Analyzing the December 2013 Metaponto Plain (Southern Italy) Flood Event by Integrating Optical Sensors Satellite Data

Lacava, Teodosio; Ciancia, Emanuele; Faruolo, Mariapia; Pergola, Nicola; Satriano, Valeria; Tramutoli, Valerio

doi:10.3390/hydrology5030043

Cited by 4 publications

(10 citation statements)

References 25 publications

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“…Floods are natural disasters that, due to their clear spatial and spectral markers in different regions of the electromagnetic spectrum, are more easily investigable by means of satellite data [14]. Among the different satellite-based contributions useful for the flood risk management cycle, is the generation of reliable multi-temporal flood maps is fundamental in all the different phases [8,60,61].…”

Section: Discussionmentioning

confidence: 99%

“…In this work, the RST-FLOOD approach, previously applied to AVHRR and MODIS VNIR data, has been fully implemented for the first time on historical series of VIIRS Imagery records for evaluating its capability in detecting inundated area. The adoption of dynamic and local-scale self-adaptive thresholds and the fully independence on any kind of auxiliary/ancillary information are the main RST-FLOOD advantages with respect to traditional techniques [14,23]. Fixed thresholding schemes or ancillary dataset are indeed often used for flooded area detection applications [11,54] as well as for facing issues related to cloud and terrain shadows, representing the main challenges for a fully reliable flood detection [11,54].…”

Section: Discussionmentioning

confidence: 99%

“…The results performance of inundated area identification can indeed largely change depending both on the availability and the accuracy of the used auxiliary/ancillary information [22]. In addition, specific site/local-setting of the investigated scene, as well as seasonal/ meteorological variations of the studied signals, may negatively affect the sensitivity of fixed thresholds schemes [14,22].…”

Section: Discussionmentioning

confidence: 99%

“…Concerning VIIRS Imagery data, in addition to the indexes above defined [14], flooded area can be detected in different single bands and/or exploiting their combination, due to the specific spectral response of water in the VNIR region [6,11,54]. To better highlight such a behaviour within the local-scale conditions, the spectral profile for different signals along the red transect shown in Figure 1, has been investigated ( Figure 6).…”

Section: The Robust Satellite Techniques (Rst) Approachmentioning

confidence: 99%

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On the Potential of RST-FLOOD on Visible Infrared Imaging Radiometer Suite Data for Flooded Areas Detection

et al. 2019

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Timely and continuous information about flood spatiotemporal evolution are fundamental to ensure an effective implementation of the relief and rescue operations in case of inundation events. In this framework, satellite remote sensing may provide a valuable contribution provided that robust data analysis methods are implemented and suitable data, in terms of spatial, spectral and temporal resolutions, are employed. In this paper, the Robust Satellite Techniques (RST) approach, a satellite-based differential approach, already applied at detecting flooded areas (and therefore christened RST-FLOOD) with good results on different polar orbiting optical sensors (i.e., Advanced Very High Resolution Radiometer – AVHRR – and Moderate Resolution Imaging Spectroradiometer – MODIS), has been fully implemented on time series of Suomi National Polar-orbiting Partnership (Suomi-NPP-SNPP) Visible Infrared Imaging Radiometer Suite (VIIRS) data. The flooding event affecting the Metaponto Plain in Basilicata and Puglia regions (southern Italy) in December 2013 was selected as a case study and investigated by analysing five years (only December month) of VIIRS Imagery bands at 375 m spatial resolution. The achieved results clearly indicate the potential of the proposed approach, especially when compared with a satellite-based high resolution map of flooded area, as well as with the official flood hazard map of the area and the outputs of a recent published VIIRS-based method. Both flood extent and dynamics have been recognized with good reliability during the investigated period, with only a residual 11.5% of possible false positives over an inundated area extent of about 73 km2. In addition, a flooded area of about 18 km2 was found outside the hazard map, suggesting it requires updating to better manage flood risk and prevent future damages. Finally, the achieved results indicate that medium-resolution optical data, if analysed with robust methodologies like RST-FLOOD, can be suitable for detecting and monitoring floods also in case of small hydrological basins.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: The Robust Satellite Techniques (Rst) Approachmentioning

confidence: 99%

See 2 more Smart Citations

On the Potential of RST-FLOOD on Visible Infrared Imaging Radiometer Suite Data for Flooded Areas Detection

et al. 2019

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“…Nowadays, the extent of inundated areas and the evolution of water expansion and regression can be effectively monitored using remotely sensed data acquired by aircraft and satellites. In this regard, Lacava et al [30] present a sensor-independent multi-temporal approach called RST-FLOOD, where Robust Satellite Techniques (RST) are applied to detect flooded areas. In particular, the application of the RST-FLOOD methodology for the flood event that affected Basilicata and Puglia regions (southern Italy) in December 2013 is illustrated.…”

