Environmental monitoring is aimed to measure biological, chemical, and physical parameters that characterize the environmental components. Recently, smart environmental monitoring has gained much attention from the technical and scientific community as it is recognized as a crucial tool for gaining insight into the state of the environment when the protection of biodiversity and ecosystems must be pursued. Indeed, it is one of the best means to understand the dynamics that develop and any changes induced by anthropic activities upon the various environmental components/factors. This paper is aimed to describe the architecture of the smart environmental monitoring system to be installed within the frame of the project BEST (Addressing joint Agro and Aqua-Biodiversity pressures Enhancing SuSTainable Rural Development) funded by the INTERREG VA Greece-Italy 2014/2020 Program, as well as the data analysis needed to synthesize the collected data. Particular attention is paid to the criteria behind the scene: the selection of the locations of monitoring stations, as well as the identification of the instrumentation and type of sensors. The use of low-cost sensors while keeping the smart features of the system management (i.e. the minimization of the role of human presence at the sensing stations) is also investigated. The analysis of the evolutionary dynamics of the coasts, starting from a robust definition of the initial state based on previous studies and new analyses and monitoring activities, has been firstly carried out to characterize the areas and to inform the monitoring strategy. The latter is aimed to get a real picture of biodiversity (i.e. habitats and species) and to relate its spatial and temporal evolution to environmental parameters. Then, measurement of physical parameters (e.g. air temperature, air and soil humidity, atmospheric pressure, wind direction and speed, precipitation, etc) has been foreseen.

Biodiversity Smart Monitoring Informed by Historical Analysis of Coastal Evolution

MALCANGIO D.
;
BRUNO M. F.;MOLFETTA M. G.;PRATOLA L.;
2022-01-01

Abstract

Environmental monitoring is aimed to measure biological, chemical, and physical parameters that characterize the environmental components. Recently, smart environmental monitoring has gained much attention from the technical and scientific community as it is recognized as a crucial tool for gaining insight into the state of the environment when the protection of biodiversity and ecosystems must be pursued. Indeed, it is one of the best means to understand the dynamics that develop and any changes induced by anthropic activities upon the various environmental components/factors. This paper is aimed to describe the architecture of the smart environmental monitoring system to be installed within the frame of the project BEST (Addressing joint Agro and Aqua-Biodiversity pressures Enhancing SuSTainable Rural Development) funded by the INTERREG VA Greece-Italy 2014/2020 Program, as well as the data analysis needed to synthesize the collected data. Particular attention is paid to the criteria behind the scene: the selection of the locations of monitoring stations, as well as the identification of the instrumentation and type of sensors. The use of low-cost sensors while keeping the smart features of the system management (i.e. the minimization of the role of human presence at the sensing stations) is also investigated. The analysis of the evolutionary dynamics of the coasts, starting from a robust definition of the initial state based on previous studies and new analyses and monitoring activities, has been firstly carried out to characterize the areas and to inform the monitoring strategy. The latter is aimed to get a real picture of biodiversity (i.e. habitats and species) and to relate its spatial and temporal evolution to environmental parameters. Then, measurement of physical parameters (e.g. air temperature, air and soil humidity, atmospheric pressure, wind direction and speed, precipitation, etc) has been foreseen.
2022
Monitoring of Mediterranean Coastal Areas: Problems and Measurement Techniques
979-12-215-0030-1
979-12-215-0031-8
Firenze University Press
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11589/242260
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