Papers by Salvatore Manfreda
The development of continuous river turbidity monitoring systems is essential, since it is a crit... more The development of continuous river turbidity monitoring systems is essential, since it is a critical water quality metric linked to the presence of organic and inorganic suspended matter. Current monitoring practices are mainly limited by low spatial and temporal resolution, and costs. This results in the huge challenge to provide extensive and timely water quality monitoring at global scale. In this work, we propose an image analysis procedure for river turbidity assessment using different camera systems (i.e., fixed trap camera, camera on board of an Unmanned Aerial Vehicle, and a multispectral camera). We explored multiple types of camera installation setup during a river turbidity event artificially recreated on site. The outcomes prove that processed digital camera data can properly represent the turbidity trends. Specifically, the experimental activities revealed that single band values were the most reliable proxy for turbidity monitoring in short terms, better than band ratios and indexes. The best camera positioning, orientation and lens sensitivity, as well as daily and seasonal changes in lightning and river flow conditions, may affect the accuracy of the results. The reliability of this application will be tested under different hydrological and environmental conditions during our next field experiments. The final goal of the work is the implementation of this camera system to support existing monitoring techniques with early warning strategies and help in finding innovative solutions to water resources management.
Water, Jun 21, 2013
Society is facing growing environmental problems that require new research efforts to understand ... more Society is facing growing environmental problems that require new research efforts to understand the way ecosystems operate and survive, and their mutual relationships with the hydrologic cycle. In this respect, ecohydrology suggests a renewed interdisciplinary approach that aims to provide a better comprehension of the effects of climatic changes on terrestrial ecosystems. With this aim, a coupled hydrological/ecological model is adopted to describe simultaneously vegetation pattern evolution and hydrological water budget at the basin scale using as test site the Upper Rio Salado basin (Sevilleta, NM, USA). The hydrological analyses have been carried out using a recently formulated framework for the water balance at the daily level linked with a spatial model for the description of the spatial organization of vegetation. This enables quantitatively assessing the effects on soil water availability on future climatic scenarios. Results highlighted that the relationship between climatic forcing (water availability) and vegetation patterns is strongly non-linear. This implies, under some specific conditions which depend on the ecosystem characteristics, small changes in climatic conditions may produce significant transformation of the vegetation patterns.
Ecohydrology, Jun 1, 2010
The papers in this issue represent a selection of the presentations made at the session entitled ... more The papers in this issue represent a selection of the presentations made at the session entitled “Climate‐soil and vegetation interactions in ecological–hydrological processes” of the European Geophysical Union General Assembly. The special issue “Coupled Ecological–Hydrological Processes” focuses on different aspects of Ecohydrology that can be summarized in the following topics: soil moisture dynamics, soil–plant interactions, vegetation modelling and effects of climate change on natural ecosystems. Copyright © 2010 John Wiley & Sons, Ltd.
Water, 2013
Society is facing growing environmental problems that require new research efforts to understand ... more Society is facing growing environmental problems that require new research efforts to understand the way ecosystems operate and survive, and their mutual relationships with the hydrologic cycle. In this respect, ecohydrology suggests a renewed interdisciplinary approach that aims to provide a better comprehension of the effects of climatic changes on terrestrial ecosystems. With this aim, a coupled hydrological/ecological model is adopted to describe simultaneously vegetation pattern evolution and hydrological water budget at the basin scale using as test site the Upper Rio Salado basin (Sevilleta, NM, USA). The hydrological analyses have been carried out using a recently formulated framework for the water balance at the daily level linked with a spatial model for the description of the spatial organization of vegetation. This enables quantitatively assessing the effects on soil water availability on future climatic scenarios. Results highlighted that the relationship between climatic forcing (water availability) and vegetation patterns is strongly non-linear. This implies, under some specific conditions which depend on the ecosystem characteristics, small changes in climatic conditions may produce significant transformation of the vegetation patterns.
EGUsphere, 2024
The development of continuous river turbidity monitoring systems is essential, since it is a crit... more The development of continuous river turbidity monitoring systems is essential, since it is a critical water quality metric linked to the presence of organic and inorganic suspended matter. Current monitoring practices are mainly limited by low spatial and temporal resolution, and costs. This results in the huge challenge to provide extensive and timely water quality monitoring at global scale. In this work, we propose an image analysis procedure for river turbidity assessment using different camera systems (i.e., fixed trap camera, camera on board of an Unmanned Aerial Vehicle, and a multispectral camera). We explored multiple types of camera installation setup during a river turbidity event artificially re-created on site. The outcomes prove that processed digital camera data can properly represent the turbidity trends. Specifically, the experimental activities revealed that single band values were the most reliable proxy for turbidity monitoring in short terms, better than band ratios and indexes. The best camera positioning, orientation and lens sensitivity, as well as daily and seasonal changes in lightning and river flow conditions, may affect the accuracy of the results. The reliability of this application will be tested under different hydrological and environmental conditions during our next field experiments. The final goal of the work is the implementation of this camera system to support existing monitoring techniques with early warning strategies and help in finding innovative solutions to water resources management.
