64th ISI World Statistics Congress - Ottawa, Canada

64th ISI World Statistics Congress - Ottawa, Canada

Near-real time monitoring of urban green spaces through remote sensing data


Marian Necula



64th ISI World Statistics Congress - Ottawa, Canada

Format: CPS Abstract

Keywords: official-statistics,, remote-sensing, urban, urban-green-spaces,

Session: CPS 84 - Environmental statistics I

Thursday 20 July 8:30 a.m. - 9:40 a.m. (Canada/Eastern)


Urban green spaces are of increasingly significance for city planning, mitigation of climate change and pollution effects. International and national organizations are stressing the importance of preserving and expanding urban green spaces in order to ensure a city sustainability. The UN includes urban green spaces in the Sustainable Development Goals 2030 Agenda.
Official statistics is trusted with providing relevant, timely and cost efficient statistics.
The advent of freely available remote sensing data sources provides strong opportunities to implement new meaningful statistical products, which satisfy the aforementioned quality criteria. Land use and land cover statistics based on remote sensing data are considered to be a low hanging fruit, while several projects carried out by national statistical offices and other agencies are underway to develop new statistics based on remote sensing data.
The paper presents the implementation and results from several methods, pixel-based and object-based image analysis, used to estimate the absolute value in squared kilometers and percentage wise of green area surfaces at a nation wide scale, for 40+ Romanian cities between 2016-2022. Through a combination of several remote sensing data sources(from optical multispectral and synthetic aperture radar sensors), we provide evidence towards the feasibility of using remote sensing data in producing relevant statistics. By combining the two types of sensors data we overcome the disadvantages and inherent risks associated with a single data source, and are able to disseminate the new statistics near real time within an interval of 5 days.