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Satellie Monitoring of Urban Growth and Indicator-based Assessment of Environmental Impact
KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geodesy and Geoinformatics.
2014 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

One of the major consequences of urbanization is the transformation of land surfaces from rural/natural environments to built-up land that supports diverse forms of human activity. These transformations impact the local geology, climate, hydrology, flora and fauna and human-life supporting ecosystem services in the region. Mapping and analysis of land use/land cover change in urban regions and tracking their environmental impact is therefore of vital importance for evaluating policy options for future growth and promoting sustainable urban development.

The overall objective of this research is to investigate the extent of urban growth and/or sprawl and its potential environmental impact in the regions surrounding a few selected major cities in North America, Europe and Asia using landscape metrics and other environmental indicators to assess the landscape changes. The urban regions examined are the Greater Toronto Area (GTA) in Canada, Stockholm region and County in Sweden and Shanghai in China. The analyses are based on classificatons of optical satellite imagery (Landsat TM/ETM+ or SPOT 1/5) between 1985 and 2010. Maximum likelihood classification (MLC) under urban/rural masks, objectbased image analysis (OBIA) with rule-based classification and support vector machines (SVM) classification methods were used with grey level cooccurrence matrix (GLCM) texture features as input to help obtain higher accuracies. Based on the classification results, landscape metrics, selected environmental indicators and indices, and ecosystem service valuation were calculated and used to estimate environmental impact of urban growth.

The results show that urban areas in the GTA grew by nearly 40% between 1985 and 2005. Results from the landscape metrics and urban compactness indicators show that low-density built-up areas increased significantly in the GTA between 1985 and 2005, mainly at the expense of agricultural areas. The majority of environmentally significant areas were increasingly surrounded by urban areas between 1985 and 2005, furthering their isolation from other natural areas. Urban areas in the Stockholm region increased by 10% between 1986 and 2006. The landscape metrics indicated that natural areas became more isolated or shrank whereas new small urban patches came into being. The most noticeable changes in terms of environmental impact and urban expansion were in the east and north of the study area. Large forested areas in the northeast dropped the most in terms of environmental impact ranking, while the most improved analysis units were close to the central Stockholm area. The study comparing Shanghai and Stockholm County revealed that urban areas increased ten times as much in Shanghai as they did in Stockholm, at 120% and 12% respectively. The landscape metrics results show that fragmentation in both study regions occurred mainly due to the growth of high density built-up areas in previously more natural environments, while the expansion of low density built-up areas was for the most part in conjunction with pre-existing patches. The growth in urban areas resulted in ecosystem service value losses of approximately 445 million USD in Shanghai, mostly due to the decrease in natural coastal wetlands, while in Stockholm the value of ecosystem services changed very little.

This study demonstrates the utility of urban and environmental indicators derived from remote sensing data via GIS techniques in assessing both the spatio-temporal dynamics of urban growth and its environmental impact in different metropolitan regions. High accuracy classifications of optical medium resolution remote sensing data are achieved thanks in part to the incorporation of texture features for both object- and pixel-based classification methods, and to the use of urban/rural masks with the latter. The landscape metrics calculated based on the classifications are useful in quantifying urban growth trends and potential environmental impact as well as facilitating their comparison. The environmental indicator results highlight the challenges in terms of sustainable urban growth unique to each landscape, both spatially and temporally. The next phase of this PhD research will involve finding valid methods of comparing and contrasting urban growth patterns and estimated environmental impact in different regions of the world and further exploration of how to link urbanizing landscapes to changes in ecosystem services via environmental indicators.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2014. , xi, 91 p.
Series
TRITA-SOM, ISSN 1653-6126 ; 2014-15
Keyword [en]
Urban growth, remote sensing, landcover classification, landscape metrics, environmental indicators, environmental impact, Greater Toronto Area, Stockholm, Shanghai
National Category
Environmental Management
Identifiers
URN: urn:nbn:se:kth:diva-157669ISBN: 978-91-7595-353-3 (print)OAI: oai:DiVA.org:kth-157669DiVA: diva2:770995
Presentation
2014-12-12, Seminarierum 4055, 3tr, Drottning Kristinas Väg 30, Stockholm, 10:00 (English)
Opponent
Supervisors
Note

QC 20141212

Available from: 2014-12-12 Created: 2014-12-12 Last updated: 2016-02-09Bibliographically approved
List of papers
1. Satellite Monitoring and Impact Assessment of Urban Growth in Stockholm, Sweden between 1986 and 2006
Open this publication in new window or tab >>Satellite Monitoring and Impact Assessment of Urban Growth in Stockholm, Sweden between 1986 and 2006
2010 (English)In: Imagin[e,g] Europe: Proceedings of the 29th Symposium of the European Association of Remote Sensing Laboratories, Chania, Greece / [ed] Ioannis Manakos, Chariton Kalaitzidis, IOS Press, 2010, 131-142 p.Conference paper, Published paper (Refereed)
Abstract [en]

