Özet
This research aims to compare landscape metrics of two different cities having distinct landscape characteristics by using up-to-date, very high resolution SPOT 6/7 images-derived and thematically extensive urban land cover/use (LCLU) maps produced from object based classification approach. Object based classification method was applied to 1.5 m resolution SPOT images in conjunction with some opensource geoinformation in order to create accurate urban LCLU maps. Landscape metrics were calculated using detailed land cover/use classes and comparisons were conducted for two different city landscapes; one having huge industrialized areas and another with urban sites and archeological city residences which was declared as World Cultural Heritage. Patch Density (PD), Edge Density (ED), Largest Patch Index (LPI), Euclidean Nearest Neighbor Distance Distribution (ENN_MN), Area-Weighted Mean Fractal Dimension Index (FRAC_AM) and Contagion (CONTAG) metrics were calculated for two cities using these land cover/use maps. Analyzes of urban areas with landscape metrics allowed objective evaluations to define the structure of urban areas and representation of differences or similarities in the spatial structure of different urban regions.
| Orijinal dil | İngilizce |
|---|---|
| Sayfa (başlangıç-bitiş) | 711-721 |
| Sayfa sayısı | 11 |
| Dergi | Photogrammetric Engineering and Remote Sensing |
| Hacim | 84 |
| Basın numarası | 11 |
| DOI'lar | |
| Yayın durumu | Yayınlandı - Kas 2018 |
Bibliyografik not
Publisher Copyright:© 2018 American Society for Photogrammetry and Remote Sensing.
Finansman
Abstract already available from regulatory, governmental or commer-This research aims to compare landscape metrics of two dif- cial sources. However, in developing countries, remote sens-ferent cities having distinct landscape characteristics by using ing applications becomes crucial due to the lack of efficient, up-to-date, very high resolution SPOT 6/7 images-derived and periodic and timely geospatial information (Miller and Small, thematically extensive urban land cover/use (LCLU) maps 2003; Sertel and Akay, 2015). New developments in satellite produced from object based classification approach. Object technology with the capability of providing very high spatial based classification method was applied to 1.5 m resolution resolution and advances in image processing methods allow SPOT images in conjunction with some opensource geoinfor- the precise determination of urban and suburban features to mation in order to create accurate urban LCLU maps. Land- characterize urban LCLU resulted in effective usage of these scape metrics were calculated using detailed land cover/use data sets not only for urban environmental studies but also for classes and comparisons were conducted for two different city urban planning purposes (Xian, 2015). landscapes; one having huge industrialized areas and another There have been wide-ranging studies and projects con-with urban sites and archeological city residences which ducted on the creation of LCLU maps from satellite images was declared as World Cultural Heritage. Patch Density (PD), from local to continental scales. There are several initiatives Edge Density (ED), Largest Patch Index (LPI), Euclidean Near- at European level as well; such as Coordination of Informa-est Neighbor Distance Distribution (ENN_MN), Area-Weighted tion on the Environment (CORINE) and Urban Atlas Projects. Mean Fractal Dimension Index (FRAC_AM) and Contagion The CORINE project is part of the Copernicus services coor-(CONTAG) metrics were calculated for two cities using these dinated and managed by the European Commission creating land cover/use maps. Analyzes of urban areas with landscape continuous LCLU maps of EU countries for every six year pe-metrics allowed objective evaluations to define the structure riod and the most recent one is created for 2012. CORINE LCLU of urban areas and representation of differences or similari- maps contain a total of 44 LCLU classes; 11 of these classes ties in the spatial structure of different urban regions. contain artificial surfaces and the minimum mapping unit Delivere(Md MbUy )I nisg 2e5n htaectares with a 1:100 000 scale. Although CORINE IP: 125.17.16.94 On: Tdautea,b 0as5e Misa vre 2ry0 1u9se 0fu3l: 5fo0r: 5co4untry wide planning and differ-Introduction Copyright: American Society for Penhto ctoougnratrmy minetetrry-c aonmdp Rareismonoste o fS leannsdisncgape characteristics, its The main objective of urban sustainability is to carefully descale, thematic and geometric details are not sufficient for ur-sign urban environments having minimal impact on ecosys-ban specific large scale applications. The Urban Atlas Project tems and maintain comfortable life for citizen. Development is part of the “European World Observation Program-Coperni-and implementation of socio-economic and environmental cus” funded by the European Commission with the support of policies that will minimize the impact of cities on local and the European Regional Development Fund (ERDF) and jointly global environment are important for urban sustainability produced by the Member States with the support of the Euro-(Dempsey and Jenks, 2006). Rational and efficient land use pean Environment Agency. Urban Atlas is available for years and management are critical to ensure urban sustainability. 2006 and 2012. 2012 data includes 0.25 ha minimum map-For the planning models to be prepared in this direction, it is ping unit for seventeen different urban related classes and necessary to know the related regions’ past and current land 1 hectare MMU for ten rural classes. For the year 2012 refer-cover and land use information and their spatio-temporal ence year, urban atlas maps of 697 large urban areas and the changes on the basis of urban settlements and resources surrounding area (population more than 100,000) providing (Iyyer, 2009). Remotely sensed data has been widely used for land information were created (Copernicus, n.d). The aims of variety of urban applications, such as mapping and monitor-the Urban Atlas project are to fill the information gap on land ing of urban sprawl and urban growth trends, urban change use in European cities, to produce comparable land use data, detection, urban utility and infrastructure planning, urban to facilitate the creation of more evidence-based policies, to land zoning, urban environment and impact assessment, compare land use models among the major cities in Europe, urban management and modeling, urban hydrology (Iyyer, and thus, to compare cities in Europe and the use of satellite 2009). Need for remote sensing data to obtain information on imagery to cost-effectively create reliable and comparable built environment especially for cities in developed countries high-resolution maps of urban areas (European Environment might not be that significant because detailed information is Agency, 2010). The Methodology of Urban Atlas contains, object based classifications based on high resolution satellite Elif Sertel is with the Civil Engineering Faculty-Geomatics Engineering Division, Istanbul Technical University, ITU Ayazaga Campus 34669 Maslak, Istanbul, Turkey ([email protected]).
| Finansörler |
|---|
| European Commission |
| European Regional Development Fund |
BM SKH
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