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A 3D model communicates more effectively than a 2D model, hence the applications of 3D city models are rapidly gaining significance in urban studies. However, presently, there is a dearth of free of cost, high-resolution 3D city models available for use. This paper offers potential solutions to this problem by providing a globally replicable methodology to generate low-cost 3D city models from open source 2D building data in conjunction with open satellite-based elevation datasets. Two geographically and morphologically different case studies were used to develop and test this methodology: the Chinese city of Shanghai and the city of Nottingham in the UK. The method is based principally on OpenStreetMap (OSM) and Advanced Land Observing Satellite World 3D digital surface model (AW3D DSM) data and use GMTED 2010 DTM data for undulating terrain. Further enhancement of the resultant 3D model, though not compulsory, uses higher resolution elevation models that are not always open source, but if available can be used (i.e., airborne LiDAR generated DTM). Further we test and develop methods to improve the accuracy of the generated 3D models, employing a small subset of high resolution data that are not open source but can be purchased with a minimal budgets. Given these scenarios of data availability are globally applicable and time-efficient for 3D building generation (where 2D building footprints are available), our proposed methodology has the potential to accelerate the production of 3D city models, and thus to facilitate their dependent applications (e.g., disaster management) wherever commercial 3D city models are unavailable.
Renoy Girindran; Doreen S Boyd; Julian Rosser; Dhanya Vijayan; Gavin Long; Darren Robinson. On the Reliable Generation of 3D City Models from Open Data. Urban Science 2020, 4, 47 .
AMA StyleRenoy Girindran, Doreen S Boyd, Julian Rosser, Dhanya Vijayan, Gavin Long, Darren Robinson. On the Reliable Generation of 3D City Models from Open Data. Urban Science. 2020; 4 (4):47.
Chicago/Turabian StyleRenoy Girindran; Doreen S Boyd; Julian Rosser; Dhanya Vijayan; Gavin Long; Darren Robinson. 2020. "On the Reliable Generation of 3D City Models from Open Data." Urban Science 4, no. 4: 47.
Understanding the energy demand of a city’s housing stock is an important focus for local and national administrations to identify strategies for reducing carbon emissions. Building energy simulation offers a promising approach to understand energy use and test plans to improve the efficiency of residential properties. As part of this, models of the urban stock must be created that accurately reflect its size, shape and composition. However, substantial effort is required in order to generate detailed urban scenes with the appropriate level of attribution suitable for spatially explicit simulation of large areas. Furthermore, the computational complexity of microsimulation of building energy necessitates consideration of approaches that reduce this processing overhead. We present a workflow to automatically generate 2.5D urban scenes for residential building energy simulation from UK mapping datasets. We describe modelling the geometry, the assignment of energy characteristics based upon a statistical model and adopt the CityGML EnergyADE schema which forms an important new and open standard for defining energy model information at the city-scale. We then demonstrate use of the resulting urban scenes for estimating heating demand using a spatially explicit building energy microsimulation tool, called CitySim+, and evaluate the effects of an off-the-shelf geometric simplification routine to reduce simulation computational complexity.
Julian F. Rosser; Gavin Long; Sameh Zakhary; Doreen S. Boyd; Yong Mao; Darren Robinson. Modelling Urban Housing Stocks for Building Energy Simulation using CityGML EnergyADE. ISPRS International Journal of Geo-Information 2019, 8, 163 .
AMA StyleJulian F. Rosser, Gavin Long, Sameh Zakhary, Doreen S. Boyd, Yong Mao, Darren Robinson. Modelling Urban Housing Stocks for Building Energy Simulation using CityGML EnergyADE. ISPRS International Journal of Geo-Information. 2019; 8 (4):163.
Chicago/Turabian StyleJulian F. Rosser; Gavin Long; Sameh Zakhary; Doreen S. Boyd; Yong Mao; Darren Robinson. 2019. "Modelling Urban Housing Stocks for Building Energy Simulation using CityGML EnergyADE." ISPRS International Journal of Geo-Information 8, no. 4: 163.