<p>Optical satellite sensors represent a reference for Earth imaging applications, ... more <p>Optical satellite sensors represent a reference for Earth imaging applications, including land monitoring and flood management, directly allowing the visual interpretation of acquired scenes or the exploitation of surfaces’ spectral signatures. An extensive literature exists that proves the ability of multispectral satellite sensors in mapping flooded areas and water bodies (Albertini et al., 2022). Several multispectral indices have been developed for water segmentation in different contexts of varying degrees of landscape complexity. Simultaneously, the advancements in Machine Learning (ML) methods led to a proliferation of supervised and unsupervised algorithms applied to classification problems in the field of flood hazard and risk mapping. In the present study, four random forest (RF) models were used in combination with three spectral indices, namely the Modified Normalized Difference Water Index (MNDWI), the Normalized Difference Moisture Index (NDMI) and the Red and Short Wave Infra-Red (RSWIR) index, to map the extent of the flood event occurred along the Sesia River (Vercelli, Italy) in October 2020. A Sentinel-2 scene was acquired soon after the flooding event and spectral bands at 20m resolution were used in the analyses. The performances of the RF methods implemented with the use of the mentioned spectral indices were evaluated and compared using as reference map the delineation product delivered by the Rapid Mapping service of the Copernicus Emergency Management Service (CEMS). Results revealed some very interesting findings regarding the performances of the examined methods, which can become a well-established operational technique. Last but not least, the validation framework itself underlined the added value of Sentinel-2 and the Copernicus platform as a robust, rapid and cost-effective solution in flood mapping.</p> <p><strong>Keywords:</strong> <em>floods mapping, spectral indices, machine learning, Sentinel-2, Italy</em></p> <p><em>References:</em></p> <p>Albertini, C.; Gioia, A.; Iacobellis, V.; Manfreda, S. Detection of Surface Water and Floods with Multispectral Satellites. Remote Sens., 14, 6005, 2022. (doi: https://doi.org/10.3390/rs14236005).</p>
<p>The use of multispectral satellite imagery for flood mapping and river m... more <p>The use of multispectral satellite imagery for flood mapping and river monitoring is a fast and cost-effective method that can benefit from the growing availability of medium-high-resolution and free remote sensing data. Since the 1970s, several satellites are observing the Earth surface supporting water detection studies and flood management. In addition, many techniques exploiting different spectral indices have been proposed in the literature. Considering the high number of available sensors and their differences in spectral and spatial characteristics, this work aims to examine the applications of satellite remote sensing for water extent delineation and flood monitoring. Focusing on freely available optical imagery, this study presents a discussion of the most used satellites for flood and wetland mapping to highlight trends of current research studies. Furthermore, performances of the most common spectral indices for water segmentation are analysed first qualitatively, based on evidence obtained from a significant literature review, and then quantitatively by comparing different water-related index algorithms applied to a real case study. Performance assessment is carried out to provide an overview of the best sensor-specific spectral index in detecting surface water and expressed in terms of overall accuracy (OA) and Kappa coefficient.</p>
<p>Optical satellite sensors represent a reference for Earth imaging applications, ... more <p>Optical satellite sensors represent a reference for Earth imaging applications, including land monitoring and flood management, directly allowing the visual interpretation of acquired scenes or the exploitation of surfaces’ spectral signatures. An extensive literature exists that proves the ability of multispectral satellite sensors in mapping flooded areas and water bodies (Albertini et al., 2022). Several multispectral indices have been developed for water segmentation in different contexts of varying degrees of landscape complexity. Simultaneously, the advancements in Machine Learning (ML) methods led to a proliferation of supervised and unsupervised algorithms applied to classification problems in the field of flood hazard and risk mapping. In the present study, four random forest (RF) models were used in combination with three spectral indices, namely the Modified Normalized Difference Water Index (MNDWI), the Normalized Difference Moisture Index (NDMI) and the Red and Short Wave Infra-Red (RSWIR) index, to map the extent of the flood event occurred along the Sesia River (Vercelli, Italy) in October 2020. A Sentinel-2 scene was acquired soon after the flooding event and spectral bands at 20m resolution were used in the analyses. The performances of the RF methods implemented with the use of the mentioned spectral indices were evaluated and compared using as reference map the delineation product delivered by the Rapid Mapping service of the Copernicus Emergency Management Service (CEMS). Results revealed some very interesting findings regarding the performances of the examined methods, which can become a well-established operational technique. Last but not least, the validation framework itself underlined the added value of Sentinel-2 and the Copernicus platform as a robust, rapid and cost-effective solution in flood mapping.</p> <p><strong>Keywords:</strong> <em>floods mapping, spectral indices, machine learning, Sentinel-2, Italy</em></p> <p><em>References:</em></p> <p>Albertini, C.; Gioia, A.; Iacobellis, V.; Manfreda, S. Detection of Surface Water and Floods with Multispectral Satellites. Remote Sens., 14, 6005, 2022. (doi: https://doi.org/10.3390/rs14236005).</p>
