TY - GEN
T1 - Assessment of evapotranspiration from urban vegetation across space and time
T2 - 10th International Workshop on the Analysis of Multitemporal Remote Sensing Images, MultiTemp 2019
AU - Vulova, Stenka
AU - Kuhlemann, Lena Marie
AU - Tetzlaff, Doerthe
AU - Soulsby, Christopher
AU - Kleinschmit, Birgit
N1 - ACKNOWLEDGMENT
This study is based in the framework of the Urban Water Interfaces Research Training Group, funded by the German Research Foundation (DFG). We are grateful to the Chair of Climatology at TU Berlin, the Berlin Senate Department for Urban Development and Housing, USGS, and DWD for data provision. We would also like to thank Dr. Tanya Doody for advice on sampling design.
PY - 2019/8/1
Y1 - 2019/8/1
N2 - Evapotranspiration (ET) is a crucial component of urban water and energy regimes, yet our understanding of the role of vegetation in the urban water cycle is still poor. In order to assess the diurnal and seasonal variability of ET from urban vegetation types, an interdisciplinary sampling campaign integrating remote sensing and field-based methods is currently underway at a study site in Berlin, Germany. The sampling is being conducted from spring to winter 2019 in order to characterize the seasonality in hydroclimatic drivers and phenological effects on ET. Three main vegetation types (urban grassland, trees, and shrubs) are sampled. Drone flights with multispectral and thermal cameras are being undertaken. Leaf Area Index and soil moisture are being measured, at monthly and 15-minute resolution, respectively. Using LI-6800, the diurnal and seasonal variation of gas exchange and stomatal conductance is being measured. ET estimates from drone data will be derived using algorithms, such as the 'Triangle Method' [1] and 3T model [2] and validated with field-based ET estimates. Eddy flux data will be analyzed to validate modelled ET and provide hydroclimatic data. Sap flow monitoring will quantify tree transpiration. In the first stage of this study, a time series of ET across seasonal and diurnal scales of a single year will be generated for the local study area. Then, the field-validated UAV data will be combined with satellite data to upscale ET spatially and temporally to provide multi-year estimates of ET for the entire urban area (Berlin). This study will provide an enhanced understanding of the spatio-Temporal variability of ET of urban vegetation, which will be essential for urban planning in the context of climate change.
AB - Evapotranspiration (ET) is a crucial component of urban water and energy regimes, yet our understanding of the role of vegetation in the urban water cycle is still poor. In order to assess the diurnal and seasonal variability of ET from urban vegetation types, an interdisciplinary sampling campaign integrating remote sensing and field-based methods is currently underway at a study site in Berlin, Germany. The sampling is being conducted from spring to winter 2019 in order to characterize the seasonality in hydroclimatic drivers and phenological effects on ET. Three main vegetation types (urban grassland, trees, and shrubs) are sampled. Drone flights with multispectral and thermal cameras are being undertaken. Leaf Area Index and soil moisture are being measured, at monthly and 15-minute resolution, respectively. Using LI-6800, the diurnal and seasonal variation of gas exchange and stomatal conductance is being measured. ET estimates from drone data will be derived using algorithms, such as the 'Triangle Method' [1] and 3T model [2] and validated with field-based ET estimates. Eddy flux data will be analyzed to validate modelled ET and provide hydroclimatic data. Sap flow monitoring will quantify tree transpiration. In the first stage of this study, a time series of ET across seasonal and diurnal scales of a single year will be generated for the local study area. Then, the field-validated UAV data will be combined with satellite data to upscale ET spatially and temporally to provide multi-year estimates of ET for the entire urban area (Berlin). This study will provide an enhanced understanding of the spatio-Temporal variability of ET of urban vegetation, which will be essential for urban planning in the context of climate change.
KW - heat fluxes
KW - remote sensing
KW - soil-plant-Atmosphere interface
KW - UAV
KW - upscaling
KW - urban water cycle
UR - http://www.scopus.com/inward/record.url?scp=85074272738&partnerID=8YFLogxK
U2 - 10.1109/Multi-Temp.2019.8866903
DO - 10.1109/Multi-Temp.2019.8866903
M3 - Published conference contribution
SN - 978-1-7281-4616-4
T3 - 2019 10th International Workshop on the Analysis of Multitemporal Remote Sensing Images, MultiTemp 2019
BT - 2019 10th International Workshop on the Analysis of Multitemporal Remote Sensing Images, MultiTemp 2019
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 5 August 2019 through 7 August 2019
ER -
