Calibration and accuracy assessment of Leica ScanStation C10 terrestrial laser scanner

Requirement of high accuracy data in surveying applications has made calibration procedure a standard routine for all surveying instruments. This is due to the assumption that all observed data are impaired with errors. Thus, this routine is also applicable to terrestrial laser scanner (TLS) to make it available for surveying purposes. There are two calibration approaches: (1) component, and (2) system calibration. With the intention to specifically identify the errors and accuracy of the Leica ScanStation C10 scanner, this study investigates component calibration. Three components of calibration were performed to identify the constant, scale error, accuracy of angular measurement and the effect of angular resolution for distance measurement. The first calibration has been processed using closed least square solutions and has yielded the values of constant (1.2 mm) and scale error (1.000008879). Using variance ratio test (F-Test), angles observation (horizontal and vertical) for Leica C10 scanner and Leica TM5100A theodolite have shown significance difference. This is because the accuracy of both sensors are not similar and these differences are 0.01 and 0.0075º for horizontal and vertical measurements, respectively. Investigation on the resolution setting for Leica C10 scanner has highlighted the drawback of the tilt-and-turn target. Using the highest resolution, Leica Cyclone software only able to recognize the tilt-and-turn target up to 10 m distance compare to 200 m for the black and white target

A study about terrestrial laser scanning for reconstruction of precast concrete to support QCLASSIC assessment

Nowadays, terrestrial laser scanning shows the potential to improve construction productivity by measuring the objects changes using real-time applications. This paper presents the process of implementation of an efficient framework for precast concrete using terrestrial laser scanning that enables contractors to acquire accurate data and support Quality Assessment System in Construction (QLASSIC). Leica Scanstation C10, black/white target, Autodesk Revit and Cyclone software were used in this study. The results were compared with the dimensional of based model precast concrete given by the company as a reference with the AutoDesk Revit model from the terrestrial laser scanning data and conventional method (measuring tape). To support QLASSIC, the tolerance dimensions of cast in-situ & precast elements is +10 mm /-5 mm. The results showed that the root mean square error for a Revit model is 2.972 mm while using measuring tape is 13.687 mm. The accuracy showed that terrestrial laser scanning has an advantage in construction jobs to support QLASSIC

Review of the environmental and organisational implications of cloud computing: final report.

Cloud computing – where elastic computing resources are delivered over the Internet by external service providers – is generating significant interest within HE and FE. In the cloud computing business model, organisations or individuals contract with a cloud computing service provider on a pay-per-use basis to access data centres, application software or web services from any location. This provides an elasticity of provision which the customer can scale up or down to meet demand. This form of utility computing potentially opens up a new paradigm in the provision of IT to support administrative and educational functions within HE and FE. Further, the economies of scale and increasingly energy efficient data centre technologies which underpin cloud services means that cloud solutions may also have a positive impact on carbon footprints. In response to the growing interest in cloud computing within UK HE and FE, JISC commissioned the University of Strathclyde to undertake a Review of the Environmental and Organisational Implications of Cloud Computing in Higher and Further Education [19]

Data-driven Economies in Central and Eastern Europe. Challenges and Perspectives

The recently published Communication on “Building a European Data Economy” (COM(2017)9) clearly highlights the increasing importance of data as a driver for growth, innovation and job creation. It is estimated that by year 2020, the value the EU data economy will increase to EUR 643 billion, representing over 3% of the EU GDP. At the same time there is no comparable and quantifiable evidence on the current state and the future perspectives of the data driven economy in the European Union neighbouring countries. It can however safely be assumed that the role of data will be following a similar pattern, and is therefore expected to be contribution to an increasing relative share of GDP. Furthermore, some European neighbouring countries, most notably those in Central and Eastern Europe, are a recognised destination for IT businesses that grow two to three times faster than in their economy of origin. Within this context, a workshop was co-organized by the World Bank, the UN Economic Commission for Europe (UNECE), the Food and Agriculture Organization of the United Nations (FAO) and the Joint Research Centre of the European Commission (JRC). The workshop took place on 05 September as part of the annual INSPIRE Conference in 2017 (co-organised in Strasbourg and Kehl by France and Germany). The workshop explored the challenges and possibilities related with Data driven economy in Central and Eastern Europe. All the presentation of attendees are available online. The rapidly emerging spatial data infrastructures (SDI) were used as a use case to have a better insight into the data economy as they address a broad spectrum of topics that relate to the legal, technological and organisational challenges towards the use and reuse of data. Particular emphasis was put on good practices that if re-used and extended, can further foster innovation and intensify growth. This JRC technical report summarises the outcomes of the WB/UNECE/FAO/JRC workshop. It includes (i) overview of relevant processes on the global and European agenda, (ii) good practices from countries in the target region on the value-added from data that provide indications future policy directions and emerging opportunities.JRC.B.6-Digital Econom