The objective of this research is to investigate the extent of land-cover change in and around Stockholm from 1986 to 2006 and the nature of the resulting landscape fragmentation with a particular focus on the possible environmental impact. Four scenes of SPOT imagery over the Stockholm area were acquired for this study: two on 13 June 1986, one on 5 August 2006 and one on 4 June 2008. Various image processing and classification algorithms were tested and compared. The best classification results were obtained using an object-based and rule-based approach with texture measures as well as spectral data as inputs. The image pairs from the two decades were classified into seven land cover categories for Stockholm Municipality, i.e., low-density built-up, high-density built-up, industrial areas, open land, forest, mixed forest and open land, and water. The overall accuracies were 93% (kappa: 0.91) for 1986 and 97% (kappa: 0.96) for 2006. Landscape fragmentation and change was evaluated using spatial metrics. The spatial metric results reveal that urban areas increased at the expense of non-built up areas by around 2% both on the municipal and regional levels. The 2006/2008 classification gives evidence of being a more fragmented landscape than that of 1986. While urban areas have become denser within Stockholm municipality, which is in line with the region's development policy, more natural land cover types have at the same time been eroded; a development not in line with the regional goal of maintaining the area's green spaces. The classification technique used on the municipality will be expanded to the region as a whole, and regional trends and consequent recommendations will be the focus of future research

Place, publisher, year, edition, pages
IOS Press, 2010
National Category
Remote Sensing Environmental Management
Identifiers
urn:nbn:se:kth:diva-88916 (URN)10.3233/978-1-60750-494-8-131 (DOI)978-1-60750-493-1 (ISBN)
Conference
29th Symposium of the European Association of Remote Sensing Laboratories, 15-18 June 2009 Chania, Greece
Note

QC 20120215

Available from: 2012-02-14 Created: 2012-02-14 Last updated: 2014-12-12Bibliographically approved
2. Satellite Monitoring of Urban Sprawl and Assessment of its Potential Environmental Impact in the Greater Toronto Area Between 1985 and 2005
Open this publication in new window or tab >>Satellite Monitoring of Urban Sprawl and Assessment of its Potential Environmental Impact in the Greater Toronto Area Between 1985 and 2005
2012 (English)In: Environmental Management, ISSN 0364-152X, E-ISSN 1432-1009, Vol. 50, no 6, 1068-1088 p.Article in journal (Refereed) Published
Abstract [en]

This research investigates urban sprawl in the Greater Toronto Area (GTA) between 1985 and 2005 and the nature of the resulting landscape fragmentation, particularly with regard to the Oak Ridges Moraine (ORM), an ecologically important area for the region. Six scenes of Landsat TM imagery were acquired in summer of 1985, 1995, and 2005. These images and their texture measures were classified into eight land cover classes with very satisfactory final overall accuracies (93-95 %). Analysis of the classifications indicated that urban areas grew by 20 % between 1985 and 1995 and by 15 % between 1995 and 2005. Landscape fragmentation due to spatio-temporal land cover changes was evaluated using urban compactness indicators and landscape metrics, and results from the latter were used to draw conclusions about probable environmental impact. The indicator results showed that urban proportions increased in nearly all areas outside of the metropolitan center, including on portions of the ORM. The landscape metrics reveal that low density urban areas increased significantly in the GTA between 1985 and 2005, mainly at the expense of agricultural land. The metric results indicate increased vulnerability and exposure to adverse effects for natural and semi-natural land cover through greater contrast and lowered connectivity. The degree of urban perimeter increased around most environmentally significant areas in the region. Changes like these negatively impact species and the regional water supply in the GTA. Further investigation into specific environmental impacts of urban expansion in the region and which areas on the ORM are most at risk is recommended.

Keyword
Landsat TM, Landscape metrics, Urban compactness indicators, Oak Ridges Moraine, Environmentally significant areas
National Category
Remote Sensing Environmental Management
Identifiers
urn:nbn:se:kth:diva-87840 (URN)10.1007/s00267-012-9944-0 (DOI)000311292800009 ()2-s2.0-84871321192 (Scopus ID)
Funder
Swedish Research CouncilFormas
Note

