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Inferring Land Use from Remote Sensing Imagery: A context-based approach
Stockholm University, Faculty of Social Sciences, Department of Human Geography.
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.
Series
Meddelanden från Kulturgeografiska institutionen vid Stockholms universitet, ISSN 0585-3508 ; 147
Keyword [en]
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
Identifiers
URN: urn:nbn:se:su:diva-103082ISBN: 978-91-7447-887-7 (print)OAI: oai:DiVA.org:su-103082DiVA: diva2:715290
Public defence
2014-06-11, De Geersalen, Geovetenskapens Hus, Svante Arrhenius väg 14, Stockholm, 10:00 (English)
Opponent
Supervisors
Note

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
List of papers
1. Formalized interpretation of compound land use objects – Mapping historical summer farms from a single satellite image
Open this publication in new window or tab >>Formalized interpretation of compound land use objects – Mapping historical summer farms from a single satellite image
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
Keyword
land use, land cover, category semantics, representation, remote sensing
National Category
Environmental Sciences related to Agriculture and Land-use
Identifiers
urn:nbn:se:su:diva-66049 (URN)10.1080/1747423X.2010.537787 (DOI)
Available from: 2011-12-16 Created: 2011-12-16 Last updated: 2014-05-02Bibliographically approved
2. Qualitative satellite image analysis: Mapping spatial distribution of farming types in Ethiopia
Open this publication in new window or tab >>Qualitative satellite image analysis: Mapping spatial distribution of farming types in Ethiopia
2012 (English)In: Applied Geography, ISSN 0143-6228, E-ISSN 1873-7730, Vol. 32, no 2, 465-476 p.Article in journal (Refereed) Published
Abstract [en]

Satellite images have enormous potential for qualitative land use analysis. This paper presents empirical results that demonstrate how normally invisible dimensions produced by land use can be identified by enriching satellite data with qualitative information from field studies.

Land use can be defined as the intentional use of a specific piece of land resulting in patterns of ecological responses that are visible in the land cover and landscape. Responses to land use often result in a heterogeneous combination of reflectance in satellite images. Statistical methods used in the classification of satellite imagery are limited in their capacity to handle categories consisting of heterogeneous combinations of spectral values. To overcome this limitation, a contextual post-classification method has been used to map land cover configurations as related to different agricultural practices in the district of Sodo, Ethiopia.

The results show that it is possible to map socio-spatial distribution of different agricultural and socioeconomic practices on a regional level by combining field observations and spatial contextual information. The empirical findings show local agricultural activity variations in cash crop production and subsistence agriculture in the Sodo district of Ethiopia.

Place, publisher, year, edition, pages
Elsevier, 2012
National Category
Geosciences, Multidisciplinary
Identifiers
urn:nbn:se:su:diva-66056 (URN)10.1016/j.apgeog.2011.04.001 (DOI)000298362400025 ()
Available from: 2011-12-16 Created: 2011-12-16 Last updated: 2017-12-08Bibliographically approved
3. Extraction of urban areas with different functions and underlying planning theories and practices using Window Independent Context Segmentation
Open this publication in new window or tab >>Extraction of urban areas with different functions and underlying planning theories and practices using Window Independent Context Segmentation
(English)Manuscript (preprint) (Other academic)
National Category
Human Geography
Identifiers
urn:nbn:se:su:diva-103084 (URN)
Available from: 2014-05-02 Created: 2014-05-02 Last updated: 2014-05-02Bibliographically approved
4. Socioeconomic residential profiles in urban areas classified by the WICS method
Open this publication in new window or tab >>Socioeconomic residential profiles in urban areas classified by the WICS method
(English)Manuscript (preprint) (Other academic)
National Category
Human Geography
Identifiers
urn:nbn:se:su:diva-103085 (URN)
Available from: 2014-05-02 Created: 2014-05-02 Last updated: 2014-05-02Bibliographically approved
5. Classification of different urban categories corresponding to the strategic spatial level of urban planning and management using a SPOT4 scene
Open this publication in new window or tab >>Classification of different urban categories corresponding to the strategic spatial level of urban planning and management using a SPOT4 scene
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.

Keyword
urban remote sensing, spatial analysis, segmentation
National Category
Human Geography
Identifiers
urn:nbn:se:su:diva-103086 (URN)10.1080/14498596.2014.943309 (DOI)000353103900008 ()
Available from: 2014-05-02 Created: 2014-05-02 Last updated: 2015-05-18Bibliographically approved
6. Automatic mapping of standing dead trees after an insect outbreak using the Window Independent Context Segmentation method
Open this publication in new window or tab >>Automatic mapping of standing dead trees after an insect outbreak using the Window Independent Context Segmentation method
2014 (English)In: Journal of forestry, ISSN 0022-1201, E-ISSN 1938-3746, Vol. 112, no 6, 564-571 p.Article in journal (Refereed) Published
Abstract [en]

Since the 1980s, there has been an increase in the spruce bark beetle population in the Bavarian Forest National Park in southeastern Germany. There is a need for accurate and time-effective methods for monitoring the outbreak, because manual interpretation of image data is time-consuming and expensive. In this article, the window independent context segmentation method is used to map deadwood areas. The aim is to evaluate the method’s ability to monitor deadwood areas on a yearly basis. Two-color infrared scenes with a spatial resolution of 40 × 40 cm from 2001 and 2008 were used for the study. The method was found to be effective with an overall accuracy of 88% for the 2001 scene and 90% for the 2008 scene.

National Category
Forest Science Geosciences, Multidisciplinary
Research subject
Human Geography
Identifiers
urn:nbn:se:su:diva-103087 (URN)10.5849/jof.13-050 (DOI)000344981800003 ()
Available from: 2014-05-02 Created: 2014-05-02 Last updated: 2017-12-05Bibliographically approved

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