The age of a building influences its form and fabric composition and this in turn is critical to inferring its energy performance. However, often this data is unknown. In this paper, we present a methodology to automatically identify the construction period of houses, for the purpose of urban energy modelling and simulation. We describe two major stages to achieving this – a per-building classification model and post-classification analysis to improve the accuracy of the class inferences. In the first stage, we extract measures of the morphology and neighbourhood characteristics from readily available topographic mapping, a high-resolution Digital Surface Model and statistical boundary data. These measures are then used as features within a random forest classifier to infer an age category for each building. We evaluate various predictive model combinations based on scenarios of available data, evaluating these using 5-fold cross-validation to train and tune the classifier hyper-parameters based on a sample of city properties. A separate sample estimated the best performing cross-validated model as achieving 77% accuracy. In the second stage, we improve the inferred per-building age classification (for a spatially contiguous neighbourhood test sample) through aggregating prediction probabilities using different methods of spatial reasoning. We report on three methods for achieving this based on adjacency relations, near neighbour graph analysis and graph-cuts label optimisation. We show that post-processing can improve the accuracy by up to 8 percentage points.
J.F. Rosser; Doreen Boyd; G. Long; Sameh Zakhary; Y. Mao; D. Robinson. Predicting residential building age from map data. Computers, Environment and Urban Systems 2018, 73, 56 -67.
AMA StyleJ.F. Rosser, Doreen Boyd, G. Long, Sameh Zakhary, Y. Mao, D. Robinson. Predicting residential building age from map data. Computers, Environment and Urban Systems. 2018; 73 ():56-67.
Chicago/Turabian StyleJ.F. Rosser; Doreen Boyd; G. Long; Sameh Zakhary; Y. Mao; D. Robinson. 2018. "Predicting residential building age from map data." Computers, Environment and Urban Systems 73, no. : 56-67.
The design and running of complex geoprocessing workflows is an increasingly common geospatial modelling and analysis task. The Business Process Model and Notation (BPMN) standard, which provides a graphical representation of a workflow, allows stakeholders to discuss the scientific conceptual approach behind this modelling while also defining a machine‐readable encoding in XML. Previous research has enabled the orchestration of Open Geospatial Consortium Web Processing Services (WPS) with a BPMN workflow engine. However, the need for direct access to predefined data inputs and outputs results in a lack of flexibility during composition of the workflow and of efficiency during execution. This article develops metadata profiling approaches, described as two possible configurations, which enable workflow management at the meta‐level through a coupling with a metadata catalogue. Specifically, a WPS profile and a BPMN profile are developed and tested using open‐source components to achieve this coupling. A case study in the context of an event mapping task applied within a big data framework and based on analysis of the Global Database of Event Language and Tone database illustrates the two different architectures.
Julian F. Rosser; Mike Jackson; Didier G. Leibovici. Full Meta Object profiling for flexible geoprocessing workflows. Transactions in GIS 2018, 22, 1221 -1237.
AMA StyleJulian F. Rosser, Mike Jackson, Didier G. Leibovici. Full Meta Object profiling for flexible geoprocessing workflows. Transactions in GIS. 2018; 22 (5):1221-1237.
Chicago/Turabian StyleJulian F. Rosser; Mike Jackson; Didier G. Leibovici. 2018. "Full Meta Object profiling for flexible geoprocessing workflows." Transactions in GIS 22, no. 5: 1221-1237.
