Sustainable SDI for EU noise mapping in NRW- best practice for INSPIRE

The Environmental Noise Directive of the European Union 2002/49/EG (END) obligates the EU member states to determine every 5 years the noise emission of major roads and railways, major airports, industrial activity sites and urban agglomerations and to document the results in noise maps. It poses high requirements, as a great number of statewide and ubiquitous geodata and thematic data in the third dimension is necessary (terrain, buildings, roads, railways). To provide these considerable amount of statewide 3D geodata, the state of North Rhine-Westphalia (NRW) follows a modern implementation concept, the sustainable use and enlargement of the Spatial Data Infrastructure GDI NRW. NRW provides for the first time statewide 3D geodata as features in CityGML via OGC Web Feature Services (3D building models in LOD1, ATKIS 3D road and railway data) and the Digital Terrain Model 10m grid via an OGC Web Coverage Service. CityGML is used as sole common exchange format between web services and noise calculation software to solve syntactic and semantic interoperability problems. A CityGML data base is realised, which contains approx. 10 million buildings. This article demonstrates the architecture of geodata provision, the 3D modelling in CityGML, the geodata refinement and interoperability tasks as well as the noise calculation results

Towards Sustainable Stewardship of Digital Collections of Scientific Data

The digital revolution has vastly increased the ability of the scientific community to collect and store a tremendous variety and quantity of data in digital form, representing a potentially irreplaceable legacy that can support scientific discovery and scholarship in both the present and the future. However, it is not yet clear what organizations or institutions can and should maintain and store such data, ensuring their long-term integrity and usability, nor how such longterm stewardship should be funded and supported. Many traditional information preservation and access institutions such as libraries and museums are struggling to develop the skills, resources, and infrastructure needed for large scale, long-term digital data stewardship. Government agencies often have strong technical capabilities, but are subject to political and budgetary pressures and competing priorities. Private organizations and companies can bring to bear innovations not only in technology but also in economic approaches that could provide financial sustainability. Developing long-term collaborative partnerships between different types of organizations may be one approach to developing sustainable models for long-term data stewardship. The development of objective criteria and open standards for trusted digital data repositories is another important step towards sustainable data stewardship. A critical challenge is the development of viable economic models for ensuring that the resources needed for long-term stewardship are put in place, while at the same time addressing the needs of the scientific community and society more generally for open access to scientific data and information resources. The development of a robust spatial data infrastructure can not only help reduce both the short- and long-term costs of data stewardship, but also provide a framework for the establishment and evolution of trustworthy data repositories that will be available for future generations of users to discover, access, and use the scientific heritage that is being created today

Proposal for a new LoD and multi-representation concept for CityGML

The Open Geospatial Consortium (OGC) CityGML standard offers a Level of Detail (LoD) concept that enables the representation of CityGML features from a very detailed to a less detailed description. Due to a rising application variety, the current LoD concept seems to be too inflexible. Here, we present a multi representation concept (MRC) that enables a user-defined definition of LoDs. Because CityGML is an international standard, official profiles of the MRC are proposed. However, encoding of the defined profiles reveals many problems including mapping the conceptual model to the normative encoding, missing technologies and so on. Therefore, we propose to use the MRC as a meta model for the further definition of an LoD concept for CityGML 3.0

Merging digital surface models sourced from multi-satellite imagery and their consequent application in automating 3D building modelling

