Geoinformatics

VGI as Big Data. A New but Delicate Geographic Data-Source.

by Florian Fischer

In: Geoinformatics 2012, issue 3, vol 15, pp. 46-47.

APIs from popular geo-social applications like Foursquare provide big data with geographical context. These data –... more APIs from popular geo-social applications like Foursquare provide big data with geographical context. These data – also termed Volunteered Geographic Information – are a valuable information base for real-time geodemographics for user profiling. But big data are not always better data. With regard to geodemographic analysis, big geographical data hold obstacles in terms of reliability and validity that require a more comprehensive understanding of the genesis of VGI.

Wertschöpfung 2.0: Neue Produktions- und Nutzungspraktiken auf dem Geoinformationsmarkt

by Florian Fischer

In: GW-Unterricht, 120, pp. 30-46.

Geodaten sind ein wichtiger Teil unseres Alltags geworden und werden immer häufiger für den Unterricht genutzt. Das... more Geodaten sind ein wichtiger Teil unseres Alltags geworden und werden immer häufiger für den Unterricht genutzt. Das zeigt sich beim selbstverständlichen Einsatz von Navigationsgeräten oder der Erkundung einer Urlaubsregion im Internet. Dabei schöpfen die Akteure auf dem Geoinforma-tionsmarkt ihren Gewinn nicht allein aus der Erfassung und dem Verkauf von Geodaten. Vor allem in der Herstellung und Nutzung von Geoinformationsprodukten steckt hohes Marktpotenzial. Die Ökonomisierung des Geoinformationsmarktes befindet sich in einem rasanten Wandel. Während früher vor allem analoge kartographische Produkte, insbesondere für den Gebrauch in Freizeit und Alltag, den Markt dominierten, sind es heute digitale, interaktive und mobile Geomedien. Neben der Technologie zur Produktion und Verbreitung von Geomedien haben sich auch die zugrunde-liegenden Produktions- und Nutzungspraktiken, sowie die Wertschöpfungsmodelle verändert. Dieser Artikel gibt einen straffen Überblick über die Wertschöpfung mit Geoinformation und skiz-ziert den Wandel des Geoinformationsmarktes von einem angebots- und großkundendominierten Markt zu einem nachfrageorientierten Massenmarkt.

Anwendungspotenziale eines Geosimulationsmodells für die Wohnungsmarktforschung

by Florian Fischer

Which Service Interfaces fit the Model Web?

by Gregoire Dubois

Schade, S., N. Ostländer, C. Granell, M. Schulz, D. McInerney, G. Dubois, L. Vaccari, M. Chinosi, L. Díaz, L. Bastin, R. Jones (2012). Which Service Interfaces fit the Model Web? In: "GEOProcessing 2012. The Fourth International Conference on Advanced Geographic Information Systems, Applications, and Services ", January 30 - February 4, 2012 - Valencia, Spain

The Model Web has been proposed as a concept for integrating scientific models in an interoperable and collaborative... more The Model Web has been proposed as a concept for integrating scientific models in an interoperable and collaborative manner. However, four years after the initial idea was formulated, there is still no stable long term solution. Multiple authors propose Web Service based approaches to model publication and chaining, but current implementations are highly case specific and lack flexibility. This paper discusses the Web Service interfaces, which are required for supporting integrated environmental modeling in a sustainable manner. We explore ways to expose environmental models and their components using Web Service interfaces. Our discussions present work in progress for establishing the Web Services technological grounds for simplifying information publication and exchange within the Model Web. As a main outcome, this contribution identifies challenges in respect to the required geoprocessing and relates them to currently available Web Service standards.

Representações computacionais do espaço: fundamentos epistemológicos da ciência da geoinformação

by Gilberto Camara

TerraLib: An open source GIS library for large-scale environmental and socio-economic applications

by Gilberto Camara

Spatial statistical analysis of land-use determinants in the Brazilian Amazonia: Exploring intra-regional heterogeneity

by Gilberto Camara

Fields and objects algebras for GIS operations

by Gilberto Camara

Forecasting Biomes of Protected Areas

by Gregoire Dubois

Jon Olav Skøien, Gregoire Dubois, Jorge De Jesus
Procedia Environmental Sciences
Volume 7, 2011, Pages 44-49
Spatial Statistics 2011: Mapping Global Change