Estimating residential building energy use across large spatial extents is vital for identifying and testing effective strategies to reduce carbon emissions and improve urban sustainability. This task is underpinned by the availability of accurate models of building stock from which appropriate parameters may be extracted. For example, the form of a building, such as whether it is detached, semi-detached, terraced etc. and its shape may be used as part of a typology for defining its likely energy use. When these details are combined with information on building construction materials or glazing ratio, it can be used to infer the heat transfer characteristics of different properties. However, these data are not readily available for energy modelling or urban simulation. Although this is not a problem when the geographic scope corresponds to a small area and can be hand-collected, such manual approaches cannot be easily applied at the city or national scale. In this article, we demonstrate an approach that can automatically extract this information at the city scale using off-the-shelf products supplied by a National Mapping Agency. We present two novel techniques to create this knowledge directly from input geometry. The first technique is used to identify built form based upon the physical relationships between buildings. The second technique is used to determine a more refined internal/external wall measurement and ratio. The second technique has greater metric accuracy and can also be used to address problems identified in extracting the built form. A case study is presented for the City of Nottingham in the United Kingdom using two data products provided by the Ordnance Survey of Great Britain: MasterMap and AddressBase. This is followed by a discussion of a new categorisation approach for housing form for urban energy assessment.
Anthony Beck; Gavin Long; Doreen S Boyd; Julian F Rosser; Jeremy Morley; Richard Duffield; Mike Sanderson; Darren Robinson. Automated classification metrics for energy modelling of residential buildings in the UK with open algorithms. Environment and Planning B: Urban Analytics and City Science 2018, 47, 45 -64.
AMA StyleAnthony Beck, Gavin Long, Doreen S Boyd, Julian F Rosser, Jeremy Morley, Richard Duffield, Mike Sanderson, Darren Robinson. Automated classification metrics for energy modelling of residential buildings in the UK with open algorithms. Environment and Planning B: Urban Analytics and City Science. 2018; 47 (1):45-64.
Chicago/Turabian StyleAnthony Beck; Gavin Long; Doreen S Boyd; Julian F Rosser; Jeremy Morley; Richard Duffield; Mike Sanderson; Darren Robinson. 2018. "Automated classification metrics for energy modelling of residential buildings in the UK with open algorithms." Environment and Planning B: Urban Analytics and City Science 47, no. 1: 45-64.
Environmental policy involving citizen science (CS) is of growing interest. In support of this open data stream of information, validation or quality assessment of the CS geo-located data to their appropriate usage for evidence-based policy making needs a flexible and easily adaptable data curation process ensuring transparency. Addressing these needs, this paper describes an approach for automatic quality assurance as proposed by the Citizen OBservatory WEB (COBWEB) FP7 project. This approach is based upon a workflow composition that combines different quality controls, each belonging to seven categories or “pillars”. Each pillar focuses on a specific dimension in the types of reasoning algorithms for CS data qualification. These pillars attribute values to a range of quality elements belonging to three complementary quality models. Additional data from various sources, such as Earth Observation (EO) data, are often included as part of the inputs of quality controls within the pillars. However, qualified CS data can also contribute to the validation of EO data. Therefore, the question of validation can be considered as “two sides of the same coin”. Based on an invasive species CS study, concerning Fallopia japonica (Japanese knotweed), the paper discusses the flexibility and usefulness of qualifying CS data, either when using an EO data product for the validation within the quality assurance process, or validating an EO data product that describes the risk of occurrence of the plant. Both validation paths are found to be improved by quality assurance of the CS data. Addressing the reliability of CS open data, issues and limitations of the role of quality assurance for validation, due to the quality of secondary data used within the automatic workflow, are described, e.g., error propagation, paving the route to improvements in the approach.
Didier G. Leibovici; Jamie Williams; Julian F. Rosser; Crona Hodges; Colin Chapman; Chris Higgins; Mike J. Jackson. Earth Observation for Citizen Science Validation, or Citizen Science for Earth Observation Validation? The Role of Quality Assurance of Volunteered Observations. Data 2017, 2, 35 .
AMA StyleDidier G. Leibovici, Jamie Williams, Julian F. Rosser, Crona Hodges, Colin Chapman, Chris Higgins, Mike J. Jackson. Earth Observation for Citizen Science Validation, or Citizen Science for Earth Observation Validation? The Role of Quality Assurance of Volunteered Observations. Data. 2017; 2 (4):35.