Recently, especially within the last two decades, the demand for DSMs (Digital Surface Models) and 3D city models has increased dramatically. This has arisen due to the emergence of new applications beyond construction or analysis and consequently to a focus on accuracy and the cost. This thesis addresses two linked subjects: first improving the quality of the DSM by merging different source DSMs using a Bayesian approach; and second, extracting building footprints using approaches, including Bayesian approaches, and producing 3D models. Regarding the first topic, a probabilistic model has been generated based on the Bayesian approach in order to merge different source DSMs from different sensors. The Bayesian approach is specified to be ideal in the case when the data is limited and this can consequently be compensated by introducing the a priori. The implemented prior is based on the hypothesis that the building roof outlines are specified to be smooth, for that reason local entropy has been implemented in order to infer the a priori data. In addition to the a priori estimation, the quality of the DSMs is obtained by using field checkpoints from differential GNSS. The validation results have shown that the model was successfully able to improve the quality of the DSMs and improving some characteristics such as the roof surfaces, which consequently led to better representations. In addition to that, the developed model has been compared with the Maximum Likelihood model which showed similar quantitative statistical results and better qualitative results. Perhaps it is worth mentioning that, although the DSMs used in the merging have been produced using satellite images, the model can be applied on any type of DSM. The second topic is building footprint extraction based on using satellite imagery. An efficient flow-line for automatic building footprint extraction and 3D model construction, from both stereo panchromatic and multispectral satellite imagery was developed. This flow-line has been applied in an area of different building types, with both hipped and sloped roofs. The flow line consisted of multi stages. First, data preparation, digital orthoimagery and DSMs are created from WorldView-1. Pleiades imagery is used to create a vegetation mask. The orthoimagery then undergoes binary classification into ‘foreground’ (including buildings, shadows, open-water, roads and trees) and ‘background’ (including grass, bare soil, and clay). From the foreground class, shadows and open water are removed after creating a shadow mask by thresholding the same orthoimagery. Likewise roads have been removed, for the time being, after interactively creating a mask using the orthoimagery. NDVI processing of the Pleiades imagery has been used to create a mask for removing the trees. An ‘edge map’ is produced using Canny edge detection to define the exact building boundary outlines, from enhanced orthoimagery. A normalised digital surface model (nDSM) is produced from the original DSM using smoothing and subtracting techniques. Second, start Building Detection and Extraction. Buildings can be detected, in part, in the nDSM as isolated relatively elevated ‘blobs’. These nDSM ‘blobs’ are uniquely labelled to identify rudimentary buildings. Each ‘blob’ is paired with its corresponding ‘foreground’ area from the orthoimagery. Each ‘foreground’ area is used as an initial building boundary, which is then vectorised and simplified. Some unnecessary details in the ‘edge map’, particularly on the roofs of the buildings can be removed using mathematical morphology. Some building edges are not detected in the ‘edge map’ due to low contrast in some parts of the orthoimagery. The ‘edge map’ is subsequently further improved also using mathematical morphology, leading to the ‘modified edge map’. Finally, A Bayesian approach is used to find the most probable coordinates of the building footprints, based on the ‘modified edge map’. The proposal that is made for the footprint a priori data is based on the creating a PDF which assumes that the probable footprint angle at the corner is 90o and along the edge is 180o, with a less probable value given to the other angles such as 45o and 135o. The 3D model is constructed by extracting the elevation of the buildings from the DSM and combining it with the regularized building boundary. Validation, both quantitatively and qualitatively has shown that the developed process and associated algorithms have successfully been able to extract building footprints and create 3D models

Proceedings. 9th 3DGeoInfo Conference 2014, [11-13 November 2014, Dubai]

It is known that, scientific disciplines such as geology, geophysics, and reservoir exploration intrinsically use 3D geo-information in their models and simulations. However, 3D geo-information is also urgently needed in many traditional 2D planning areas such as civil engineering, city and infrastructure modeling, architecture, environmental planning etc. Altogether, 3DGeoInfo is an emerging technology that will greatly influence the market within the next few decades. The 9th International 3DGeoInfo Conference aims at bringing together international state-of-the-art researchers and practitioners facilitating the dialogue on emerging topics in the field of 3D geo-information. The conference in Dubai offers an interdisciplinary forum of sub- and above-surface 3D geo-information researchers and practitioners dealing with data acquisition, modeling, management, maintenance, visualization, and analysis of 3D geo-information