Section: Introduction To the Special Issuementioning

confidence: 99%

Advances in Large-Scale Flood Monitoring and Detection

et al. 2018

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The last decades have seen a massive advance in technologies for Earth observation (EO) and environmental monitoring, which provided scientists and engineers with valuable spatial information for studying hydrologic processes. At the same time, the power of computers and newly developed algorithms have grown sharply. Such advances have extended the range of possibilities for hydrologists, who are trying to exploit these potentials the most, updating and re-inventing the way hydrologic and hydraulic analyses are carried out. A variety of research fields have progressed significantly, ranging from the evaluation of water features, to the classification of land-cover, the identification of river morphology, and the monitoring of extreme flood events. The description of flood processes may particularly benefit from the integrated use of recent algorithms and monitoring techniques. In fact, flood exposure and risk over large areas and in scarce data environments have always been challenging topics due to the limited information available on river basin hydrology, basin morphology, land cover, and the resulting model uncertainty. The ability of new tools to carry out intensive analyses over huge datasets allows us to produce flood studies over large extents and with a growing level of detail. The present Special Issue aims to describe the state-of-the-art on flood assessment, monitoring, and management using new algorithms, new measurement systems and EO data. More specifically, we collected a number of contributions dealing with: (1) the impact of climate change on floods; (2) real time flood forecasting systems; (3) applications of EO data for hazard, vulnerability, risk mapping, and post-disaster recovery phase; and (4) development of tools and platforms for assessment and validation of hazard/risk models.

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Multi-Decadal Assessment of Soil Loss in a Mediterranean Region Characterized by Contrasting Local Climates

Samela

Imbrenda

Coluzzi

et al. 2022

Land

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Soil erosion is one of the most widespread soil degradation phenomena worldwide. Mediterranean landscapes, due to some peculiar characteristics, such as fragility of soils, steep slopes, and rainfall distribution during the year, are particularly subject to this phenomenon, with severe and complex issues for agricultural production and biodiversity protection. In this paper, we present a diachronic approach to the analysis of soil loss, which aims to account for climate variability and land cover dynamics by using remote data about rainfall and land cover to guarantee sufficient observational continuity. The study area (Basilicata, Southern Italy) is characterized by different local climates and ecosystems (temperate, Csa and Csb; arid steppic, Bsk; and cold, Dsb and Dsc), and is particularly suited to represent the biogeographical complexity of the Mediterranean Italy. The well-known Revised Universal Soil Loss Equation (RUSLE) was applied by integrating information from remote sensing to carry out decadal assessments (1994, 2004, 2014, and 2021) of the annual soil loss. Changes in the rainfall regime and vegetation cover activity were derived from CHIRPS and Landsat data, respectively, to obtain updated information useful for dynamical studies. For the analyzed region, soil loss shows a slight reduction (albeit always remarkable) over the whole period, and distinct spatial patterns between lowland Bsk and Mediterranean mountain Dsb and Dsc climate areas. The most alarming fact is that most of the study area showed soil erosion rates in 2021 greater than 11 t/ha*y, which is considered by the OECD (Organization for Economic Cooperation and Development) the threshold for identifying severe erosion phenomena. A final comparison with local studies shows, on average, differences of about 5 t ha−1 y−1 (minimum 2.5 and maximum 7) with respect to the local estimates obtained with the RUSLE model. The assessment at a regional scale provided an average 9.5% of soil loss difference for the arable lands and about 10% for all cultivated areas. The spatial-temporal patterns enhance the relevance of using the cover management factor C derived from satellite data rather than land cover maps, as remote observations are able to highlight the heterogeneity in vegetation density within the same vegetation cover class, which is particularly relevant for agricultural areas. For mountain areas, the adoption of a satellite-gridded rainfall dataset allowed the detection of erosion rate fluctuations due to rainfall variability, also in the case of sparse or absent ground pluviometric stations. The use of remote data represents a precious added value to obtain a dynamic picture of the spatial-temporal variability of soil loss and new insights into the sustainability of soil use in a region whose economy is mostly based on agriculture and the exploitation of natural resources.

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Analyzing the December 2013 Metaponto Plain (Southern Italy) Flood Event by Integrating Optical Sensors Satellite Data

Cited by 4 publications

References 25 publications

On the Potential of RST-FLOOD on Visible Infrared Imaging Radiometer Suite Data for Flooded Areas Detection

On the Potential of RST-FLOOD on Visible Infrared Imaging Radiometer Suite Data for Flooded Areas Detection

Advances in Large-Scale Flood Monitoring and Detection

Multi-Decadal Assessment of Soil Loss in a Mediterranean Region Characterized by Contrasting Local Climates

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