Critical analysis of urban vegetation mapping by satellite multispectral and airborne hyperspectral imagery

Abstract

The monitoring and management of urban vegetation is an important issue nowadays due to the multiple benefits of vegetation for people well-being and for maintaining the balance of ecosystem. In that context, the following study explore to what extent remote sensing imagery could be used to detect and to characterize urban vegetation. Two types of imagery were tested which are low-resolution satellite (i.e. Sentinel 2 and Landsat 8 OLI) and high resolution airborne (i.e. Rikola hyperspectral sensor), the study assessed the detectability of vegetation species over Kaunas city (Lithuania) for different seasonal acquisitions. Satellite imagery showed accurate detection of 3 coarse classes of vegetation with overall accuracies (O.A.) superior to 90%, and airborne hyperspectral imagery showed decent detection of 13 fine classes of vegetation with O.A. of up to 73%.