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Dr Paul Elsner

Lecturer in Geographical Information Science and Physical Geography
Course Director MSc Business Strategy and the Environment

PhD (University of Cambridge)
MPhil in GIS and Remote Sensing (University of Cambridge)
Master of Marine Management (Dalhousie University)
First State Exam in Geography, German Language and Literature Studies (University of Hamburg)

Research interests

My general research interests cluster around the application geoinformation technologies for renewable energy potential assessment and environmental monitoring. This includes the use of unmanned aerial vehicles (UAV).

 

  • DESERTEC Global Grid Corridor Feasibility Study
    • I am responsible investigator for the DESERTEC Global grid corridor feasibility study, funded by the DESERTEC Foundation. The general framework for this project is provided by the Desertec Global concept. Desertec Global proposes the utilization of solar resources in deserts worldwide for the large scale supply of energy of urbanised regions in the relative vicinity. The backbone of this concept is the construction of a network of CSP power stations in suitable desert locations and to transmit the electric energy via high-voltage-direct current (HVDC) grids to demand centers.
    • A central issue within the Desertec Global concept is the feasibility of constructing long-distance HVDC grids that shall link energy resource and energy demand areas. It is unclear how far the implementation of such power lines might be subject to potential technical and socio-economic limitations. Examples for this include terrain morphology, land cover and land use conflicts, and political barriers such as the territories of states that can be expected to be unwilling to co-operate. Only in the EUMENA region, the delineation of potential HVDC lines has been thoroughly investigated, leading to a robust information base for subsequent investment decisions. For other Desertec regions, such rigorous analysis is not available.
    • The grid corridor feasibility study at Birkbeck aims to address this shortcoming by carrying out a detailed analysis of potential HVDC corridors by the development and calibration of spatially explicit decision support models for three example regions:
    • A) China/Korea/Japan, and
    • B) Australia/South-East Asia
  • Estimating temporal and spatial variability of inherent optical properties of turbid coastal waters
    • Coastal remote sensing has successfully been employed to estimate suspended sediment concentration from space-bore and airborne platforms. The central optical process determining the reflectance of turbid coastal waters is scattering by inorganic suspended particles and the key problem for developing regionally and temporally stable models for the turbid Case 2 waters are variations in particle properties such as size, composition, and mineralogy.
    • To date, most applications implicitly assume that the backscattering coefficient remains spatially homogeneous throughout the entire image. Similar assumptions in the temporal domain apply to cases where a timeseries of e.g. tidal dynamics is analysed.
    • This project aims to test these assumption by monitoring variations of optical properties over short spatial and temporal units by using the combined deployment of the Wetlabs AC-S underwater spectral absorption and attenuation meter and the HyperOCR radiometer in an intertidal environment.
    • Deployment of AC-S/HyperOCR instrument suite at Blackwater Estuary.

PhD/MPhil supervision

  • I am interested in supervising in the areas of:
    • Energy Geography
    • Unmanned Aerial Systems (UAS) as novel research platform for environmental research.
    • Aquatic remote sensing and field spectroscopy
    • Spatial Decision Support Systems

