Abstract
The 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 different 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 efficiency 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 data.
Highlights
Increasing urban green area is a valuable adaptation policy to face climate change [1] and to mitigate its effects on human beings [2] while providing access to green areas for an increasing population [3]
Similar effects can be achieved by using mycorrhizal inoculation, whose application in Mediterranean urban areas can overcome stress factors caused by soil conditions and drought episodes combined with high irradiance exposure [16,17]
The main objectives of our study were to (i) demonstrate how a methodology based on soil sensors, atmospheric data, and ground surveys can be implemented to monitor the establishment of a new urban forest and (ii) test the efficiency of the restoration techniques at improving the survival rate of the tree and shrub species selected
Summary
Increasing urban green area is a valuable adaptation policy to face climate change [1] and to mitigate its effects on human beings [2] while providing access to green areas for an increasing population [3]. The recovery of forest cover in arid urban environments requires the implementation of technical solutions to create environmentally favorable conditions while optimizing resources [8]. In this regard, soil conditions play an important role in the framework of urban forestry, especially in Mediterranean semi-arid areas [9]. There is a need to capture the spatial pattern of water-soil dynamics for a better application of engineering solutions [19] Disciplines such as agronomy or geology have already integrated spatially-explicit sensor-based solutions into experimental designs and operational projects [20,21].
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