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Formalized interpretation of compound land use objects – Mapping historical summer farms from a single satellite image
Department of Geography, The Ohio State University, Columbus, OH, USA.
Department of Economics, Swedish University of Agricultural Sciences, Uppsala, Sweden.
Stockholm University, Faculty of Social Sciences, Department of Human Geography.
2012 (English)In: Journal of Land Use Science, ISSN 1747-423X, Vol. 7, no 1, 89-107 p.Article in journal (Refereed) Published
Abstract [en]

Notions of land cover relating to physical landscape characters are readily captured by satellite imagery. Land use on the other hand relates more to the societal aspects of a landscape. We argue that much of the spatial configuration of landscape characters is related to land use and that satellite data can be used to represent and investigate interpretations of land use. We propose and demonstrate the joint use of a novel SRPC procedure for satellite imagery together with an explicit representation of category semantics. We use these two mechanisms to identify a collection of conceptual spaces related to land use on Swedish historic summer farms. We also outline a framework for analysis of the relations between two separate ways of knowing: the machine-based knowledge and the human, mental knowledge. An evaluation demonstrates that satellite images can be used to identify land use processes as a mixture of land cover objects occurring in particular spatial contextual relationships closely tied to the land use category semantics. This opens up an unexplored possibility for research on vague spatial ontologies and questions on how to formally articulate different interpretations of space, land use, and other branches of spatial social science.

Place, publisher, year, edition, pages
Taylor & Francis, 2012. Vol. 7, no 1, 89-107 p.
Keyword [en]
land use, land cover, category semantics, representation, remote sensing
National Category
Environmental Sciences related to Agriculture and Land-use
URN: urn:nbn:se:su:diva-66049DOI: 10.1080/1747423X.2010.537787OAI: diva2:466807
Available from: 2011-12-16 Created: 2011-12-16 Last updated: 2014-05-02Bibliographically approved
In thesis
1. Inferring Land Use from Remote Sensing Imagery: A context-based approach
Open this publication in new window or tab >>Inferring Land Use from Remote Sensing Imagery: A context-based approach
2014 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

This doctoral thesis investigates the potential of classification methods based on spatial context to infer specific forms of land use from remote sensing data. The problem is that some types of land use are characterized by a complex configuration of land covers that traditional per-pixel based methods have problems classifying due to spectral heterogeneity. The problem of spectral heterogeneity is also present in classification of high resolution imagery. Two novel methods based on contextual information are evaluated, Spatial Relational Post-Classification (SRPC) and Window Independent Context Segmentation (WICS). The thesis includes six case studies in rural and urban areas focusing on the classification of: agricultural systems, urban characteristics, and dead wood areas. In the rural case studies specific types of agricultural systems associated with different household strategies are mapped by inferring the physical expression of land use using the SRPC method. The urban remote sensing studies demonstrate how the WICS method is able to extract information corresponding to different phases of development. Additionally, different urban classes are shown to correspond to different socioeconomic profiles, demonstrating how urban remote sensing can be used to make a connection between the physical environment and the social lives of residents. Finally, in one study the WICS method is used to successfully classify dead trees from high resolution imagery. Taken together these studies demonstrate how approaches based on spatial context can be used to extract information on land use in rural and urban environments where land use manifests itself in the form of complex spectral class and land cover patterns. The thesis, thus, contributes to the research field by showing that contextual methods can capture multifaceted patterns that can be linked to land use. This, in turn, enables an increased use of remote sensing data, particularly in the social sciences.

Place, publisher, year, edition, pages
Stockholm: Department of Human Geography, Stockholm University, 2014. 174 p.
Meddelanden från Kulturgeografiska institutionen vid Stockholms universitet, ISSN 0585-3508 ; 147
land use, remote sensing, urban remote sensing, image analysis, segmentation, spatial context, land cover, land cover configuration, farming types, bark beetle, dead trees, forest inventory
National Category
Human Geography
Research subject
Human Geography
urn:nbn:se:su:diva-103082 (URN)978-91-7447-887-7 (ISBN)
Public defence
2014-06-11, De Geersalen, Geovetenskapens Hus, Svante Arrhenius väg 14, Stockholm, 10:00 (English)

At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 3: Manuscript. Paper 4: Manuscript. Paper 5: Manuscript. Paper 6: Manuscript.

Available from: 2014-05-20 Created: 2014-05-02 Last updated: 2014-09-30Bibliographically approved

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Nielsen, Michael Meinild
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