Chicago/Turabian StyleDidier G. Leibovici; Jamie Williams; Julian F. Rosser; Crona Hodges; Colin Chapman; Chris Higgins; Mike J. Jackson. 2017. "Earth Observation for Citizen Science Validation, or Citizen Science for Earth Observation Validation? The Role of Quality Assurance of Volunteered Observations." Data 2, no. 4: 35.
Environmental policy involving citizen science (CS) is of growing interest. In support of this open data stream, validation or quality assessment of the CS data and their appropriate usage for evidence-based policy making, needs a flexible and easily adaptable data curation process ensuring transparency. Addressing these needs, this paper describes an approach for automatic quality assurance as proposed by the Citizen OBservatory WEB (COBWEB) FP7 project. This approach is based upon a workflow composition that combines different quality controls, each belonging to seven categories or ‘pillars’. Each pillar focuses on a specific dimension in the types of reasoning algorithms for CS data qualification. These pillars attribute values to a range of quality elements belonging to three complementary quality models. Additional data from various sources, such as Earth Observation (EO) data, are often included as part of the inputs of quality controls within the pillars. However, qualified CS data can also contribute to the validation of EO data. Therefore, the question of validation can be considered as ‘two sides of the same coin’. Based on an invasive species CS study, concerning Fallopia japonica (Japanese knotweed), the paper discusses the flexibility and usefulness of qualifying CS data, either when using an EO data for the validation within the quality assurance process, or validating an EO data product that describes the risk of occurrence of the plant. Both validation paths are found to be improved by quality assurance of the CS data. Addressing the reliability of CS open data, issues and limitations of the role of quality assurance for validation, due to the quality of secondary data used within the automatic workflow, are described, e.g. error propagation, paving the route to improvements in the approach.
Didier Leibovici; Jamie Williams; Julian Rosser; Crona Hodges; Colin Chapman; Chris Higgins; Mike Jackson. Earth Observation for Citizen Science Validation, or, Citizen Science for Earth Observation Validation? The Role of Quality Assurance of Volunteered Observations. 2017, 1 .
AMA StyleDidier Leibovici, Jamie Williams, Julian Rosser, Crona Hodges, Colin Chapman, Chris Higgins, Mike Jackson. Earth Observation for Citizen Science Validation, or, Citizen Science for Earth Observation Validation? The Role of Quality Assurance of Volunteered Observations. . 2017; ():1.
Chicago/Turabian StyleDidier Leibovici; Jamie Williams; Julian Rosser; Crona Hodges; Colin Chapman; Chris Higgins; Mike Jackson. 2017. "Earth Observation for Citizen Science Validation, or, Citizen Science for Earth Observation Validation? The Role of Quality Assurance of Volunteered Observations." , no. : 1.
Volunteer geographical information (VGI), either in the context of citizen science or the mining of social media, has proven to be useful in various domains including natural hazards, health status, disease epidemics, and biological monitoring. Nonetheless, the variable or unknown data quality due to crowdsourcing settings are still an obstacle for fully integrating these data sources in environmental studies and potentially in policy making. The data curation process, in which a quality assurance (QA) is needed, is often driven by the direct usability of the data collected within a data conflation process or data fusion (DCDF), combining the crowdsourced data into one view, using potentially other data sources as well. Looking at current practices in VGI data quality and using two examples, namely land cover validation and inundation extent estimation, this paper discusses the close links between QA and DCDF. It aims to help in deciding whether a disentanglement can be possible, whether beneficial or not, in understanding the data curation process with respect to its methodology for future usage of crowdsourced data. Analysing situations throughout the data curation process where and when entanglement between QA and DCDF occur, the paper explores the various facets of VGI data capture, as well as data quality assessment and purposes. Far from rejecting the usability ISO quality criterion, the paper advocates for a decoupling of the QA process and the DCDF step as much as possible while still integrating them within an approach analogous to a Bayesian paradigm.
Didier G. Leibovici; Julian F. Rosser; Crona Hodges; Barry Evans; Michael J. Jackson; Chris I. Higgins. On Data Quality Assurance and Conflation Entanglement in Crowdsourcing for Environmental Studies. ISPRS International Journal of Geo-Information 2017, 6, 78 .
