1 research outputs found
Monitoring water-soil dynamics and tree survival using soil sensors under a big data approach
ArticleThe high importance of green urban planning to ensure access to green areas requires
modern and multi-source decision-support tools. The integration of remote sensing data and sensor
developments can contribute to the improvement of decision-making in urban forestry. This study
proposes a novel big data-based methodology that combines real-time information from soil sensors
and climate data to monitor the establishment of a new urban forest in semi-arid conditions. Water-soil
dynamics and their implication in tree survival were analyzed considering the application of di erent
treatment restoration techniques oriented to facilitate the recovery of tree and shrub vegetation in
the degraded area. The synchronized data-capturing scheme made it possible to evaluate hourly,
daily, and seasonal changes in soil-water dynamics. The spatial variation of soil-water dynamics
was captured by the sensors and it highly contributed to the explanation of the observed ground
measurements on tree survival. The methodology showed how the e ciency of treatments varied
depending on species selection and across the experimental design. The use of retainers for improving
soil moisture content and adjusting tree-watering needs was, on average, the most successful
restoration technique. The results and the applied calibration of the sensor technology highlighted the
random behavior of water-soil dynamics despite the small-scale scope of the experiment. The results
showed the potential of this methodology to assess watering needs and adjust watering resources to
the vegetation status using real-time atmospheric and soil datainfo:eu-repo/semantics/publishedVersio