Finding alternative right of way using multi-criteria decision analysis based on least cost path: A case study of 20’’Anoh pipeline

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial TechnologiesA multi-criteria decision analysis was conducted using a geographic information system (GIS) coupled with analytical hierarchy process (AHP) methods to evaluate and prioritize the pipeline project areas for Assa North Ohaji South. Alternative Right-of-Ways (ROWs) with two optimal routes were determined and compared with the existing ROWs. During the analysis, several criteria were considered to determine the least cost alternative ROW, including slope, geology, waterbodies, roads, land use, and land cover. The optimum route for connecting the source and destination was then determined. The LANDSAT 8 imageries of the study area were processed and classified into various land use and land cover types, which were then modeled using ArcMap 10.8 GIS software for routing analysis. It was used in the study to demonstrate the efficiency of MCDA LCP and AHP integration in generating optimum routes for the ANOH project. By avoiding steep slopes, built-up areas, and waterbodies, the optimal route avoided the limitations of the existing ROW. This route has a 22% reduction in length and will decrease construction costs, which is an indication of its efficiency

Navigation Recommender:Real-Time iGNSS QoS Prediction for Navigation Services

Global Navigation Satellite Systems (GNSSs), especially Global Positioning System (GPS), have become commonplace in mobile devices and are the most preferred geo-positioning sensors for many location-based applications. Besides GPS, other GNSSs under development or deployment are GLONASS, Galileo, and Compass. These four GNSSs are planned to be integrated in the near future. It is anticipated that integrated GNSSs (iGNSSs) will improve the overall satellite-based geo-positioning performance. However, one major shortcoming of any GNSS and iGNSSs is Quality of Service (QoS) degradation due to signal blockage and attenuation by the surrounding environments, particularly in obstructed areas. GNSS QoS uncertainty is the root cause of positioning ambiguity, poor localization performance, application freeze, and incorrect guidance in navigation applications. In this research, a methodology, called iGNSS QoS prediction, that can provide GNSS QoS on desired and prospective routes is developed. Six iGNSS QoS parameters suitable for navigation are defined: visibility, availability, accuracy, continuity, reliability, and flexibility. The iGNSS QoS prediction methodology, which includes a set of algorithms, encompasses four modules: segment sampling, point-based iGNSS QoS prediction, tracking-based iGNSS QoS prediction, and iGNSS QoS segmentation. Given that iGNSS QoS prediction is data- and compute-intensive and navigation applications require real-time solutions, an efficient satellite selection algorithm is developed and distributed computing platforms, mainly grids and clouds, for achieving real-time performance are explored. The proposed methodology is unique in several respects: it specifically addresses the iGNSS positioning requirements of navigation systems/services; it provides a new means for route choices and routing in navigation systems/services; it is suitable for different modes of travel such as driving and walking; it takes high-resolution 3D data into account for GNSS positioning; and it is based on efficient algorithms and can utilize high-performance and scalable computing platforms such as grids and clouds to provide real-time solutions. A number of experiments were conducted to evaluate the developed methodology and the algorithms using real field test data (GPS coordinates). The experimental results show that the methodology can predict iGNSS QoS in various areas, especially in problematic areas

Comparison of Ground-to-Air Visibility Analysis Methods

When a disaster occurs, remotely sensed imagery is critical for emergency responders. Aircraft collect digital images of damaged areas to assist with damage assessment and response planning. Such airborne imagery can be transmitted directly from the plane to ground antennae and internet-connected dispersal, allowing for faster acquisition of data. However, air-to-ground transmission of images requires near-constant visibility between the aircraft transmitter and ground station antenna. This research uses GIS-based models to identify the ground station locations that can reliably receive data from aircraft, using a variety of visibility analysis methods and a comparison of their performance. A custom algorithm is demonstrated to perform significantly faster than commercially available software tools

Optimal Paths for Electricity Interconnections between Central Asia and Europe

The European Union is increasingly considering energy cooperation with Central Asia as this is a relatively nearby and stable region with tremendous energy resources. Locally produced electricity – i.e. predominantly from gas and hydro and potentially from solar and wind energy – offer opportunities for beneficial electricity trade, both among the Central Asian countries and with the European Union. As such, Central Asia may contribute to the European Union’s security of electricity supply and the achievement of its renewable energy targets. Underpinning policies and strategies for improved energy connectivity with Central Asia and the use of renewable energy sources in this region have been developed. However, efficient electricity interconnections are still lacking, hindering the full potential of Central Asia’s energy resources. Against this background, this report presents a methodology for the computation of optimal electricity transmission routes, crossing Central Asia, the Caspian Sea and the Transcaucasia towards the European Union. This methodology, which is based on the concept of friction maps, makes use of a set of 13 input variables and is implemented in geographic information system software. For each pixel of the friction map, covering the addressed countries, a crossing cost is calculated from semi-quantitative friction scores, which are locally attributed to the variables. Starting from the final cost surface, which represents a composite weighted map of the constituent variables, the software model successfully evaluates the least-cost paths for electricity transmission throughout the considered region. It is found that the evaluated route is most sensitive to the renewable energy potential across the considered region and not to the already existing electricity assets.JRC.C.3-Energy Security, Distribution and Market

