In a nutshell : Data Scientist with the emphasis on Spatial Science. PhD in Computer Science, MSc in GIScience and Remote Sensing, and BA(hons) in Geography / Socio-Economics / History.¨ Formerly - Researcher, Geographical Information and Remote Sensing. The James Hutton Institute, Aberdeen, UK.
Methods / Skills : Algorithm development, Computational Geometry, Cartography, Database design, Data Visualisation, Dynamic Modelling, Economic & Social History, Geography, Environmental Science, Geo-spatial Modelling, GIS, Landscape change modelling, Longitudinal Statistics, Qualitative Analysis, Remote Sensing, Spatial Analysis, Survey design, Software development, Spatial sampling, Spatial statistics, Scientific writing, Teaching (HE).
MISTRA Urbans - The Ecosystem Service City (2017-2018, The Swedish Foundation for Strategic Environmental Research)
’En kunskapsöversikt om scenario modellering’ / ‘A Review of the State of the Art in Environmental Scenario Modelling’ (2014-2015, Swedish Environmental Protection Agency)
COMPILE – Cooperation on Mapping Physiological Indicators of Landscape Experience (2012 – 2015, SLU, KoHN-Medel Project, SLU, Sweden)
CULTOUR - “Cultural Landscapes of Tourism and Hospitality : Character, management and perceptions of tourism-related cultural landscapes” (2008-2011, Research Council of Norway 189977/10, subcontract from the Norwegian Forest and Landscape Institute).
Selected Other Research Projects
2014-2016 FARM – Farm Abandonment Regression Modelling. Multi-Linear-, Logistical- and Geographically Weighted- Regression modelling of farm production data and land use abandonment, on behalf of researchers at the Norwegian Forest and Landscape Institute. Financed by the Norwegian Forest and Landscape Institute.
2014-2015 Örensund Landscape Network, Interreg IVA.
2014 Rising Sea Levels – Extreme Value Flood Risk Estimation (in R-Stats) and Spatial Modelling (in ArcGIS) on behalf of researchers at Lund University (Sweden) and SLU (Sweden). Financed by the Swedish Civil Contingencies Agency.
2011-2014 WINDA – Software development in ArcGIS and VB.Net for a project simulating wind damage to forestry on behalf of researchers at SLU. Financed by SLU (Sweden).
2009-2011 GS Soil – “Assessment and Strategic Development of INSPIRE compliant Geo-data Services for European Soil Data” (EU e-content plus project http://www.gssoil.eu).
2008 – Secondment, Global Land Project, University of Copenhagen, Denmark. MLURI Funded.
2005 – 2010 OISIN – Optimised Inventorying Of Soil Information Networks. OISIN developed a heuristic, multi-variate, sub-sample optimisation algorithm by automatic comparison of statistical distributions (MLURI, Scottish Executive Core Funding).
2005 – 2010 VM-LITE, a software and spatial-data-structure to enable map-query in perspective view and model horizon graph topological complexity as part of a larger project Protecting and Enhancing Landscapes and Rural Communities (MLURI, Scottish Executive Core Funding).
2001 – 2005 The Ythan Project. Module leader monitoring the impact of a participatory ecosystem restoration project on public attitudes to nitrate pollution in an EU Nitrate Vulnerable Zone. (EU Life Environment LIFE00 ENV/UK/000894).
I am course responsible for the Advanced Digital Landscape Analysis MSc course, and am currently developing a theme course on GeoDesign.
Research interests : Modelling Landscape perceptions, processes and characteristics; Design of data structures to support spatio-temporal modelling tasks; Spatial Statistics; Spatial Data Infrastructures; Citizen Science; GeoDesign.
ESRI ArcMap, Q-GIS, MS Access, MS Office, MS Visual Studio, Eclipse, R, SPSS, VB.Net, VBA, ESRI ArcObjects, ESRI Avenue, Borland Delphi-Pascal, R, Python, HTML, Java.
Peer-reviewed articles in international journals
Sang, N., Gold, C., Miller, D., 2016, The topological viewshed: embedding topological pointers into digital terrain models to improve GIS capability for visual landscape analysis, International Journal of Digital Earth, 9, 1185-1205.
Sang N, Hägerhäll C, Ode, Å., 2015, The Euler character: a new type of visual landscape metric?, Environment and Planning B: Planning and Design, 42, 1, 110 – 132.
Sang, N., Dramstad, W., Bryn, A., 2014, Regionality in Norwegian farmland abandonment: Inferences from production data. Applied Geography, 55, 238-247.
Dramstad, D., Sang, N., 2010, Tenancy in Norwegian Agriculture., Land Use Policy, 27, 3, 946–956.
Ode, A., Hägerhäll, C., Sang, N., 2010, Analysing visual landscape complexity: theory and application, Landscape Research, 35, 111-131.
Sang, N., Ode, A.; Miller, D., 2008, Landscape metrics and visual topology in the analysis of landscape preference, Environment and Planning B, 35, 504-520.
Sang, N., 2008, Informing common pool resource problems: A survey of preference for catchment management strategies amongst farmers and the general public in the Ythan river catchment., Journal of Environmental Management, 88, 1161-1174.
Sang, N., Birnie, R.V.B., 2008, Spatial sampling and public opinion in environmental management: A case study of the Ythan catchment, Land Use Policy, 25, 30-42.