Protected areas are designed for a range of purposes, mainly with the aim of protecting certain habitats including... more Protected areas are designed for a range of purposes, mainly with the aim of protecting certain habitats including their associated species. The possible threats have mainly been thought of as anthropogenic influences such as deforestation from lodging and fires, hunting, construction of roads and houses etc. The biomes of the park have been assumed to be the constant, so that the distribution of animals and vegetation would only change rapidly due to direct anthropogenic influence. However, with a changing climate, the conditions within the park might change to conditions unsuitable for the current population of animals and vegetation within relatively short time. In this paper we will introduce eHabitat, a Web Processing Service (WPS) designed to compute the likelihood of finding ecosystems with equal properties. We present a use case where eHabitat is applied to an ensemble of climate change scenarios, in order to compute the probability that an ecosystem's ecological niche will occur in a particular location in the future. This will help us to identify the future suitability of an area for a particular ecosystem

Uncertainty propagation in chained web based modeling services: the case of eHabitat

by Gregoire Dubois

Skøien, J., M. Schulz, G. Dubois, R. Jones, G.B.M. Heuvelink, D. Cornford (2011). Uncertainty propagation in chained web based modeling services: the case of eHabitat.  In: “Innovation in sharing environmental observations and information. Proceedings of EnviroInfo 2011, 25th International Conference Environmental Informatics”. W. Pillmann, S. Schade and P. Smits (Eds), pp: 46-58, 5-7 October 2011, Ispra, Italy.

eHabitat is a Web Processing Service (WPS) designed to compute the likelihood of finding ecosystems with similar... more eHabitat is a Web Processing Service (WPS) designed to compute the likelihood of finding ecosystems with similar conditions. Starting from a reference area, typically a protected area, one can compute for each pixel of a region of interest the probability to find a combination of a set of predefined environmental indicators that is similar to the one observed in the reference area using the Mahalanobis distances to the mean and covariance of these indicators. Inputs to the WPS are thus the reference polygon and a set of environmental indicators, typically thematic geospatial “layers”, which can be discovered using standardised catalogues. The outputs can be tailored to specific end user needs in terms of data format and data resolution. Because these input layers can range from geophysical data captured through remote sensing to socio-economical indicators, eHabitat is exposed to a broad range of different types and levels of uncertainties which are inevitably propagated through the service (see e.g. Heuvelink, 1998). Potentially chained to other services to perform ecological forecasting, for example, eHabitat would be an additional component further propagating uncertainties from a potentially long chain of model services. Such a configuration of distributed data and model services as envisaged by initiatives such as the “Model Web” from the Group on Earth Observations, to be of any use to policy or decision makers, requires from users clear information on data uncertainties. The development of such an Uncertainty-Enabled Model Web is the scope of the UncertWEB project which is promoting interoperability between data and models with quantified uncertainty and building a framework on existing open, international standards. It is the objective of this paper to illustrate a few key ideas behind UncertWeb using eHabitat to discuss the main types of uncertainties the WPS has to deal with and to present the benefits of the use of the UncertWeb framework.

Predicting habitat suitability with machine learning models: the potential area of Pinus sylvestris L. in the Iberian Peninsula

by Markus Neteler

M. Benito Garzón, R. Blazek, M. Neteler, R. Sanchez de Dios, H. Sainz Ollero, and C. Furlanello, 2006: Predicting habitat suitability with Machine Learning models: the potential area of Pinus sylvestris L. in the Iberian Peninsula. Ecological Modelling, 197(3-4), pp. 383-393

We present a modelling framework for predicting forest areas. The framework is obtained by integrating a machine... more We present a modelling framework for predicting forest areas. The framework is obtained by integrating a machine learning software suite within the GRASS Geographical Information System (GIS) and by providing additional methods for predictive habitat modelling. Three machine learning techniques (Tree-Based Classification, Neural Networks and Random Forest) are available in parallel for modelling from climatic and topographic variables. Model evaluation and parameter selection are measured by sensitivity-specificity ROC analysis, while the final presence and absence maps are obtained through maximisation of the kappa statistic. The modelling framework is applied at a resolution of 1 km with Iberian subpopulations of Pinus sylvestris L. forests. For this data set, the most accurate algorithm is Breiman's random forest, an ensemble method which provides automatic combination of tree-classifiers trained on bootstrapped subsamples and randomised variable sets. All models show a potential area of P. sylvestris for the Iberian Peninsula which is larger than the present one, a result corroborated by regional pollen analyses.

