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Spatio-temporal analysis of prodelta dynamics by means of new satellite generation: the case of Po river by Landsat-8 data
- Source :
- ITC journal 66 (2018): 210–225. doi:10.1016/j.jag.2017.11.012, info:cnr-pdr/source/autori:Manzo, Ciro; Federica, Braga; Luca, Zaggia; Ernesto, Brando Vittorio; Claudia, Giardino; Mariano, Bresciani; Cristiana, Bassani/titolo:Spatio-temporal analysis of prodelta dynamics by means of new satellite generation: the case of Po river by Landsat-8 data/doi:10.1016%2Fj.jag.2017.11.012/rivista:ITC journal/anno:2018/pagina_da:210/pagina_a:225/intervallo_pagine:210–225/volume:66
- Publication Year :
- 2018
- Publisher :
- Elsevier BV, 2018.
-
Abstract
- This paper describes a procedure to perform spatio-temporal analysis of river plume dispersion in prodelta areas by multi-temporal Landsat-8-derived products for identifying zones sensitive to water discharge and for providing geostatistical patterns of turbidity linked to different meteo-marine forcings. In particular, we characterized the temporal and spatial variability of turbidity and sea surface temperature (SST) in the Po River prodelta (Northern Adriatic Sea, Italy) during the period 2013–2016. To perform this analysis, a two-pronged processing methodology was implemented and the resulting outputs were analysed through a series of statistical tools. A pixel-based spatial correlation analysis was carried out by comparing temporal curves of turbidity and SST hypercubes with in situ time series of wind speed and water discharge, providing correlation coefficient maps. A geostatistical analysis was performed to determine the spatial dependency of the turbidity datasets per each satellite image, providing maps of correlation and variograms. The results show a linear correlation between water discharge and turbidity variations in the points more affected by the buoyant plumes and along the southern coast of Po River delta. Better inverse correlation was found between turbidity and SST during floods rather than other periods. The correlation maps of wind speed with turbidity show different spatial patterns depending on local or basin-scale wind effects. Variogram maps identify different spatial anisotropy structures of turbidity in response to ambient conditions (i.e. strong Bora or Scirocco winds, floods). Since the implemented processing methodology is based on open source software and free satellite data, it represents a promising tool for the monitoring of maritime ecosystems and to address water quality analyses and the investigations of sediment dynamics in estuarine and coastal waters.
- Subjects :
- 010504 meteorology & atmospheric sciences
Correlation coefficient
0211 other engineering and technologies
02 engineering and technology
Management, Monitoring, Policy and Law
01 natural sciences
Turbidity
Spatial pattern
Computers in Earth Sciences
Variogram
021101 geological & geomatics engineering
0105 earth and related environmental sciences
Earth-Surface Processes
Global and Planetary Change
geography
River delta
geography.geographical_feature_category
Sediment dispersion
SST
Sea surface temperature
Climatology
Prodelta area
Spatial ecology
Environmental science
Common spatial pattern
Spatial variability
Subjects
Details
- ISSN :
- 15698432
- Volume :
- 66
- Database :
- OpenAIRE
- Journal :
- International Journal of Applied Earth Observation and Geoinformation
- Accession number :
- edsair.doi.dedup.....1c7ba003a3b06c460b818369821bd1a5
- Full Text :
- https://doi.org/10.1016/j.jag.2017.11.012