60 IGS and EUREF reference stations are processed using the PPP module in the Bernese software to estimate the vertical total electron contents. The developed model has spatial and temporal resolutions of 1° × 1° and 15 minutes, respectively. The resulting model is validated for PPP applications using GNSS observations from another set of stations in three different days. The single-frequency PPP accuracy and convergence time obtained through the developed model are assessed and compared with those obtained through the international GNSS service global ionospheric maps (IGS-GIM). The dual-frequency ionosphere-free PPP is used as a reference. It is shown that the model improves the PPP accuracy and convergence time by about 20, 45 and 45% for the 2D, height and 3D components, respectively, in comparison with the IGS-GIM model.

MGR-DCB: A Precise Model for Multi-Constellation GNSS Receiver Differential Code Bias

In this study, we develop a Multi-constellation Global Navigation Satellite System (GNSS) Receiver Differential Code Bias (MGR-DCB) model. The model estimates the receiver DCBs for the Global Positioning System (GPS), BeiDou and Galileo signals from the ionosphere-corrected geometry-free linear combinations of the code observations. In order to account for the ionospheric delay, a Regional Ionospheric Model (RIM) over Europe is developed. GPS observations from 60 International GNSS Servoce (IGS) and EUREF reference stations are processed in the Bernese-5·2 Precise Point Positioning (PPP) module to estimate the Vertical Total Electron Content (VTEC). The RIM has spatial and temporal resolutions of 1° × 1° and 15 minutes, respectively. The receiver DCBs for three stations from the International GNSS Service Multi-GNSS Experiment (IGS-MGEX) are estimated for three different days. The estimated DCBs are compared with the MGEX published values. The results show agreement with the MGEX values with mean difference and Root Mean Square Error (RMSE) values less than 1 ns. In addition, the combined GPS, BeiDou and Galileo VTEC values are evaluated and compared with the IGS Global Ionospheric Maps (IGS-GIM) counterparts. The results show agreement with the GIM values with mean difference and RMSE values less than 1 Total Electron Content Unit (TECU).

Clustering patient mobility patterns to assess effectiveness of health-service delivery

BackgroundAnalysis of patient mobility in a country not only gives an idea of how the health-care system works, but also can be a guideline to determine the quality of health care and health disparity among regions. Even though determination of patient movement is important, it is not often realized that patient mobility could have a unique pattern beyond health-related endowments (e.g., facilities, medical staff). This study therefore addresses the following research question: Is there a way to identify regions with similar patterns using spatio-temporal distribution of patient mobility? The aim of the paper is to answer this question and improve a classification method that is useful for populous countries like Turkey that have many administrative areas.MethodsThe data used in the study consist of spatio-temporal information on patient mobility for the period between 2009 and 2013. Patient mobility patterns based on the number of patients attracted/escaping across 81 provinces of Turkey are illustrated graphically. The hierarchical clustering method is used to group provinces in terms of the mobility characteristics revealed by the patterns. Clustered groups of provinces are analyzed using non-parametric statistical tests to identify potential correlations between clustered groups and the selected basic health indicators.ResultsIneffective health-care delivery in certain regions of Turkey was determined through identifying patient mobility patterns. High escape values obtained for a large number of provinces suggest poor health-care accessibility. On the other hand, over the period of time studied, visualization of temporal mobility revealed a considerable decrease in the escape ratio for inadequately equipped provinces. Among four of twelve clusters created using the hierarchical clustering method, which include 64 of 81 Turkish provinces, there was a statistically significant relationship between the patterns and the selected basic health indicators of the clusters. The remaining eight clusters included 17 provinces and showed anomalies.ConclusionsThe most important contribution of this study is the development of a way to identify patient mobility patterns by analyzing patient movements across the clusters. These results are strong evidence that patient mobility patterns provide a useful tool for decisions concerning the distribution of health-care services and the provision of health care equipment to the provinces.

Understanding Health Service Delivery Using Spatio-Temporal Patient Mobility Data

This research aims to identify and analyze mobility patterns and trends across eighty-one provinces in Turkey to understand spatio-temporal characteristics of health-service areas at the national level. In the study we focus on classification of mobility characteristics of different health administration areas with a comprehensive spatial and temporal perspective. We identified four major clusters in addition to several smaller and isolated ones. Statistical tests show that groups identified by clustering patient mobility data correlate, in a statistically significant manner, with all but one of the basic health-care indicators considered. Our analysis identifies several important patterns revealing the level of effectiveness of Turkish health-care delivery in certain regions.

