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• W4387224596 abstract "In most urban environments, loss of natural vegetation, the reduction of open spaces, and the rapid invasive transformation of the natural environment into impervious have happened. These changes can lead to a decline in life quality and in an increase in various economic, social, ecological, and infrastructural problems and risks. The complexity of the urban environment at various scales requires the application of high spatial and temporal resolution data in the process of urban planning. The main goal of this paper was to derive specific landscape metrics characteristic for urban areas based on WV-3 very-high-resolution imagery and the GEOBIA method. A supervised machine learning technique support vector machine (SVM) was used as a classification algorithm. The derived land-cover model is evaluated using the confusion matrix and related accuracy metrics: user accuracy (UA), producer’s accuracy (PA), overall accuracy (OA), and Kappa coefficient. Land-cover classification accuracy assessment resulted in moderate overall accuracy while aggregation of classes depending on the physical characteristics of the material increased OA. For landscape diversity and area metric analysis, aggregated classes were used in combination with user-defined polygons. In the city of Split, there is no absolute homogeneity (SHDI = 0) within any of the hexagons. Inner parts of the city have a higher SHDI than the outskirts but impervious surfaces are the dominant material. Urban planning indicators (UPIs), have been derived for statistical circles (SC) of Split settlement in Croatia. Vegetation indicators (TCR - tree cover ratio, LCR - lawn cover ratio, GCR - green cover ratio) and indicators of urbanization (SCR - street cover ratio, BCR - building cover ratio, IMR - impervious surface ratio) were derived from the derived land cover model. The UPIs values at the studied level are the reflection of the historical spatial-functional development of the Split settlement. These types of UPIs can be used at the neighborhood level of urban planning and analysis of different issues in an urban environment." @default.
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• W4387224596 date "2023-01-01" @default.
• W4387224596 modified "2023-10-01" @default.
• W4387224596 title "WorldView-3 Imagery and GEOBIA Method for the Urban Land Use Pattern Analysis: Case Study City of Split, Croatia" @default.
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• W4387224596 doi "https://doi.org/10.1007/978-3-031-44112-7_4" @default.
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