Abstract
Mapping and monitoring of the urban green space (UGS) are necessary for improving the quality of urban life. Mapping the UGS is the first step in sustainable urban planning because comprehensive information on vegetation in cities is lacking. Very high- resolution imagery and object-based image analysis (OBIA) offer a viable semi-automatic solution in mapping the UGS in greater detail. In this study, GeoEye image is used to map the spatial distribution of UGS in Kalaburagi, India. Normalised Difference Vegetation Index (NDVI) values are used including fuzzy rule sets in classifying the image in OBIA environment. A new urban green space index (UGSI) is developed to visualize the density of greenness in Kalaburagi city. The analysis is carried out at two levels considering the granularity. The first Meso-level analysis is at the ward level of Kalaburagi city. The second micro-level analysis is at 200 m × 200 m grid zones level. The UGS extraction results are highly accurate (> 90%). The results are crucial to urban planners as the results are critical to the Kalaburagi city where 22 administrative wards out of 55in Kalaburagi have less than 10% of UGS and 25 out of 55 wards have less than 9 m2 Per Capita Green Space (PCGS). Priority has to be given to these areas to build a healthy city through green planning.
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