Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Using GEOBIA and Vegetation Indices to Assess Small Urban Green Areas in Two Climatic Regions

Version 1 : Received: 26 September 2022 / Approved: 27 September 2022 / Online: 27 September 2022 (03:59:34 CEST)

A peer-reviewed article of this Preprint also exists.

Popa, A.M.; Onose, D.A.; Sandric, I.C.; Dosiadis, E.A.; Petropoulos, G.P.; Gavrilidis, A.A.; Faka, A. Using GEOBIA and Vegetation Indices to Assess Small Urban Green Areas in Two Climatic Regions. Remote Sens. 2022, 14, 4888. Popa, A.M.; Onose, D.A.; Sandric, I.C.; Dosiadis, E.A.; Petropoulos, G.P.; Gavrilidis, A.A.; Faka, A. Using GEOBIA and Vegetation Indices to Assess Small Urban Green Areas in Two Climatic Regions. Remote Sens. 2022, 14, 4888.

Abstract

The importance of small urban green areas has increased in the context of rapid urbanization and densification of the urban tissue. The analysis of these areas through remote sensing has been limited due to the low spatial resolution of freely available satellite images. We propose a timeseries analysis on 3 m resolution Planet images, using GEOBIA and vegetation indices, with the aim of extracting and assessing the quality of small urban green areas in two different climatic and biogeographical regions – temperate (Bucharest, Romania) and mediterranean (Athens, Greece). Our results have shown high accuracy (over 91%) regarding the extraction of small urban green areas in both cities, across all analysed images. The timeseries analysis showed consistency in location for around 55% of the identified surfaces throughout the entire period. The vegetation indices registered higher values in the temperate region, due to the vegetation characteristics and the planning of the two cities. For the same reasons, the increase in vegetation density and quality, as a result of the distance from the city centre and the decrease in the density of built-up areas is more obvious in Athens. The proposed method provides valuable insights in the distribution and quality of small urban green areas at city level and can represent the ground basis for many analyses, currently limited by poor spatial resolution.

Keywords

small urban green areas; timeseries; GEOBIA; NDVI; MSAVI2; Planet

Subject

Social Sciences, Geography, Planning and Development

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