Sang,N., Birnie, R.V., Geddes, A., Bayfield, N.G., Midgley, J.L., Shucksmith, D.M. and Elston, D.A., 2005, Improving the rural data infrastructure: The problem of addressable spatial units in a rural context., Land Use Policy, 22, 175-186.
Book Chapters, Reports and Popular Science Articles
Sang, N., 2016, Wild Vistas : Progress in Computational Approaches to ‘Viewshed’ Analysis, in Steve Carver and Steffen Fritz Eds. Mapping the wild, Springer, London.
Sang, N., Ode-Sang, Å., Eds., 2015, A Review on the State of the Art in Scenario Modelling for Environmental Management, Swedish Environmental Protection Agency. ISBN 978-91-620-6695-6.
Deak, J., Sang, N., 2015, Flood And Climate Modelling For Urban Ecosystem Services, in Sang, N., Ode-Sang, Å., Eds., A Review On The State Of The Art In Scenario Modelling For Environmental Management, Swedish Environmental Protection Agency. ISBN 978-91-620-6695-6.
Sang, N., Aitkenhead, M., 2015, Data Mining, Machine Learning And Spatial Data Infrastructures For Scenario Modelling, in Sang, N., Ode-Sang, Å., Eds., A Review On The State Of The Art In Scenario Modelling For Environmental Management, Swedish Environmental Protection Agency. ISBN 978-91-620-6695-6.
Feiden K, Kirchenbauer V, Kruse F, Englisch M, [......], Sang N, 2013, Discover INSPIRE compliant harmonised soil data and services. Assessment and Strategic Development of INSPIRE compliant Geodata-Services for European Soil Data. 05/2012; Publisher: Paris-Lodron, University of Salzburg, Austria, Editor: Katharina Feiden and Fred Kruse.
Sang, N., 2011, Visual Topology : A Data Structure for Modeling Landscape Perception, Doctoral Thesis. The University of Glamorgan, Glamorgan, Wales, UK.
Sang, N., 2005, Prescription by post-code? If only it were that simple!: An analysis of the geographic distribution of GP patients, MSc Thesis, University of Leicester, Leicester, UK.
Sang, N., 2005, The Ythan Project, Final report summary of results from the community survey http://ythan.org.uk/WP8%205%20_community%20surveys_%20-%20analysis%20report.pdf
The Ythan Project, Contribution to the Layman Report, http://ec.europa.eu/environment/life/project/Projects/index.cfm?fuseaction=home.showFile&rep=file&fil=LIFE00_ENV_UK_000894_LAYMAN.pdf
Presentations at Conferences
Sang, N., 2016, Weaving the Cartographers Canvas : From 3D + 1 to 4D Mapping, GISRUK, April, Greenwich, UK.
Sang, N., 2015, A Review of State of the Art in Environmental Scenario Modelling’, GeoInfo, October, Malmö, Sweden.
Sang, N., Dramstad, D., Bryn, A., 2015, Agricultural Land : Dimensions of Management & Abandonment, CheriScape: Facing Global Change Through Landscape, 23-35 September Madrid, Spain.
Sang, N., 2015, Scenariomodellering, Forskningsdagen på Naturvårdsverket, February 2015, Stockholm, Sweden.
Sang, N., Dramstad, W., Bryn, A. , 2014, Multifaceted characterisation of spatial and temporal land abandonment patterns using descriptive statistics and massive logistic regression- the Norwegian case. Geographical Information Science Research UK, April, 2014, Glasgow, UK.
Sang, N., 2014, ’En kunskapsöversikt om scenario modullering’ Forskningsdagen på Naturvårdsverket, Stockholm, May 2014.
Sang, N., Dramstad, W., 2011, Mapping Estimates of Future Rates of Farm Abandonment Based on Historic Subsidy Information, People and Nature in Mountains, 21-23 September, Trondheim, Norway.
Sang, N., 2011, “New Horizons for the Stanford Bunny – A novel method for view analysis”, Geographical Information Science Research UK, April 2011, Lancaster, UK.
Sang, N., 2010, “OISIN - Optimised Inventorying of Soil Information Networks”, 4th Global Workshop on Digital Soil Mapping, , 24-26th May, Rome, Italy.
Sang, N., 2008, Return of the Stanford Bunny - definition, computation and application of visual topology, Geographical Information Science Research UK, 2-4 April, Manchester, UK.
Ode, A.; Sang, N., 2007, The influence of vision on calculations of experienced based landscape indicators., Scandinavian Conference on GIS, 5-7 September, Aas, Norway.
Sang, N.; Gold, C.; Miller, D., 2007, Shadow of the Stanford bunny: Analysing visual models of landscape data using Delaunay TIN., Proceedings International Symposium on Voronoi Diagrams in Science and Engineering 2007, (ISVD 2007), 9-11 July, University Glamorgan, Pontypridd, Wales, IEEE Computer Society, pp294-299.
Sang, N., Ode, A. and Miller, D.R., 2005, Visual topology for analysing landscape change, Landscape Change, ECLAS, September, Ankara, Turkey.
Sang, N., 2004, The topology matrix: a method for extracting and analysing higher order topology from triangular irregular networks, Geographical Information Science Research, UK. April, Norwich, UK.
Sang, N., 2004, Spatial sampling strategies for assessing public opinion under the Water Framework Directive: a case study of the Ythan Project., Proceedings of the European Regional Science Association Congress, Faculty of Economics, , August, Porto, Portugal. (Epainos Award)
Sang, N., 2002, Joined up geography - building Babel?, Association of Geographical Information, Earls Court, May, London, UK. (*Best Poster)