scholarly journals Construction of nearshore elevation model using open satellite data

Author(s):  
A.E. Hmelnov ◽  
A.S. Gachenko

For the tasks considering changes of water level it is required to have a combined (above water and underwater) elevation model. And the highest accuracy requirements are imposed on the parts of the model, which produce the contour lines in the range of the actual water level changes, while the information about the underwater elevation is usually very scarce and rough. In the article we consider the possibility to obtain this part of the elevation model using open high resolution (10 m/pixel) satellite images corresponding to different water levels. Here we describe the technique, which allows us to obtain the subpixel accuracy of the resulting contour lines. And we consider the problems in the quality of the satellite images that the contour lines reveal, and some ways to deal with the problems.

2020 ◽  
Author(s):  
Robert Sämann ◽  
Thomas Graf ◽  
Insa Neuweiler

<p><span>Early warning systems for floods in urban areas should forecast water levels and damage estimation to protect vulnerable regions. To estimate the danger of a flood for buildings and people, the energy of the flood has to be taken into account additionally to the water level. The energy is related to the flow velocity. For directing rescue workers or trace spreading of contaminants through flooded streets, a high resolution of the water’s energy in space and time is required. Direct numerical run-off calculation is too slow for a flood forecast in time. Therefore a database with pre-calculated events is needed and a method to select the water levels and velocity fields that are similar to a forecasted rain event. </span></p><p><span>We present a method, how to create a real-time forecast based on pre-calculated data. The selection and weighting of the pre-calculated data is based on the precipitation pattern in the flood region. A nearest neighbor approach is applied to find water levels and velocity fields from a database that are similar to the forecasting event. For the ranking of similarity, different new metrics are compared against each other. The quality of the metrics is tested with a new approach of comparing velocity fields on the surface and in the pipe system. Considering both domains is crucial for understanding the complex dynamic flow paths on the surface. An urban catchment of 5 km² with high resolution (~3 m³) triangular surface mesh and connected drainage system is used for a hydrodynamic run-off simulation. The 1D-2D coupled software HYSTEM EXTRAN is used to generate the water levels and velocity fields for strong rainfall events of the past 20 years. More than 900 events with a duration between 15 minutes and 24 hours and return periods between 10 and 100 years were calculated and stored as the “pre-calculated” dataset.</span></p><p><span>For comparing two events, the mean square error is calculated between the precipitation patterns with different approaches to select the start index and number of intervals. This number depends on the hydraulic response time, the temporal resolution and the length of the reference pattern. The quality of the nearest neighbor selection is quantified using the Nash–Sutcliffe model efficiency coefficient of pipe flow and the root mean square error of water level and velocity in significant surface cells. Additionally, the transport paths of artificial contamination spills are compared between the events to show the reproducibility of velocity fields for each metric. </span></p><p><span>Results show that the reaction time and the wetting state of the surface is very important. Single cell values correspond well between a forecasted and a dataset event. However, complex transport paths have a very high variability that is not reproducible with similar events. Further research is required to clarify if this is a result of the random walk approach or of the injection time of the particles. </span></p>


2014 ◽  
Vol 18 (5) ◽  
pp. 2007-2020 ◽  
Author(s):  
F. Baup ◽  
F. Frappart ◽  
J. Maubant

Abstract. This study presents an approach to determining the volume of water in small lakes (<100 ha) by combining satellite altimetry data and high-resolution (HR) images. In spite of the strong interest in monitoring surface water resources on a small scale using radar altimetry and satellite imagery, no information is available about the limits of the remote-sensing technologies for small lakes mainly used for irrigation purposes. The lake being studied is located in the south-west of France and is only used for agricultural irrigation purposes. The altimetry satellite data are provided by an RA-2 sensor onboard Envisat, and the high-resolution images (<10 m) are obtained from optical (Formosat-2) and synthetic aperture radar (SAR) antenna (Terrasar-X and Radarsat-2) satellites. The altimetry data (data are obtained every 35 days) and the HR images (77) have been available since 2003 and 2010, respectively. In situ data (for the water levels and volumes) going back to 2003 have been provided by the manager of the lake. Three independent approaches are developed to estimate the lake volume and its temporal variability. The first two approaches (HRBV and ABV) are empirical and use synchronous ground measurements of the water volume and the satellite data. The results demonstrate that altimetry and imagery can be effectively and accurately used to monitor the temporal variations of the lake (R2ABV = 0.98, RMSEABV = 5%, R2HRBV = 0.90, and RMSEABV = 7.4%), assuming a time-varying triangular shape for the shore slope of the lake (this form is well adapted since it implies a difference inferior to 2% between the theoretical volume of the lake and the one estimated from bathymetry). The third method (AHRBVC) combines altimetry (to measure the lake level) and satellite images (of the lake surface) to estimate the volume changes of the lake and produces the best results (R2AHRBVC = 0.98) of the three methods, demonstrating the potential of future Sentinel and SWOT missions to monitor small lakes and reservoirs for agricultural and irrigation applications.