Keywords: Machine learning; Random forest; Neural networks; Classification and regression trees; AUC; Kappa; Iberian Peninsula; Pinus sylvestris L.; Habitat suitability

Open source GIS: a GRASS GIS approach

by Markus Neteler

Markus Neteler and Helena Mitasova, 2008, Open Source GIS: A GRASS GIS Approach. Third Edition. 406 pages, 80 illus., Springer, New York, ISBN: 978-0-387-35767-6

With this third edition of Open Source GIS: A GRASS GIS Approach, we enter the new era of GRASS6, the first release... more With this third edition of Open Source GIS: A GRASS GIS Approach, we enter the new era of GRASS6, the first release that includes substantial new code developed by the International GRASS Development Team. The dramatic growth in open source software libraries has made GRASS6 development more efficient, and has enhanced GRASS interoperability with a wide range of open source and proprietary geospatial tools.

Thoroughly updated with material related to GRASS6, the third edition includes new sections on attribute database management and SQL support, vector networks analysis, lidar data processing and new graphical user interfaces. All chapters are updated with numerous practical examples using the first release of a comprehensive, state-of-the-art geospatial data set.

Open Source GIS: A GRASS GIS Approach, Third Edition preserves the continuity of previous editions by maintaining the book's proven structure. This volume is structured for a professional audience composed of researchers and practitioners in government and industry, as well as graduate students interested in geospatial analysis and modeling.

Benchmarking GIS: a charter for European Education

by Karl Donert

Donert K (2009), Benchmarking GIS: a charter for European Education, in Jekel T, Koller A and Donert K (eds.) (2009),... more Donert K (2009), Benchmarking GIS: a charter for European Education, in Jekel T, Koller A and Donert K (eds.) (2009), Learning with GeoInformation IV, Berlin, Wichman Verlag

Go-Geo! Metadata News newsletter (August 2007)

by Tony Mathys

Go-Geo! Metadata Newsletter (November 2010)

by Tony Mathys

Go-Geo! Metadata News newsletter (April 2010)

by Tony Mathys

The Go-Geo! Spatial Data Portal: A Data Discovery and Research Tool for UK Academia

by Tony Mathys

ASSIGNation, Journal of the ASLIB Social Science Interest Group and Network (ASSIGN) in the U.K

Metropolitan GIS: The Minnesota Metadata Mission

by Tony Mathys

Geo Info Systems Journal, November 1999 Geo Info Systems Journal, November 1999

Making Metadata a Part of your Daily Diet

by Tony Mathys

Tony Mathys and Rick Gelbmann

(Please note that with other references found pertaining to this article, the authors are switched around. This was a mistake on the part of URISA as the Met Council would not cover my expenses to present the paper at the URISA conference, which Rick Gelbmann kindly did on my behalf, so URISA assumed him to be first author).

1999 URISA Conference Proceedings

A GIS Comparative Analysis of Bronze Age Settlement Patterns and the Contemporary Physical Landscape in the Jazira Region of Syria

by Tony Mathys

Most of the datasets presented in this thesis are available for free in ArcGIS shapefile format on the ShareGeo Open data repository at http://www.sharegeo.ac.uk/.

These datasets are available for everyone to use as it is important to encourage data sharing in support of research activities.

There are also some CORONA satellite images available on ShareGeo for the Syrian Jazira region. The plan is to eventually provide complete CORONA coverage for this region, though geo-referencing will not be precise as it's intended to be more for user orientation.

Acknowledgement should go to the U.S. Geological Survey (USGS), which makes CORONA imagery available via its EarthExplorer online data service at http://edcsns17.cr.usgs.gov/NewEarthExplorer/
Many CORONA images are available to download for free from this service, though require processing and geo-referencing for use in a GIS or a software package for processing remotely sensed imagery.

Relevant to this, and the thesis, is the following paper presented which first introduced how CORONA satellite imagery could be applied to archaeological work in the Near East. Martin Fowler also wrote about the potential of CORONA in the Aerial Archaeology Research Group (AARG) news.

Mathys, Tony. “The Use of Declassified Intelligence Satellite Photographs in a GIS (IDRISI) to Map Archaeological Sites and the Surrounding Landscape in the Northeastern Region of the Syrian Jazirah. The University of Chicago Oriental Institute, NASA and St. Cloud State University Remote Sensing Applications in Archaeology Conference. St. Cloud, Minnesota, May 29-31, 1997.

Unfortunately, papers presented at this conference were not published.

My gratitude and thanks to Dr Sarah Parcak for citing this unpublished conference paper in her book (Satellite Remote Sensing in Archaeology), and to Dr Aled Rowlands and Dr Apostolos Sarris for citing it in their Journal of Archaeological Science article 34 (2007).