Wetlands ecosystems support a significant percentage of the world’s biodiversity and also provide a number of ecological services, such as carbon sequestration. These fragile ecosystems need to be monitored over time in order to better understand the ecological dynamics and changes within. The study areas are the marshland of the Ostiglia and Busatello marshes. Thus, geographic and climatic aspects have been investigated in order to better explain the dynamics of this ecosystem. The aims of this study were: (i) the evaluation of satellite instruments and methods for monitoring the health state of wetland ecosystems and the impacts of Climate Change; (ii) the investigation of seasonal dynamics of this wetland. The temperature, precipitation and humidity trends have been analyzed from 2016 to 2021. Time series of spectral indices (NDVI, NDMI and NMDI) and backscatter (VV and VH) have been extracted in order to analyze the trends of seasonal variation. To better understand the backscatter variation, the correlation between spectral indices and backscatter have been computed.
SAR and Multispectral Data Contribution to the Monitoring of Wetland Ecosystems Vulnerable to Climate Change
Marco, Dubbini;Michaela, De Giglio;Chiara, Salvatori
2022
Abstract
Wetlands ecosystems support a significant percentage of the world’s biodiversity and also provide a number of ecological services, such as carbon sequestration. These fragile ecosystems need to be monitored over time in order to better understand the ecological dynamics and changes within. The study areas are the marshland of the Ostiglia and Busatello marshes. Thus, geographic and climatic aspects have been investigated in order to better explain the dynamics of this ecosystem. The aims of this study were: (i) the evaluation of satellite instruments and methods for monitoring the health state of wetland ecosystems and the impacts of Climate Change; (ii) the investigation of seasonal dynamics of this wetland. The temperature, precipitation and humidity trends have been analyzed from 2016 to 2021. Time series of spectral indices (NDVI, NDMI and NMDI) and backscatter (VV and VH) have been extracted in order to analyze the trends of seasonal variation. To better understand the backscatter variation, the correlation between spectral indices and backscatter have been computed.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