Low-cost UAV surveys of hurricane damage in Dominica: automated processing with co-registration of pre-hurricane imagery for change analysis

In 2017, hurricane Maria caused unprecedented damage and fatalities on the Caribbean island of Dominica. In order to ‘build back better’ and to learn from the processes causing the damage, it is important to quickly document, evaluate and map changes, both in Dominica and in other high-risk countries. This paper presents an innovative and relatively low-cost and rapid workflow for accurately quantifying geomorphological changes in the aftermath of a natural disaster. We used unmanned aerial vehicle (UAV) surveys to collect aerial imagery from 44 hurricane-affected key sites on Dominica. We processed the imagery using structure from motion (SfM) as well as a purpose-built Python script for automated processing, enabling rapid data turnaround. We also compared the data to an earlier UAV survey undertaken shortly before hurricane Maria and established ways to co-register the imagery, in order to provide accurate change detection data sets. Consequently, our approach has had to differ considerably from the previous studies that have assessed the accuracy of UAV-derived data in relatively undisturbed settings. This study therefore provides an original contribution to UAV-based research, outlining a robust aerial methodology that is potentially of great value to post-disaster damage surveys and geomorphological change analysis. Our findings can be used (1) to utilise UAV in post-disaster change assessments; (2) to establish ground control points that enable before-and-after change analysis; and (3) to provide baseline data reference points in areas that might undergo future change. We recommend that countries which are at high risk from natural disasters develop capacity for low-cost UAV surveys, building teams that can create pre-disaster baseline surveys, respond within a few hours of a local disaster event and provide aerial photography of use for the damage assessments carried out by local and incoming disaster response teams

Digital real estate: a review of the technologies and tools transforming the industry and society

© 2023 The Author(s); Shantou University. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/Real estate plays a crucial role in driving national economies. However, the process of transferring properties and engaging with various stakeholders can be hindered by a lack of adequate information, complex procedures, and excessive paperwork. The advent of digital real estate has revolutionized the industry and how stakeholders interact. The present study aims to conduct a bibliometric and systematic review of digital real estate, utilizing historical, institutional, country, and keyword analyses for the bibliometric review and Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines for the systematic review. Through thematic analysis, the study identified four key themes for transforming digital real estate: information communication technologies, data collection technologies, data networking tools, and digital decision-making systems. Additionally, the study proposes a digital real estate transformation framework that can assist stakeholders, urban planners, and decision-makers in embracing digital tools and technologies. The study concludes that digital real estate has the potential to revolutionize future urban planning and real estate development through the use of decision support systems and advanced technologies.Peer reviewe

New Trends in Development of Services in the Modern Economy

The services sector strategic development unites a multitude of economic and managerial aspects and is one of the most important problems of economic management. Many researches devoted to this industry study are available. Most of them are performed in the traditional aspect of the voluminous calendar approach to strategic management, characteristic of the national scientific school. Such an approach seems archaic, forming false strategic benchmarks. The services sector is of special scientific interest in this context due to the fact that the social production structure to the services development model attraction in many countries suggests transition to postindustrial economy type where the services sector is a system-supporting sector of the economy. Actively influencing the economy, the services sector in the developed countries dominates in the GDP formation, primary capital accumulation, labor, households final consumption and, finally, citizens comfort of living. However, a clear understanding of the services sector as a hyper-sector permeating all spheres of human activity has not yet been fully developed, although interest in this issue continues to grow among many authors. Target of strategic management of the industry development setting requires substantive content and the services sector target value assessment