Change search
ReferencesLink to record
Permanent link

Direct link
Classification of different urban categories corresponding to the strategic spatial level of urban planning and management using a SPOT4 scene
Stockholm University, Faculty of Social Sciences, Department of Human Geography.
2015 (English)In: Journal of Spatial Science, ISSN 1836-5655, Vol. 60, no 1, 99-117 p.Article, review/survey (Refereed) Published
Abstract [en]

Information about the spatial and structural properties as well as different indicators of social and economic functions cannot be easily extracted from remote-sensing data in an urban milieu. This paper focuses on the extraction of information that is relevant to the strategic spatial level of urban planning management, i.e., more general land-use descriptions, using the window-independent context segmentation method to extract urban area categories from a SPOT4 satellite scene. In this study, we were able to extract three different urban categories, industrial/commercial, and two residential categories that belong to different suburbanisation phases.

Place, publisher, year, edition, pages
2015. Vol. 60, no 1, 99-117 p.
Keyword [en]
urban remote sensing, spatial analysis, segmentation
National Category
Human Geography
URN: urn:nbn:se:su:diva-103086DOI: 10.1080/14498596.2014.943309ISI: 000353103900008OAI: diva2:715288
Available from: 2014-05-02 Created: 2014-05-02 Last updated: 2015-05-18Bibliographically 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

Open Access in DiVA

No full text

Other links

Publisher's full text

Search in DiVA

By author/editor
Nielsen, Michael Meinild
By organisation
Department of Human Geography
Human Geography

Search outside of DiVA

GoogleGoogle Scholar
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Altmetric score

Total: 85 hits
ReferencesLink to record
Permanent link

Direct link