Geographic Knowledge Engineering for Territorial Intelligence
Robert Laurini, Computer Department, Knowledge Systems Institute, France
Hyperspectral Remote Sensing Data Analysis
José B. Dias, ECE,, Portugal
eARTh Observation - A World to Be Sensed
Jordi Corbera, Independent Researcher, Spain
Why the Map of the Future Will Not Look like a Map
Ed Parsons, Independent Researcher, United Kingdom
Geographic Knowledge Engineering for Territorial Intelligence
Robert Laurini
Computer Department, Knowledge Systems Institute
France
http://www.laurini.net/robert/
Brief Bio
Dr. Robert Laurini, presently professor emeritus at INSA, University of Lyon, France, is a well-known specialist in GIS. He has also taught GIS at the University of Maryland, USA, at the IUAV University of Venice, Italy and at several other universities especially in Latin America. He speaks French, English, Italian and Spanish. His present interests are in location-based services, geographic knowledge and territorial intelligence. He is also the founder of «Academics Without Borders» which is a network of academic consultants working for the modernization of higher education institutions in developing countries.
Abstract
In a lot of applications from agriculture to zoology, from environmental planning to territorial intelligence, actual systems of artificial intelligence are not very efficient, essentially because of a naïve representation of space.
As spatial knowledge corresponds to conventional geometric and topological knowledge, geographic knowledge corresponds to knowledge about geographic features in the real world even if real features can have spatial relationships between them. In other words, spatial knowledge is based on topological, projective and distance relations; but if applied to geographic features, one must take earth rotundity and other characteristics (demography, physical geographic, economic geography, etc.) into account.
After a rapid presentation of geographic relations and their properties, this paper will detail the 12 principles governing geographic knowledge. First emphasis will be given to various forms of geography knowledge, such as located facts, geographic clusters, flows, co-location rules and topological constraints.
Then, based on ribbon theory spatial relations and earth rotundity, geographic relations will be defined. For instance, let us consider two features in the real world associated with a DISJOINT relation; when down-scaling, those objects can be associated with a TOUCHES relation. As a consequence, any reasoning mechanism must be transformed accordingly.
Territorial intelligence is what business intelligence is for companies. Territorial intelligence can be defined as a cross-fertilization of human intelligence and artificial intelligence for sustainable development of any territory, countries, regions, cities, etc.
Hyperspectral Remote Sensing Data Analysis
Brief Bio
José M. Bioucas-Dias received the E.E., M.Sc., Ph.D., and “Agregado” degrees, in electrical and computer engineering, from the Technical University of Lisbon, Lisbon, Portugal, in 1985, 1991, 1995, and 2007, respectively. Since 1995, he has been with the Department of Electrical and Computer Engineering at Instituto Superior Técnico, Lisbon, Portugal. He is also a Senior Researcher with the Pattern and Image Analysis group at the Instituto de Telecomunicações, Lisbon, Portugal. His research interests include signal and image processing, pattern recognition, optimization, and remote sensing.
He was an Associate Editor for the IEEE Transactions on Circuits and Systems (1997-2000) and he is an Associate Editor for the IEEE Transactions on Image Processing and IEEE Transactions on Geoscience and Remote Sensing. He was and is involved in several national and international research projects and networks. Dr. Bioucas-Dias was and is a Guest Editor of IEEE special issues (IEEE TGRS, IEEE JSTARS, IEEE SPM, IEEE JSTSP). He has been a member of program/technical committees of several international conferences. He was General Co-Chair of the 3rd IEEE Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing-Whispers'2011.
Abstract
Hyperspectral remote sensing technology has advanced significantly in the past two decades. Current sensors onboard airborne and spaceborne platforms cover large areas of the Earth surface with unprecedented spectral, spatial, and temporal resolutions. These characteristics enable a myriad of applications requiring fine identification of materials or estimation of physical parameters. Very often, these applications rely on sophisticated and complex data analysis methods. The sources of difficulties are, namely, the high dimensionality and size of the hyperspectral data, the spectral mixing (linear and nonlinear), and the degradation mechanisms associated to the measurement process such as noise, blur, and atmospheric effects. In this talk, I will present an overview cross section of some relevant hyperspectral data analysis methods and algorithms, namely, data fusion, unmixing, classification, target detection, physical parameter retrieval, and fast computing. For each topic, I will summarize the mathematical problem involved, give relevant pointers to state-of-the-art algorithm to address these problems, and illustrate experimentally the potentialities and limitations of these algorithms.
eARTh Observation - A World to Be Sensed
Jordi Corbera
Independent Researcher
Spain
www.icgc.cat
Brief Bio
Dr. Jordi Corbera, Head of the Earth Observation area at the Institute Cartographic and Geological of Catalonia, the official geoinformation agency for the autonomous government of Catalonia. Ph. D in Physics on the use of Earth Observation in Antartica for climate change issues, he has developed his professional activity on the usability of space assets, in particular on Earth Observation and Navigation, working for European Commission agencies as expert evaluator in more than 60 research and development projects. Currently is the director of the post grade International Applied Techniques and Management on Geoinformation – www.iccartotechnology.com.
Abstract
Geoinformation of specific regions, territories and ecosystems requires tools operating on a stable and integrity basis. Earth Observation Platforms are nowadays a mature tehnology, allowing continous, high quality terrain observations. Consequently, space and air- borne EO is progressively becoming more affordable for new actors. The lecturer describe the main EO challenges and current added value experiences based on more than 30 years of EO at the Institute Cartographic and Geological of Catalonia, in particular addressed to provide geoinformation layers for sustainable and eficience urban areas (Smart City concept). The key note will revise the main drivers, elements, challenges and technologies to be considered when designing Geoinformation programs from Earth Observation assets. The analysis of the added value chain to transform data into knowledge and information is a paramount issue as well as to measure the social, environmental and economic impact of the potential products and services generated. A critical view of main applications in terms of energy efficiency, environmental/health and risk analysis will be discussed from a technical, operational and benefits point of view.
Why the Map of the Future Will Not Look like a Map
Ed Parsons
Independent Researcher
United Kingdom
Brief Bio
Ed Parsons is the Geospatial Technologist of Google, with responsibility for evangelising Google’s mission to organise the world’s information using geography. In this role he maintains links with Universities, Research and Standards Organisations which are involved in the development of Geospatial Technology.Ed was the first Chief Technology Officer in the 200-year-old history of Ordnance Survey, and was instrumental in moving the focus of the organisation from mapping to Geographical Information. He came to the Ordnance Survey from Autodesk, where he was EMEA Applications Manager for the Geographical Information Systems (GIS) Division.He earned a Masters degree in Applied Remote Sensing from Cranfield Institute of Technology and holds a Honorary Doctorate in Science from Kingston University, London and is a fellow of the Royal Geographical Society.
Abstract
Until very recently rich geographical information has been a valuable, but highly specialized, corner of the Web. With the widespread adoption of Web Mapping and the growth of consumer applications built around location technology maps have become mainstream. In the near future however the most widespread use of geospatial information will be to provide context for applications of the linked web. A linked Web that understands geographical concepts will immediately make much of the Web more useful to the developers of Web applications and will provide an important foundation for the emerging Internet of Things.