Satellie Monitoring of Urban Growth and Indicator-based Assessment of Environmental Impact

As of 2018, 55% of the world population resides in urban areas. This proportion is projected to increase to 68% by 2050 (United Nations 2018). The Stockholm region is no exception to this urbanizing trend: the population of Stockholm City has risen by 28% since the year 2000. One of the major consequences of urbanization is the transformation of land cover from rural/natural environments to impervious surfaces that support diverse forms of human activity. These transformations impact local geology, climate, hydrology, flora and fauna and human-life supporting ecosystem services in the region where they occur. Mapping and analysis of land-cover change in urban regions and monitoring 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 urbanization and analyze its environmental impact in and around selected major cities in North America, Europe and Asia by evaluating change in relevant environmental indicators, from local to regional scales. The urban regions examined are the Greater Toronto Area in Canada, Stockholm City, region and County in Sweden and Shanghai in China. The analyses are based on classifications of optical satellite imagery at medium to high spatial resolutions (i.e, Landsat TM/ETM+, SPOT 1/5, Sentinel-2A MSI and QuickBird-2/WorldView-2) between 1985 and 2018. Various classification techniques (maximum likelihood under urban/rural masks, object-based image analysis with rule-based or support vector machine classifiers) were used with combinations of spectral, shape and textural input features to obtain high accuracy classifications. Environmental indicators such as landscape metrics, urbanization indices, buffer/edge/proximity analysis, ecosystem service valuation and provision bundles as well as habitat connectivity were calculated based on the classifications and used to estimate environmental impact of urbanization.The results reveal urban growth and environmental impact to varying degrees in each of the study sites. Urban areas in the GTA grew by nearly 40% between 1985 and 2005. There, change in landscape metrics and urban compactness measures indicated that low-density built-up areas increased significantly, mainly at the expense of agricultural areas. Urban land cover increasingly surrounded the majority of environmentally significant areas during the examined time-period, furthering their isolation from other natural areas. The study comparing Shanghai and Stockholm County between 1990 and 2010 revealed that urban areas increased ten times as much in Shanghaiivas they did in Stockholm, at 120% and 12% respectively. 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 mostly in conjunction with pre-existing patches. The growth in urban areas resulted in ecosystem service value losses of approximately 445 million USD in Shanghai, largely due to the decrease in natural coastal wetlands, while in Stockholm the value of ecosystem services changed very little. The remotely sensed data for these studies had the same resolution (30 m) at roughly the same study area extent, which allowed cross-site comparison of regional urbanization and environmental change trends.Analysis of classifications of SPOT data at 20/10 m resolution indicated urban areas in the greater Stockholm metropolitan area increased by 10% between 1986 and 2006. The landscape metrics indicated that natural areas became more isolated or shrank whereas new small urban patches appeared. Large forested areas in the northeast dropped the most in terms of environmental impact ranking, while the most improved analysis units were close to central Stockholm. Land-cover change analysis in Stockholm County between 2005 and 2015 using Sentinel-2 and SPOT-5 data at 10 m resolution indicated that urban areas increased by 15% and non-urban land cover decreased by 4%. This data’s higher spatial resolution combined with the county study area extent allowed for analysis of regional ecosystem services as well as localized impacts on green infrastructure. In terms of ecosystem services, changes in proximity of forest and low-density built-up areas were the main cause of lowered provision of temperature regulation, air purification and noise reduction. Urban areas near nature reserves increased 16%, with examples of their construction along reserve boundaries. Urban expansion overlapped the deciduous ecological corridor network and green wedge/core areas to a small but increasing degree, often in close proximity to weak but important green links in the landscape. The results from the urban land-cover change analysis based on high-resolution (1 m) data over Stockholm City between 2003 and 2018 revealed that the most significant change occurred through the expansion of the transport network, paved surfaces and construction areas, which increased by 12%, mainly at the expense of grass fields and coniferous forest. Examination of urban growth within ecologically significant green infrastructure indicated that most land area was lost in ecological dispersal zones while the highest percent change was within habitat for species of conservation concern (14%). The high-resolution data made it possible to perform connectivity analysis of the habitat network for the European crested tit, representing small coniferous forest-dependent bird species in Stockholm. Habitat network analysis in both years revealed that overall probability of connectivity decreased slightly through patch fragmentation and shrinkage mainly caused by road expansion at the outskirts of the city.vThis research demonstrates the utility of urban and environmental indicators combined with remote sensing data to assess the spatio-temporal dynamics of urbanization and its environmental impact in different urban regions. Landscape-metric based bundles were effective for monitoring ecosystem service provision in a moderately urbanizing region. Habitat network analysis based on high-resolution urban land-cover classifications, which has not often been undertaken in previous research, provided informative results. A complementary dual-level analysis approach worked well in several studies. Appropriate indicators at the landscape level yielded an estimation of overall impacts on ecosystem value or service provision for the whole region. More specific indicator analysis at a local level pertaining to green infrastructure highlighted impacted ecological areas as localized manifestations of the regional trends. In addition, comparison of classified remotely sensed urban land-cover data with administrative boundaries and significant green infrastructure can reveal transboundary “hotspots” where environmental impact occurs and where further investigation and coordinated conservation or restorative management efforts may be needed. The combination of study results pertaining to Stockholm allowed comparison of classifications of differing spatial resolutions over the same spatial extent, highlighting advantages and challenges in satellite-based urban land-cover mapping for estimation of environmental impact.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.