AMA StyleDidier G. Leibovici, Julian F. Rosser, Crona Hodges, Barry Evans, Michael J. Jackson, Chris I. Higgins. On Data Quality Assurance and Conflation Entanglement in Crowdsourcing for Environmental Studies. ISPRS International Journal of Geo-Information. 2017; 6 (3):78.
Chicago/Turabian StyleDidier G. Leibovici; Julian F. Rosser; Crona Hodges; Barry Evans; Michael J. Jackson; Chris I. Higgins. 2017. "On Data Quality Assurance and Conflation Entanglement in Crowdsourcing for Environmental Studies." ISPRS International Journal of Geo-Information 6, no. 3: 78.
Flood events cause substantial damage to urban and rural areas. Monitoring water extent during large-scale flooding is crucial in order to identify the area affected and to evaluate damage. During such events, spatial assessments of floodwater may be derived from satellite or airborne sensing platforms. Meanwhile, an increasing availability of smartphones is leading to documentation of flood events directly by individuals, with information shared in real-time using social media. Topographic data, which can be used to determine where floodwater can accumulate, are now often available from national mapping or governmental repositories. In this work, we present and evaluate a method for rapidly estimating flood inundation extent based on a model that fuses remote sensing, social media and topographic data sources. Using geotagged photographs sourced from social media, optical remote sensing and high-resolution terrain mapping, we develop a Bayesian statistical model to estimate the probability of flood inundation through weights-of-evidence analysis. Our experiments were conducted using data collected during the 2014 UK flood event and focus on the Oxford city and surrounding areas. Using the proposed technique, predictions of inundation were evaluated against ground-truth flood extent. The results report on the quantitative accuracy of the multisource mapping process, which obtained area under receiver operating curve values of 0.95 and 0.93 for model fitting and testing, respectively.
Julian F. Rosser; Didier Leibovici; M. J. Jackson. Rapid flood inundation mapping using social media, remote sensing and topographic data. Natural Hazards 2017, 87, 103 -120.
AMA StyleJulian F. Rosser, Didier Leibovici, M. J. Jackson. Rapid flood inundation mapping using social media, remote sensing and topographic data. Natural Hazards. 2017; 87 (1):103-120.
Chicago/Turabian StyleJulian F. Rosser; Didier Leibovici; M. J. Jackson. 2017. "Rapid flood inundation mapping using social media, remote sensing and topographic data." Natural Hazards 87, no. 1: 103-120.
Creating as-built plans of building interiors is a challenging task. In this paper we present a semi-automatic modelling system for creating residential building interior plans and their integration with existing map data to produce building models. Taking a set of imprecise measurements made with an interactive mobile phone room mapping application, the system performs spatial adjustments in accordance with soft and hard constraints imposed on the building plan geometry. The approach uses an optimisation model that exploits a high accuracy building outline, such as can be found in topographic map data, and the building topology to improve the quality of interior measurements and generate a standardised output. We test our system on building plans of five residential homes. Our evaluation shows that the approach enables construction of accurate interior plans from imprecise measurements. The experiments report an average accuracy of 0.24 m, close to the 0.20 m recommended by the CityGML LoD4 specification.
Julian Rosser; Jeremy Morley; Gavin Smith. Modelling of Building Interiors with Mobile Phone Sensor Data. ISPRS International Journal of Geo-Information 2015, 4, 989 -1012.
AMA StyleJulian Rosser, Jeremy Morley, Gavin Smith. Modelling of Building Interiors with Mobile Phone Sensor Data. ISPRS International Journal of Geo-Information. 2015; 4 (2):989-1012.
Chicago/Turabian StyleJulian Rosser; Jeremy Morley; Gavin Smith. 2015. "Modelling of Building Interiors with Mobile Phone Sensor Data." ISPRS International Journal of Geo-Information 4, no. 2: 989-1012.