"Rocky Water 93/10": in-situ measurements supported by satellite remote sensing and high resolution ocean modelling in near real time

2002 ◽  
Author(s):  
T. Wahl ◽  
J. Glattetre ◽  
T. Jenserud ◽  
A. Skoelv ◽  
E.A. Martinsen ◽  
...  
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Real Time ◽  
Satellite Remote Sensing ◽  
In Situ Measurements ◽  
Ocean Modelling

MARINE-EO project: Monitoring and forecast of eutrophication around fish farms, a Maliakos Gulf case (Eastern Mediterranean).

2021 ◽  
Author(s):  
Amandine Declerck ◽  
Matthias Delpey ◽  
Thibaut Voirand ◽  
Ioanna Varkitzi
Keyword(s):  
Water Quality ◽  
High Resolution ◽  
Real Time ◽  
Chlorophyll A ◽  
Satellite Observation ◽  
Risk Level ◽  
Fish Farms ◽  
Ocean Modelling ◽  
Monitoring And Forecasting

<p>Keywords: eutrophication; high resolution ocean modeling ; Chla satellite data ; biogeochemistry</p><p>Maliakos Gulf corresponds to mesotrophic waters that can reach eutrophic conditions and are occasionally subject to Harmful Algal Blooms (HAB) (Varkitzi et al. 2018). At the same time, it is an important fish farming and aquaculture production area. A large issue is thus related to the monitoring and forecasting of the risk of occurrence of algae blooms in the Gulf. For this purpose, the present study couples predictions from a high-resolution numerical ocean model with satellite observation to improve the monitoring and anticipation of threats for the local fish farms induced by occasional eutrophication.</p><p>This solution is developed in the frame of the MARINE-EO project (https://marine-eo.eu/). It combines satellite observation with high-resolution ocean modelling to provide detailed information as a support to fish farms management and operations. It is implemented in an operational platform, which provides continuous information in real time as well as short term predictions. The deployed solution uses CMEMS physical products as an input data and offers to refine this solution in order to provide a local information on site using a downscaling strategy. High resolution satellite products and ocean modelling allow to include the impact of local coastal processes on currents and water quality parameters to provide a proper monitoring and forecasting solution at the scale of a specific fish farm.</p><p>To model specific eutrophication processes, a NPZD (Nutrients-Phytoplankton-Zooplankton-Detritus) biogeochemical model is used. Included in the MOHID Water modelling system, the water quality module (Mateus, 2006) considering 18 properties: nutrients and organic matter (nitrogen, phosphorus and silica biogeochemical cycles), oxygen and organisms (phytoplankton and zooplankton) was deployed in the western Aegean Sea. The simulated chlorophyll a concentrations are used to compute a risk level for the eutrophication occurrence. To complete this indicator, another risk level was based on the eutrophication variation following Primpas et al. (2010) formulation. In addition to model forecasts, ocean color observations from the Sentinel-2 MSI and Landsat-8 OLI sensors are used to provide high resolution chlorophyll a concentrations maps in case of bloom events. The processing chain uses the sixth version of the Quasi-Analytical Algorithm initially developed by Lee et al. (2002) and an empirical relation based on a database built using the HydroLight software to compute chlorophyll a concentration.</p><p>Two past eutrophication events monitored in situ (Varkitzi et al. 2018) were studied to assess the accuracy of the developed tool. Although few in situ data were available on environmental input (as rivers flow and nutrient concentrations), it was possible using statistics to reproduce qualitatively these blooms. Finally, an operational demonstration was conducted during 2 months of the 2020 autumn season, to showcase real time monitoring and predictive perspectives.</p>

scholarly journals Evaluation of RapidEye-3 Satellite Data for Assessing Water Turbidity of Lake Borabey

Proceedings ◽  
2019 ◽  
Vol 48 (1) ◽  
pp. 14
Author(s):  
Gordana Kaplan ◽  
Zehra Yigit Avdan ◽  
Serdar Goncu ◽  
Ugur Avdan
Keyword(s):  
Remote Sensing ◽  
Water Quality ◽  
High Resolution ◽  
Remote Sensing Data ◽  
Quality Parameters ◽  
In Situ Measurements ◽  
Water Quality Parameters ◽  
Water Turbidity ◽  
Sensing Data

In water resources management, remote sensing data and techniques are essential in watershed characterization and monitoring, especially when no data are available. Water quality is usually assessed through in-situ measurements that require high cost and time. Water quality parameters help in decision making regarding the further use of water-based on its quality. Turbidity is an important water quality parameter and an indicator of water pollution. In the past few decades, remote sensing has been widely used in water quality research. In this study, we compare turbidity parameters retrieved from a high-resolution image with in-situ measurements collected from Borabey Lake, Turkey. Here, the use of RapidEye-3 images (5 m-resolution) allows for detailed assessment of spatio-temporal evaluation of turbidity, through the normalized difference turbidity index (NDTI). The turbidity results were then compared with data from 21 in-situ measurements collected in the same period. The actual water turbidity measurements showed high correlation with the estimated NDTI mean values with an R2 of 0.84. The research findings support the use of remote sensing data of RadipEye-3 to estimate water quality parameters in small water areas. For future studies, we recommend investigating different water quality parameters using high-resolution remote sensing data.