Publications

    • Esch, T., Bay-Hasager, C., Elsner, P., Hirschmugl, M., Roth, A. (forthcoming 2016). Support of wind resource modeling using Earth Observation – A European perspective on the status and future options. In: Qihao Weng (Ed.) Remote Sensing for Sustainability. CRC Press. ISBN 9781498700719.
    • Elsner, P. Dornbusch, U., Thomas, I., and Amos, D. 2015. Monitoring Mixed Sand and Gravel Beaches Using Unmanned Aerial Systems. Proceedings of COASTAL SEDIMENTS 2015, May 11-15, 2015. San Diego, California.
    • Elsner, P. Spencer, T., Moeller, I. and Smith, G.M. 2012. Multitemporal Remote Sensing of Coastal Sediment Dynamics. In: Ni-Bin Chang (Ed.) Environmental Remote Sensing and Systems Analysis. Taylor & Francis Group/CRC Press. Boca Raton (Florida). Page 109-122. ISBN 9781439877456.
    • Elsner, P. 2011. Desertec Global Grid Feasibility Study. Intermediate Report for the DESERTEC Foundation. Grant contract no. 3105. Institute of Environment, Birkbeck College, University of London.
    • Lizarazo, I. and Elsner, P. 2011. Segmentation of Remotely Sensed Imagery: Moving from Sharp Objects to Fuzzy Regions, Image Segmentation, Pei-Gee Ho (Ed.), ISBN: 978-953-307-228-9, InTech, 16 pp.
    • Elsner, P. 2009. Multi-temporal Airborne Remote Sensing of Intertidal Sediment Dynamics. Proceedings of the SPIE Europe Remote Sensing, 31 August–3 September 2009, Berlin (Germany). Proc. SPIE, Vol. 7478, 74781R (2009); DOI:10.1117/12.830672; 8 pp.
    • Lizarazo, I. and Elsner, P. 2009. Fuzzy segmentation for geographic object-based image analysis. Proceedings of the SPIE Europe Remote Sensing, 31 August–3 September 2009, Berlin (Germany). Proc. SPIE, Vol. 7478, 74781M (2009); DOI:10.1117/12.830477; 12pp.
    • Lizarazo, I. and Elsner, P. 2009. Improving Urban Land Cover Classification using Fuzzy Image Segmentation. In: M.L. Gavrilova and C.J.K. Tan (Eds.): Trans. on Comput. Sci. VI, LNCS 5730, pp. 41–56; DOI: 10.1007/978-3-642-10649-1_3.
    • Lizarazo, I. and Elsner, P., 2009. Fuzzy segmentation for object-based image classification. International Journal of Remote Sensing 30 (6): 1643-1649.
    • Lizarazo, I. and Elsner, P. 2008. Fuzzy Regions for Handling Uncertainty in Remote Sensing Image Segmentation. Lecture Notes in Computer Science, Volume 5072/2008, Computational Science and Its Applications – ICCSA 2008: 724-739, DOI 10.1007/978-3-540-69839-5
    • Lizarazo, I. and Elsner, P. 2008. From Pixels to Grixels: A Unified Functional Model for Geographic-Object-Based Image Analysis. In: 2008, G.J .Hay, T. Blaschke and D. Marceau (Eds). GEOBIA 2008 – Pixels, Objects, Intelligence. GEOgraphic Object Based Image Analysis for the 21st Century. University of Calgary, Calgary Alberta, Canada, August 05-08. ISPRS Vol. No. XXXVIII-4/C1. Archives ISSN No.: 1682-1777. 373p.
    • Elsner, P. and Bonnici, M. 2007. Vertical accuracy of Shuttle Radar Topography Mission (SRTM) elevation and void-filled data in the Libyan Desert. International Journal of Ecology & Development 8(7): 66-80.
    • Elsner, P. 2005. GIS teaching via distance learning experiences and lessons learned. Planet (14): 28:30. GEES Subject Centre, The Higher Education Academy, UK.
    • Elsner, P.H., G.M. Smith, I. Möller and T. Spencer 2003. 'Airborne Imaging Spectroscopy - A Novel Approach for Monitoring Intertidal Sediment Dynamics', Proceedings of Coastal Sediments '03 May 18-23, St. Petersburg/Florida.
    • Recent Invited Presentations

        “The coming of age of China’s offshore wind energy: Opportunities for the maritime sector”. Invited Seminar at the IMCC Frank Tsao Maritime Library and Research & Development Center, Department of Logistics and Maritime Studies, Hong Kong Polytechnic University. August 2015.

Contact details

Email: p.elsner@bbk.ac.uk
Tel:
+ 44 (0)20 3073 8449