EGU25-15942, updated on 15 Mar 2025
https://doi.org/10.5194/egusphere-egu25-15942
EGU General Assembly 2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Analyzing variability and possible trends in NDVI for urban water management: A remote-sensing approach for long term monitoring of green infrastructure
Franziska Sarah Kudaya, Albert König, and Daniela Fuchs-Hanusch
Franziska Sarah Kudaya et al.
  • Graz University of Technology, Institute of Urban Water Management and Landscape Water Engineering, Austria (franziska.kudaya@tugraz.at)

The changing climate creates challenges for green spaces everywhere. A special case is presented by the urban tree, which has several harsh environmental conditions to deal with, i.e. compacted soil, polluted rainwater, etc. Climate adaptation strategies for cities involve the urban tree as a nature-based solution due to its high potential for heat island mitigation and reducing surface runoff. Managing water resources efficiently is receiving more attention with measures including alternative resources for irrigation or incorporating more drought-resistant species, while the effects of changing macro- and micro-climatic conditions on urban trees are only now becoming subject of scientific scrutiny. 

There are several important indicators for evaluating a tree’s living conditions and its water demand at a certain location. One such indicator is the start and end of the growing season. As temperatures rise, plants are seen to have shorter dormancy periods, resulting in earlier flowering and longer growing seasons, increasing both water demand and susceptibility to damage.  

In this study, we compare the growing cycles of urban trees across varying locations in the city of Graz during a period of over 20 years. Tree specific information is taken from the city’s tree register which gives important information about species, age and location of urban trees. Growing cycles are evaluated using a remote sensing approach where NDVI-timeseries are then calculated for the selected areas using openly available satellite imagery to identify changes in dormancy and evaluate a possible trend. The influence of parameters such as location, micro-climate, species and date of planting are investigated using statistical analysis. The generated knowledge is expected to help in the prediction of future urban green irrigation demand and choice of tree species.

How to cite: Kudaya, F. S., König, A., and Fuchs-Hanusch, D.: Analyzing variability and possible trends in NDVI for urban water management: A remote-sensing approach for long term monitoring of green infrastructure, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15942, https://doi.org/10.5194/egusphere-egu25-15942, 2025.