scholarly journals RFim: A Real-Time Inundation Extent Model for Large Floodplains Based on Remote Sensing Big Data and Water Level Observations

2019 ◽  
Vol 11 (13) ◽  
pp. 1585 ◽  
Author(s):  
Zeqiang Chen ◽  
Jin Luo ◽  
Nengcheng Chen ◽  
Ren Xu ◽  
Gaoyun Shen
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Water Level ◽  
Real Time ◽  
Remote Sensing Images ◽  
The Real ◽  
Remote Sensing Imagery ◽  
Inundation Simulation ◽  
Inundation Extent

The real-time flood inundation extent plays an important role in flood disaster preparation and reduction. To date, many approaches have been developed for determining the flood extent, such as hydrodynamic models, digital elevation model-based (DEM-based) methods, and remote sensing methods. However, hydrodynamic methods are time consuming when applied to large floodplains, high-resolution DEMs are not always available, and remote sensing imagery cannot be used alone to predict inundation. In this article, a new model for the highly accurate and rapid simulation of floodplains, called “RFim” (real-time inundation model), is proposed to simulate the real-time flooded area. The model combines remote sensing images with in situ data to find the relationship between the inundation extent and water level. The new approach takes advantage of remote sensing images, which have wide spatial coverage and high resolution, and in situ observations, which have continuous temporal coverage and are easily accessible. This approach has been applied in the study area of East Dongting Lake, representing a large floodplain, for inundation simulation at a 30 m resolution. Compared with the submerged extent from observations, the accuracy of the simulation could be more than 90% (the lowest is 93%, and the highest is 96%). Hence, the approach proposed in this study is reliable for predicting the flood extent. Moreover, an inundation simulation for all of 2013 was performed with daily water level observation data. With an increasing number of Earth observation satellites operating in space and high-resolution mappers deployed on satellites, it will be much easier to acquire large quantities of images with very high resolutions. Therefore, the use of RFim to perform inundation simulations with high accuracy and high spatial resolutions in the future is promising because the simulation model is built on remote sensing imagery and gauging station data.

scholarly journals In situ measurements and satellite remote sensing of case 2 waters: first results from the Curonian Lagoon

Oceanologia ◽  
2010 ◽  
Vol 52 (2) ◽  
pp. 197-210 ◽  
Author(s):  
Claudia Giardino ◽  
Mariano Bresciani ◽  
Renata Pilkaitytė ◽  
Marco Bartoli ◽  
Artūras Razinkovas
Keyword(s):  
Remote Sensing ◽  
Satellite Remote Sensing ◽  
In Situ Measurements ◽  
Curonian Lagoon ◽  
First Results

scholarly journals Satellite remote sensing of a low-salinity water plume in the East China Sea

2008 ◽  
Vol 26 (7) ◽  
pp. 2019-2035 ◽  
Author(s):  
Y. H. Ahn ◽  
P. Shanmugam ◽  
J. E. Moon ◽  
J. H. Ryu
Keyword(s):  
Remote Sensing ◽  
Satellite Remote Sensing ◽  
Atmospheric Correction ◽  
In Situ Measurements ◽  
The East China Sea ◽  
Water Types ◽  
Low Salinity ◽  
Low Salinity Water ◽  
Salinity Water