An accurate Kriging-based regional ionospheric model using combined GPS/BeiDou observations

Abstract In this study, we propose a regional ionospheric model (RIM) based on both of the GPS-only and the combined GPS/BeiDou observations for single-frequency precise point positioning (SF-PPP) users in Europe. GPS/BeiDou observations from 16 reference stations are processed in the zero-difference mode. A least-squares algorithm is developed to determine the vertical total electron content (VTEC) bi-linear function parameters for a 15-minute time interval. The Kriging interpolation method is used to estimate the VTEC values at a 1 ° × 1 ° grid. The resulting RIMs are validated for PPP applications using GNSS observations from another set of stations. The SF-PPP accuracy and convergence time obtained through the proposed RIMs are computed and compared with those obtained through the international GNSS service global ionospheric maps (IGS-GIM). The results show that the RIMs speed up the convergence time and enhance the overall positioning accuracy in comparison with the IGS-GIM model, particularly the combined GPS/BeiDou-based model.

Analysis of big patient mobility data for identifying medical regions, spatio-temporal characteristics and care demands of patients on the move

BackgroundPatient mobility can be defined as a patient’s movement or utilization of a health care service located in a place or region other than the patient’s place of residence. Mobility provides freedom to patients to obtain health care from providers across regions and even countries. It is essential to monitor patient choices in order to maintain the quality standards and responsiveness of the health system, otherwise, the health system may suffer from geographic disparities in the accessibility to quality and responsive health care. In this article, we study patient mobility in a national health care system to identify medical regions, spatio-temporal and service characteristics of health care utilization, and demands for patient mobility.MethodsWe conducted a systematic analysis of province-to-province patient mobility in Turkey from December 2009 to December 2013, which was derived from 1.2 billion health service records. We first used a flow-based regionalization method to discover functional medical regions from the patient mobility network. We compare the results of data-driven regions to designated regions of the government in order to identify the areas of mismatch between planned regional service delivery and the observed utilization in the form of patient flows. Second, we used feature selection, and multivariate flow clustering to identify spatio-temporal characteristics and health care needs of patients on the move.ResultsMedical regions we derived by analyzing the patient mobility data showed strong overlap with the designated regions of the Ministry of Health. We also identified a number of regions that the regional service utilization did not match the planned service delivery. Overall, our spatio-temporal and multivariate analysis of regional and long-distance patient flows revealed strong relationship with socio-demographic and cultural structure of the society and migration patterns. Also, patient flows exhibited seasonal patterns, and yearly trends which correlate with implemented policies throughout the period. We found that policies resulted in different outcomes across the country. We also identified characteristics of long-distance flows which could help inform policy-making by assessing the needs of patients in terms of medical specialization, service level and type.ConclusionsOur approach helped identify (1) the mismatch between regional policy and practice in health care utilization (2) spatial, temporal, health service level characteristics and medical specialties that patients seek out by traveling longer distances. Our findings can help identify the imbalance between supply and demand, changes in mobility behaviors, and inform policy-making with insights.

An efficient regional ionospheric model using combined GPS/BeiDou observations

Abstract In this study, we develop a regional ionospheric model (RIM) based on the GPS-only observations and the combined GPS/BeiDou observations for single-frequency precise point positioning (SF-PPP) users in Europe. GPS/BeiDou observations from 16 reference stations are processed in the zero-differenced mode. A least-squares algorithm is developed to determine the total electron content (TEC) bi-linear function parameters for a 15-min time interval. The inverse distance weighted (IDW) interpolation technique is used to create the vertical TEC maps for a 1° × 1° grid. The developed models are evaluated for PPP applications using GNSS observations from another set of reference stations. The SF-PPP accuracy and convergence time obtained through the RIMs are assessed and compared with those obtained through the International GNSS Service Global Ionospheric Maps (IGS-GIM). The results show that the RIMs accelerate the convergence time and improve the positioning accuracy in the horizontal and height components in comparison with the IGS-GIM counterparts.