Mr. Adrian C. Penache Profile

Adrian C. Penache

at Rheinische Friedrich-Wilhelms-Univ Bonn

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Proceedings Article | 21 September 2023 Paper

Assessment of climate and anthropogenic impacts on the urban forest through derived MODIS satellite biophysical variables

Maria Zoran, Roxana Savastru, Dan Savastru, Marina Tautan, Adrian Penache

Proceedings Volume 12786, 127861D (2023) https://doi.org/10.1117/12.2680584

KEYWORDS: Vegetation, Climatology, Climate change, Land cover, MODIS, Satellites, Environmental sensing, Remote sensing, Landsat, Ecosystems

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Urban/periurban forest, sensitive to climatic factors with different vulnerability thresholds according to the species, amplitude, and rate of climatic stressors plays a critical function in the urban microclimate, mitigating air pollution. Use of urban forest-derived satellite variables is essential for understanding its spatiotemporal changes. To address this issue, we applied time series analysis of MODIS Terra, Landsat TM/ETM+/OLI, and Sentinel-2 data, to assess spatiotemporal changes of the periurban forest Cernica-Branesti system, located in the Eastern part of Bucharest city in Romania, from the perspective of vegetation phenology and its relation with climate changes and extreme climate events during 2002- 2022 period. To evaluate the impacts of climate and anthropogenic stressors on the forest properties, a set of biophysical variables have been estimated and several classifications of forest vegetation over the tested areas have been done. Time series of MODIS satellite-derived Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI), Land Surface Temperature (LST), Leaf Area Index (LAI), and Evapotranspiration (ET), together in-situ climate variables were analyzed through anomaly detection techniques, and correlations between them were computed. Temperature, rainfall and solar irradiance were significantly correlated with land-cover classes. Annual change detection rates across the investigated forest area over the study period were estimated at 0.82 % per annum in the range of 0.47% (2002) to 0.93% (2022). This study found that vegetation indices NDVI/EVI in Cernica-Branesti periurban forest are inversely correlated with LST during summer season and positively correlated with LST during autumn, winter and spring seasons. Also, NDVI/EVI are positively correlated with LAI and ET during entire investigated period.

Proceedings Article | 21 September 2023 Paper

Exploring with time-series satellite data of multiple stressors effects on urban/periurban vegetation

Maria Zoran, Roxana Savastru, Dan Savastru, Marina Tautan, Adrian Penache

Proceedings Volume 12786, 127861E (2023) https://doi.org/10.1117/12.2680577

KEYWORDS: Vegetation, Land cover, Climatology, Satellites, MODIS, Climate change, Landsat, Environmental sensing, Spatial resolution, Remote sensing

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Urban vegetation and its carbon storage capacity are critical factors for terrestrial carbon cycling and global Sustainable Development Goals (SDGs). Scientific research for a better managing of urban green land cover is an essential issue of the sustainable urban development initiative promoted by the EU governments. Owing to a crucial role that urban vegetation performs in an urban ecosystem, being effective in mitigating the air pollution and urban heat island effect by canopy shade and evapotranspiration, studying the vegetation dynamics in terms of its derived satellite biogeophysical variables becomes inevitable in the context of climate-smart city planning and design. However, in order to explain the urban-rural gradient in vegetation greenness trends and its responses to climate and antropogenic drivers of land-cover changes this study used time-series of derived satellite data (normalized difference vegetation index-NDVI, enhanced vegetation index- EVI, land surface temperature- LST, leaf area index LAI, and fraction of photosynthetically active radiation absorbed by vegetation- FPAR). Satellite datasets of MODIS Terra, and Landsat TM/ETM+ have been used for urban vegetation analysis over 2002-2022 period of Bucharest metropolitan area in Romania. It was found that the average decrease in vegetation land cover was 0.1 to 0.3. The correlation analyses revealed that, at the pixel-scale, LST possessed a strong positive correlation with NDVI, EVI, FPAR and LAI during the entire investigated period. Only during summer period NDNI/EVI are inversely correlated with LST (r= -0.67; p<0.01) The spatio-temporal pattern of urban/periurban vegetation dynamics trends and their association with other atmospheric, biological, and soil indicators need to be studied with different satellite sensors and resolutions over the long-term periods of time.

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