Urban Vegetation Quality Assessment Using Vegetation Index and Leaf Area Index from Spot 7 Data with Fuzzy Logic Algorithm

Urban vegetation plays an essential role in the health and comfort of the urban environment. On the other hand, the decrease of urban vegetation is mostly due to land cover change from vegetation to build up the area. Detection of urban vegetation objects is essential for monitoring the distribution and the extent of vegetation in realizing a sustainable urban environment. SPOT 7 satellite image data with high spatial resolution can display objects in urban areas, including vegetation. With this capability, the extraction of vegetation objects can be conducted more accurately. This study aims to assess urban vegetation quality using vegetation index and Leaf Area Index (LAI) from SPOT 7 data. The method proposed in this study was the fuzzy logic on each vegetation index and LAI, which was extended by involving all indexes. The results showed that urban vegetation quality classification could be done using vegetation index NDVI, SR, RDVI, and another index LAI extracted from SPOT 7 data using a fuzzy logic algorithm. Based on these four variables' overlay, the highest quality of vegetation was shown with a fuzzy value of 0.928, and the lowest quality has a fuzzy value of 0.004. The highest quality of vegetation was in paddy fields and mixed garden, while the lowest quality of vegetation was in bare land with grass plantation. Based on the results, the appropriate treatment of urban vegetation in the study area can be determined.