QC 20121219

Available from: 2012-02-14 Created: 2012-02-14 Last updated: 2017-12-07Bibliographically approved
3. Satellite Monitoring of Urban Land Cover Change in Stockholm Between 1986 and 2006 and Indicator-Based Environmental Assessment
Open this publication in new window or tab >>Satellite Monitoring of Urban Land Cover Change in Stockholm Between 1986 and 2006 and Indicator-Based Environmental Assessment
2013 (English)In: Earth Observation of Global Changes (EOGC), Springer Berlin/Heidelberg, 2013, 205-222 p.Chapter in book (Refereed)
Abstract [en]

Over the past few decades, there has been substantial urban growth in Stockholm, Sweden, now the largest city in Scandinavia. This research investigates and evaluates the evolution of land cover/use change in Stockholm between 1986 and 2006 with a particular focus on what impact urban growth has had on the environment using indicators derived from remote sensing and environmental data. Four scenes of SPOT imagery over the Stockholm County area were acquired for this study including two on 13 June 1986, one on 5 August 2006 and one on 4 June 2008. These images are classified into seven land cover categories using an object-based and rule-based approach with spectral data and texture measures as inputs. The classification is then used to generate spatial metrics and environmental indicators for evaluation of fragmentation and land cover/land use change. Based on the environmental indicators, an environmental impact index is constructed for both 1986 and 2006 and then compared. The environmental impact index is based on the proportion and condition of green areas important for ecosystem services, proximity of these areas to intense urban land use, proportion of urban areas in their immediate vicinity, and how impacted they are by noise. The analysis units are then ranked according to their indicator values and an average of the indicator rankings gives an overall index score. Results include a ranking of the landscape in terms of environmental impact in 1986 and 2006, as well as an analysis of which units have improved the least or the most and why. The highest ranked units are located most often to the north and east of the central Stockholm area, while the lowest tend to be located closer to the center itself. Yet units near the center also tended to improve the most in ranking over the two decades, which would suggest a convergence towards modest urban expansion and limited environmental impact.

Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2013
Series
Lecture Notes in Geoinformation and Cartography, ISSN 1863-2246
National Category
Remote Sensing Environmental Management
Identifiers
urn:nbn:se:kth:diva-87792 (URN)10.1007/978-3-642-32714-8_14 (DOI)978-3-642-32713-1 (ISBN)
Note

QC 20121219

Available from: 2012-02-14 Created: 2012-02-14 Last updated: 2014-12-12Bibliographically approved
4. Satellite monitoring of urbanization and environmental impacts: A comparison of Stockholm and Shanghai
Open this publication in new window or tab >>Satellite monitoring of urbanization and environmental impacts: A comparison of Stockholm and Shanghai
2015 (English)In: International Journal of Applied Earth Observation and Geoinformation, ISSN 0303-2434, Vol. 38, 138-149 p.Article in journal (Refereed) Published
Abstract [en]

This study investigates urbanization and its potential environmental consequences in Shanghai andStockholm metropolitan areas over two decades. Changes in land use/land cover are estimated fromsupport vector machine classifications of Landsat mosaics with grey-level co-occurrence matrix fea-tures. Landscape metrics are used to investigate changes in landscape composition and configurationand to draw preliminary conclusions about environmental impacts. Speed and magnitude of urbaniza-tion is calculated by urbanization indices and the resulting impacts on the environment are quantified byecosystem services. Growth of urban areas and urban green spaces occurred at the expense of croplandin both regions. Alongside a decrease in natural land cover, urban areas increased by approximately 120%in Shanghai, nearly ten times as much as in Stockholm, where the most significant land cover changewas a 12% urban expansion that mostly replaced agricultural areas. From the landscape metrics results,it appears that fragmentation in both study regions occurred mainly due to the growth of high densitybuilt-up areas in previously more natural/agricultural environments, while the expansion of low densitybuilt-up areas was for the most part in conjunction with pre-existing patches. Urban growth resulted inecosystem service value losses of approximately 445 million US dollars in Shanghai, mostly due to thedecrease in natural coastal wetlands while in Stockholm the value of ecosystem services changed very lit-tle. Total urban growth in Shanghai was 1768 km2and 100 km2in Stockholm. The developed methodologyis considered a straight-forward low-cost globally applicable approach to quantitatively and qualitativelyevaluate urban growth patterns that could help to address spatial, economic and ecological questions inurban and regional planning.

Keyword
Urbanization, Land use/land cover (LULC), Ecosystme Services, Landscape Metrics, Environmental Impact, SVM
National Category
Remote Sensing
Research subject
Geodesy and Geoinformatics
Identifiers
urn:nbn:se:kth:diva-160125 (URN)10.1016/j.jag.2014.12.008 (DOI)000351970100015 ()
Funder
Swedish Research Council Formas
Note

QC 20150519. Updated fråm Manuscript to Article

Available from: 2015-02-16 Created: 2015-02-16 Last updated: 2017-12-04Bibliographically approved

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