Change search
ReferencesLink to record
Permanent link

Direct link
Remote Sensing of Urbanization and Environmental Impacts
KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geodesy and Geoinformatics.
2013 (English)Licentiate thesis, monograph (Other academic)
Abstract [en]

The unprecedented growth of urban areas all over the globe is nowadays maybe most apparent in China having undergone rapid urbanization since the late 1970s. The need for new residential, commercial and industrial areas leads to new urban regions challenging sustainable development and the maintenance and creation of a high living standard as well as the preservation of ecological functionality. Therefore, timely and reliable information on land-cover changes and their consequent environmental impacts are needed to support sustainable urban development.The objective of this research is the analysis of land-cover changes, especially the development of urban areas in terms of speed, magnitude and resulting implications for the natural and rural environment using satellite imagery and the quantification of environmental impacts with the concepts of ecosystem services and landscape metrics. The study areas are the cities of Shanghai and Stockholm and the three highly-urbanized Chinese regions Jing-Jin-Ji, the Yangtze River Delta and the Pearl River Delta. The analyses are based on classification of optical satellite imagery (Landsat TM/ETM+ and HJ-1A/B) over the past two decades. The images were first co-registered and mosaicked, whereupon GLCM texture features were generated and tasseled cap transformations performed to improve class separabilities. The mosaics were classified with a pixel-based SVM and a random forest decision tree ensemble classifier. Based on the classification results, two urbanization indices were derived that indicate both the absolute amount of urban land and the speed of urban development. The spatial composition and configuration of the landscape was analysed by landscape metrics. Environmental impacts were quantified by attributing ecosystem service values to the classifications and the observation of value changes over time.

ivThe results from the comparative study between Shanghai and Stockholm show a decrease in all natural land-cover classes and agricultural areas, whereas urban areas increased by approximately 120% in Shanghai, nearly ten times as much as in Stockholm where no significant land-cover changes other than a 12% urban expansion could be observed. From the landscape metrics analysis results, it appears 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. Urban growth resulted in ecosystem service value losses of ca. 445 million US dollars in Shanghai, mostly due to a decrease in natural coastal wetlands. In Stockholm, a 4 million US dollar increase in ecosystem service values could be observed that can be explained by the maintenance and development of urban green spaces. Total urban growth in Shanghai was 1,768 km2 compared to 100 km2 in Stockholm. Regarding the comparative study of urbanization in the three Chinese regions, a total increase in urban land of about 28,000 km2 could be detected with a simultaneous decrease in ecosystem service values corresponding to ca. 18.5 billion Chinese Yuan Renminbi. The speed and relative urban growth in Jing-Jin-Ji was highest, followed by the Yangtze River Delta and the Pearl River Delta. The increase in urban land occurred predominately at the expense of cropland. Wetlands decreased due to land reclamation in all study areas. An increase in landscape complexity in terms of land-cover composition and configuration could be detected. Urban growth in Jing-Jin-Ji contributed most to the decrease in ecosystem service values, closely followed by the Yangtze River Delta and the Pearl River Delta.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2013. , 117 p.
Trita-SOM , ISSN 1653-6126 ; 2013:06
Keyword [en]
Remote Sensing, Classification, Land Use/Land-Cover, Support Vector Machine, Random Forest, Urbanization, Environmental Impact, Landscape Metrics, Ecosystem Services
National Category
Remote Sensing
URN: urn:nbn:se:kth:diva-123500ISBN: 978-91-7501-791-4OAI: diva2:626750
2013-06-11, Sal 4055, Drottning Kristinas väg 30, KTH, Stockholm, 13:00 (English)

QC 20130610

Available from: 2013-06-10 Created: 2013-06-10 Last updated: 2013-06-11Bibliographically approved

Open Access in DiVA

fulltext(9314 kB)4362 downloads
File information
File name FULLTEXT01.pdfFile size 9314 kBChecksum SHA-512
Type fulltextMimetype application/pdf

Search in DiVA

By author/editor
Haas, Jan
By organisation
Geodesy and Geoinformatics
Remote Sensing

Search outside of DiVA

GoogleGoogle Scholar
Total: 4362 downloads
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

Total: 454 hits
ReferencesLink to record
Permanent link

Direct link