engleski

Analysis of vegetation indices of urban vegetation in Zagreb (Croatia)

Copernicus is a European Union programme designed to provide a service in delivering free, openly accessible data about the Earth’s surface through satellite and in-situ observations. On the other hand, Landsat represents the world's longest standing continuously acquired collection of space-based, moderate-resolution, land remote sensing data for those working in agriculture, geology, forestry, regional planning, education, mapping, and global change research. Although the images of these satellite systems are characterised by coarse resolution, they can be a good source of information and data to provide better observation of certain objects or phenomena of interest to experts and help them in decision-making. This paper presents an analysis of the vegetation indices of urban vegetation in the city of Zagreb, Croatia, during 2017, calculated using Sentinel 2 and Landsat 8 bands. The information and data obtained as the results of interpreting and processing Sentinel 2 and Landsat 8 satellite systems images can be used by experts in forestry and urban planning as a support in making decisions on urban vegetation management. The results obtained were analysed and interpreted. The interpretation of the results was made visually and statistically, and then presented by means of statistical parameters (correlation, regression). Some channels of the Sentinel 2 satellite system have better surface resolution than all the multispectral channels of the Landsat 8 satellite system. However, the Landsat 8 satellite system channels have better surface resolution than some Sentinel 2 satellite system channels. In both cases, a surface resolution is 10 m and higher. So it is not possible to precisely identify certain objects and phenomena of interest in the field, but only to detect them with a certain level of confidence. Therefore, processing that included the channels of both systems was performed.

NDVI ; SAVI ; Sentinel 2 ; Landsat 8 ; urban vegetation ; correlation

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