Abstract. With the aim to map and monitor a low-salinity water (LSW) plume in the East China Sea (ECS), we developed more robust and proper regional algorithms from large in-situ measurements of apparent and inherent optical properties (i.e. remote sensing reflectance, Rrs, and absorption coefficient of coloured dissolved organic matter, aCDOM) determined in ECS and neighboring waters. Using the above data sets, we derived the following relationships between visible Rrs and absorption by CDOM, i.e. Rrs (412)/Rrs (555) vs. aCDOM (400) (m−1) and aCDOM (412) (m−1) with a correlation coefficient R2 0.67 greater than those noted for Rrs (443)/Rrs (555) and Rrs (490)/Rrs (555) vs. aCDOM (400) (m−1) and aCDOM (412) (m−1). Determination of aCDOM (m−1) at 400 nm and 412 nm is particularly necessary to describe its absorption as a function of wavelength λ using a single exponential model in which the spectral slope S as a proxy for CDOM composition is estimated by the ratio of aCDOM at 412 nm and 400 nm and the reference is explained simply by aCDOM at 412 nm. In order to derive salinity from the absorption coefficient of CDOM, in-situ measurements of salinity made in a wide range of water types from dense oceanic to light estuarine/coastal systems were used along with in-situ measurements of aCDOM at 400 nm, 412 nm, 443 nm and 490 nm. The CDOM absorption at 400 nm was better inversely correlated (R2=0.86) with salinity than at 412 nm, 443 nm and 490 nm (R2=0.85–0.66), and this correlation corresponded best with an exponential (R2=0.98) rather than a linear function of salinity measured in a variety of water types from this and other regions. Validation against a discrete in-situ data set showed that empirical algorithms derived from the above relationships could be successfully applied to satellite data over the range of water types for which they have been developed. Thus, we applied these algorithms to a series of SeaWiFS images for the derivation of CDOM and salinity in the context of operational mapping and monitoring of the springtime evolution of LSW plume in the ECS. The results were very encouraging and showed interesting features in surface CDOM and salinity fields in the vicinity of the Yangtze River estuary and its offshore domains, when a regional atmospheric correction (SSMM) was employed instead of the standard (global) SeaWiFS algorithm (SAC) which revealed large errors around the edges of clouds/aerosols while masking out the nearshore areas. Nevertheless, there was good consistency between these two atmospheric correction algorithms over the relatively clear regions with a mean difference of 0.009 in aCDOM (400) (m−1) and 0.096 in salinity (psu). This study suggests the possible utilization of satellite remote sensing to assess CDOM and salinity and thus provides great potential in advancing our knowledge of the shelf-slope evolution and migration of the LSW plume properties in the ECS.

In Situ Observations and Satellite Remote Sensing in SEACOOS: Program Development and Lessons Learned

2008 ◽  
Vol 42 (3) ◽  
pp. 41-54 ◽  
Author(s):  
James R. Nelson ◽  
Robert H. Weisberg
Keyword(s):  
Remote Sensing ◽  
Real Time ◽  
Satellite Remote Sensing ◽  
Coastal Ocean ◽  
Lessons Learned ◽  
Test Bed ◽  
Data Logging ◽  
Mobile Platforms ◽  
Ocean Observing

In situ observing and satellite remote sensing components of the Southeast Atlantic Coastal Ocean Observing System (SEACOOS) implemented from 2002 through 2006 are reviewed and "lessons learned" from the operation of these systems are summarized. The in situ observing program built upon several efforts initiated at academic institutions in the southeast U.S. prior to 2002. The partnership and observing capacity were expanded as the SEACOOS program developed. Sustained near real-time in situ observations were obtained from buoys, offshore towers, pier and shore stations, and mobile platforms (ships, gliders, drifters) using several communications options. The SEACOOS observing program also included several test-bed studies, and a pilot program in regional satellite remote sensing utilized established capabilities at partner institutions to deliver satellite products in near real-time to SEACOOS. Many of the SEACOOS observing activities leveraged personnel and infrastructure resources at partner institutions and support from complementary research projects. The SEACOOS experience provides a number of pragmatic (operational) "lessons learned" that are relevant to the future operation of a Regional Coastal Ocean Observing System (RCOOS). Adequate support of experienced personnel is critical to the efficient, sustained operation of a real-time observing network. Also required are sufficient inventories of spare components, appropriate transportation options to accommodate both routine and unscheduled maintenance, robust communications with sufficient bandwidth and back-up options, and data logging on deployment platforms to minimize gaps in the time-series. RCOOS planning should include mechanisms to ensure effective communications on operational matters among technical personnel within and across regions.

Estimations for Percentage of Impervious Area by the Use of Satellite Remote Sensing Imagery

1994 ◽  
Vol 29 (1-2) ◽  
pp. 135-144 ◽  
Author(s):  
C. Deguchi ◽  
S. Sugio
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Satellite Imagery ◽  
Satellite Remote Sensing ◽  
Aerial Photographs ◽  
Estimation Errors ◽  
Remote Sensing Imagery ◽  
Impervious Area ◽  
Urbanized Areas

This study aims to evaluate the applicability of satellite imagery in estimating the percentage of impervious area in urbanized areas. Two methods of estimation are proposed and applied to a small urbanized watershed in Japan. The area is considered under two different cases of subdivision; i.e., 14 zones and 17 zones. The satellite imageries of LANDSAT-MSS (Multi-Spectral Scanner) in 1984, MOS-MESSR(Multi-spectral Electronic Self-Scanning Radiometer) in 1988 and SPOT-HRV(High Resolution Visible) in 1988 are classified. The percentage of imperviousness in 17 zones is estimated by using these classification results. These values are compared with the ones obtained from the aerial photographs. The percent imperviousness derived from the imagery agrees well with those derived from aerial photographs. The estimation errors evaluated are less than 10%, the same as those obtained from aerial photographs.

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