Paper
6 August 2018 Integrated remote sensing for urban forest changes monitoring
Dan M. Savastru, Maria A. Zoran, Roxana S. Savastru, Ionel R. Popa
Author Affiliations +
Proceedings Volume 10773, Sixth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2018); 107730O (2018) https://doi.org/10.1117/12.2324960
Event: Sixth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2018), 2018, Paphos, Cyprus
Abstract
Drivers of global climate change and the increased frequency of extreme climate events may affect urban and periurban forest ecosystems more rapidly than natural forest ecosystems. Multi stressors of urban forest ecosystems include alterations in forest soils and to the diversity and composition of forest ecosystem, as well as higher temperatures during heat waves periods and increasing carbon dioxide content due to high traffic issue. Global conservation targets and management practices of urban forest ecosystems in Romania requires adequate novel monitoring methodology for monitoring the dynamics changing status. Ground-based measurements are valuable tools with limited spatial footprints. Multispectral and multitemporal satellite remote sensing data allow detailed information on forest structure and can deliver ecologically relevant, long-term datasets suitable of vegetation phenology for analyzing changes in periurban and urban forest ecosystem areas, structure and function at temporal and spatial scales relevant to forest dynamics monitoring. The aim of this paper was to evaluate and characterize forest changes for selected test area Cernica –Branesti in Ilfov county located in the Eastern part of Bucharest metropolitan region, Romania, where the climate and anthropogenic stressors endanger natural and economical values of forest environment. Based on time-series Landsat 5 TM, 7 ETM+, 8 OLI/TIRS, MODIS Terra/Aqua and Sentinel 2A satellite data have been investigated urban forest land cover and forest biophysical parameters (LST, NDVI/EVI and LAI) changes over 2000-2016 period of time. Accuracy of image processing results (spectral classification) was confirmed through in-situ spectroradiometrical analysis of reflectance spectra with portable GER 2600 spectroradiometer.
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Dan M. Savastru, Maria A. Zoran, Roxana S. Savastru, and Ionel R. Popa "Integrated remote sensing for urban forest changes monitoring", Proc. SPIE 10773, Sixth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2018), 107730O (6 August 2018); https://doi.org/10.1117/12.2324960
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KEYWORDS
Vegetation

Climatology

Climate change

Satellites

Remote sensing

Ecosystems

MODIS

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