Multi-objective optimisation based planning of power-line grid expansions

German nuclear power phase out in 2022 leads to significant reconstruction of the energy transmission system. Thus, efficient identification of practical transmission routes with minimum impact on ecological and economical interests is of growing importance. Due to the sensitivity of Germany’s public to grid expansion (especially in case of overhead lines), the participation and planning process needs to provide a high degree of openness and accountability. Therefore, a new methodological approach for the computer-assisted finding of optimal power-line routes considering planning, ecological and economic decision criteria is presented. The approach is implemented in a tool-chain for the determination of transmission line routes (and sets of transmission line route alternatives) based on multi-criteria optimisation. Additionally, a decision support system, based on common Geographic Information Systems (GIS), consisting of interactive visualisation and exploration of the solution space is proposed

Enhanced Multi Criteria Decision Analysis for Planning Power Transmission Lines

The energy transition towards alternative energy sources requires new power transmission lines to connect these additional energy production plants with electricity distribution centers. For this reason, Multi Criteria Decision Analysis (MCDA) offers a useful approach to determine the optimal path of future transmission lines with minimum impact on the environment, on the landscape, and on affected citizens. As objections could deteriorate such a project and in turn increase costs, transparent communication regarding the planning procedure is required that fosters citizens\u27 acceptance. In this context, GIS-based information on the criteria taken into account and for modeling possible power transmission lines is essential. However, planners often forget that the underlying multi criteria decision model and the used data might lead to biased results. Therefore, this study empirically investigates the effect of various MCDA parameters by applying a sensitivity analysis on a multi criteria decision model. The output of this analysis is evaluated combining a Cluster Analysis, a Principal Component Analysis, and a Multivariate Analysis of Variance. Our results indicate that the variability of different corridor alternatives can be increased by using different MCDA parameter combinations. In particular, we found that applying continuous boundary models on areas leads to more distinct corridor alternatives than using a sharp-edged model, and better reflects actual planning practice for protecting areas against transmission lines. Comparing the results of two study areas, we conclude that our decision model behaved similarly across both sites and, hence, that the proposed procedure for enhancing the decision model is applicable to other study areas with comparable topographies. These results can help decision-makers and transmission line planners in simplifying and improving their decision models in order to increase credibility, legitimacy, and thus practical applicability

Towards a National 3D Mapping Product for Great Britain

Knowing where something happens and where people are located can be critically important to understand issues ranging from climate change to road accidents, crime, schooling, transport and much more. To analyse these spatial problems, two-dimensional representations of the world, such as paper or digital maps, have traditionally been used. Geographic information systems (GIS) are the tools that enable capture, modelling, storage, retrieval, sharing, manipulation, analysis, and presentation of geographically referenced data. Three-dimensional geographic information (3D GI) is data that can represent real-world features as objects in 3D space. 3D GI offers additional functionality not possible in 2D, including analysing and querying volume, visibility, surface and sub-surface, and shadowing. This thesis contributes to the understanding of user requirements and other data related considerations in the production of 3D geographic information at a national level. The study promotes Ordnance Survey’s efforts in developing a 3D geographic product through: (1) identifying potential applications; (2) analysing existing 3D city modelling approaches; (3) eliciting and formalising user requirements; (4) developing metrics to describe the usefulness of 3D data and; (5) evaluating the commerciality of 3D GI. A review of current applications of 3D showed that visualisation dominated as the main use, allowing for better communication, and supporting decision-making processes. Reflecting this, an examination of existing 3D city models showed that, despite the varying modelling approaches, there was a general focus towards accurate and realistic geometric representation of the urban environment. Web-based questionnaires and semi-structured interviews revealed that while some applications (e.g. subsurface, photovoltaics, air and noise quality) lead the field with a high adoption of 3D, others were laggards due to organisational inertia (e.g. insurance, facilities management). Individuals expressed positive views on the use of 3D, but still struggled to justify the value and business case. Simple building geometry coupled with non-building thematic classes was perceived to be most useful by users. Several metrics were developed to quantify and compare the characteristics of thirty-three 3D datasets. Results showed that geometry-based metrics such as minimum feature length or Euler characteristic can be used to provide additional information as part of fitness-for-purpose evaluations. The metrics can also contribute to quality control during data production. An investigation into the commercial opportunities explored the economic value of 3D, the market size of 3D data in Great Britain, as well as proposed a number of opportunities within the wider business context of Ordnance Survey

3D oceanographic data compression using 3D-ODETLAP

This paper describes a 3D environmental data compression technique for oceanographic datasets. With proper point selection, our method approximates uncompressed marine data using an over-determined system of linear equations based on, but essentially different from, the Laplacian partial differential equation. Then this approximation is refined via an error metric. These two steps work alternatively until a predefined satisfying approximation is found. Using several different datasets and metrics, we demonstrate that our method has an excellent compression ratio. To further evaluate our method, we compare it with 3D-SPIHT. 3D-ODETLAP averages 20% better compression than 3D-SPIHT on our eight test datasets, from World Ocean Atlas 2005. Our method provides up to approximately six times better compression on datasets with relatively small variance. Meanwhile, with the same approximate mean error, we demonstrate a significantly smaller maximum error compared to 3D-SPIHT and provide a feature to keep the maximum error under a user-defined limit