Unmanned Aerial Systems for Monitoring Soil, Vegetation, and Riverine Environments
EGU General Assembly Conference Abstracts, Apr 1, 2018
Flood Monitoring through Remote Sensing, 2017
Knowing the location and the extent of areas exposed to floods is the most basic information need... more Knowing the location and the extent of areas exposed to floods is the most basic information needed for planning flood management strategies. Unfortunately, a complete identification of these areas is still lacking in many countries. Recent studies have highlighted that a significant amount of information regarding the inundation process is already contained in the structure and morphology of a river basin. Therefore, several geomorphic approaches have been proposed for the delineation of areas exposed to flood inundation using DEMs. Such DEM-based approaches represent a useful tool, characterized by low cost and simple data requirements, for a preliminary identification of the flood-prone areas or to extend flood hazard mapping over large areas. Moreover, geomorphic information may be used as external constraint in remote-sensing algorithms for the identification of inundated areas during or after a flood event.
XXXIV Convegno Nazionale di idraulica e Costruzioni Idrauliche, 2014
EGU General Assembly Conference Abstracts, Apr 1, 2019
<p>Soil moisture (SM) content is a crucial parameter for an extensive range... more <p>Soil moisture (SM) content is a crucial parameter for an extensive range of fields (e.g., hydrology cycle, smart agriculture, environmental risk management, climate system) as it regulates the water balance, land surface energy, and the carbon cycle. However, the non-homogeneous horizontal and vertical distribution of water content in the soil complicates SM evaluation. The integration of in-situ measurements with those remotely acquired or produced by models may help in overcoming such a problem.</p><p>Focusing on satellite data, it is worth noting that the growing availability of sensors (active or passive) working in the microwave spectral region has increased the capability to have SM information on a regional scale with a level of accuracy depending on the selected data, the characteristics of the study area as well as the metric considered for their evaluation.  </p><p>This study aims to compare the accuracy of several freely available microwave-based SM satellite products with in-situ measurements distributed, after quality control and harmonization, by the International Soil Moisture Network (ISMN) for several stations located in the European (EU) Ecoregions for rivers and lakes (WFD 2000/60/CE) in the time frame 2015-2020.</p><p>The satellite products investigated are based on the acquisition by: i) the National Aeronautics and Space Administration (NASA) Soil Moisture Active Passive (SMAP) mission, ii) the European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) mission, iii) the Advanced Scatterometer (ASCAT) aboard of MetOp satellites and iv) the radar onboard ESA’s SENTINEL-1 platforms. In particular we have used processed the following SM products: the SMAPL4 V5 (3-hourly and 9 km of spatial resolution) is based on the assimilation of SMAP (operated in L-band ) observations into a customized version of the NASA Goddard Earth Observing System Version 5 (GEOS-5) land data assimilation system (LDAS); the SMOS-IC V2.0 is the second version of a physically-based algorithm applied to SMOS retrievals operating in L-Band; the H115 and H116 SM products from the ASCAT backscatter observations provided on a fixed Earth grid (12.5 km sampling) in time series format. Finally, the SSM1km -CGLS V retrieved by Sentinel-1 radar images have been also considered (available only for the European continent every 1.5-4 days at spatial resolution of 1km).</p><p>Satellite SM retrievals performances are evaluated against ground-based measurements in terms of Bias, Root Mean Square Error (RMSE), unbiased RMSE, and Pearson correlation (considering both original observations and anomalies). On average, SMAP and SMOS-IC highlight the best performance.</p><p>The proposed inter-comparison offers both guidelines for choosing among available satellite products and insights on SM retrieval products and versions. As the EU Ecoregions outline is based on a large scale, they enclose areas affected by several climate change impacts (such as drought, changes in relative sea level, salinity, etc.). Thus, the outcomes can be used to develop novel satellite-based integrated methods for modelling the hydrologic response to climate change.</p>
IDRA 2008 - 31° Convegno Nazionale di Idraulica e Costruzioni Idrauliche, 2008
EGU General Assembly Conference Abstracts, Apr 1, 2019
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Papers by Salvatore Manfreda