2013 ◽  
Vol 10 (12) ◽  
pp. 15731-15770 ◽  
Author(s):  
F. Baup ◽  
F. Frappart ◽  
J. Maubant

Abstract. This study presents an approach to determine the volume of water in small lakes (<100 ha) by combining satellite altimetry data and high-resolution (HR) images. The lake being studied is located in the south-west of France and is only used for agricultural irrigation purposes. The altimetry satellite data are provided by RA-2 sensor on board Envisat, and the high-resolution images (<10 m) are obtained from optical (Formosat-2) and synthetic aperture radar (SAR) sensors (Terrasar-X and Radarsat-2) satellites. The altimetry data (data are obtained every 35 days) and the HR images (45) have been available since 2003 and 2010, respectively. In situ data (for the water levels and volumes) going back to 2003 have been provided by the manager of the lake. Three independent approaches are developed to estimate the lake volume and its temporal variability. The first two approaches are empirical and use synchronous ground measurements of the water volume and the satellite data. The results demonstrate that altimetry and imagery can be effectively and accurately used to monitor the temporal variations of the lake (R2altimetry = 0.97, RMSEaltimetry = 5.2%, R2imagery = 0.90, and RMSEimagery = 7.4%). The third method combines altimetry (to measure the lake level) and satellite images (of the lake surface) to estimate the volume changes of the lake and produces the best results (R2 = 0.99) of the three methods, demonstrating the potential of future Sentinel and SWOT missions to monitor small lakes and reservoirs for agricultural and irrigation applications.


PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e8616
Author(s):  
Yueqing Chen ◽  
Sijia Qiao ◽  
Guangxin Zhang ◽  
Y. Jun Xu ◽  
Liwen Chen ◽  
...  

Background Interferometric Synthetic Aperture Radar (InSAR) has become a promising technique for monitoring wetland water levels. However, its capability in monitoring wetland water level changes with Sentine-1 data has not yet been thoroughly investigated. Methods In this study, we produced a multitemporal Sentinel-1 C-band VV-polarized SAR backscatter images and generated a total of 28 interferometric coherence maps for marsh wetlands of China’s Momoge National Nature Reserve to investigate the interferometric coherence level of Sentinel-1 C-VV data as a function of perpendicular and temporal baseline, water depth, and SAR backscattering intensity. We also selected six interferogram pairs acquired within 24 days for quantitative analysis of the accuracy of water level changes monitored by Sentinel-1 InSAR. The accuracy of water level changes determined through the Sentinel-1 InSAR technique was calibrated by the values of six field water level loggers. Results Our study showed that (1) the coherence was mainly dependent on the temporal baseline and was little affected by the perpendicular baseline for Sentinel-1 C-VV data in marsh wetlands; (2) in the early stage of a growing season, a clear negative correlation was found between Sentinel-1 coherence and water depth; (3) there was an almost linear negative correlation between Sentinel-1 C-VV coherence and backscatter for the marsh wetlands; (4) once the coherence exceeds a threshold of 0.3, the stage during the growing season, rather than the coherence, appeared to be the primary factor determining the quality of the interferogram for the marsh wetlands, even though the quality of the interferogram largely depends on the coherence; (5) the results of water level changes from InSAR processing show no agreement with in-situ measurements during most growth stages. Based on the findings, we can conclude that although the interferometric coherence of the Sentinel-1 C-VV data is high enough, the data is generally unsuitable for monitoring water level changes in marsh wetlands of China’s Momoge National Nature Reserve.


Author(s):  
C. M. Bhatt ◽  
G. S. Rao ◽  
B. Patro

Conventional method of identifying areas to be inundated for issuing flood alert require inputs like discharge data, fine resolution digital elevation model (DEM), software for modelling and technically trained manpower to interpret the results meaningfully. Due to poor availability of these inputs, including good network of historical hydrological observations and limitation of time, quick flood early warning becomes a difficult task. Presently, based on the daily river water level and forecasted water level for major river systems in India, flood alerts are provided which are non-spatial in nature and does not help in understanding the inundation (spatial dimension) which may be caused at various water levels. In the present paper a concept for developing a series of flood-inundation map libraries two approaches are adopted one by correlating inundation extent derived from historical satellite data analysis with the corresponding water level recorded by the gauge station and the other simulation of inundation using digital elevation model (DEM's) is demonstrated for a part of Godavari Basin. The approach explained can be one of quick and cost-effective method for building a library of flood inundation extents, which can be utilized during flood disaster for alerting population and taking the relief and rescue operations. This layer can be visualized from a spatial dimension together with other spatial information like administrative boundaries, transport network, land use and land cover, digital elevation data and satellite images for better understanding and visualization of areas to be inundated spatially on free web based earth visualization portals like ISRO's Bhuvan portal (<a href="http://http://bhuvan.nrsc.gov.in" target="_blank">http://bhuvan.nrsc.gov.in</a>). This can help decision makers in taking quick appropriate measures for warning, planning relief and rescue operations for the population to get affected under that river stage.


2020 ◽  
Vol 223 (2) ◽  
pp. 1288-1303
Author(s):  
K Strehlow ◽  
J Gottsmann ◽  
A Rust ◽  
S Hautmann ◽  
B Hemmings

Summary Aquifers are poroelastic bodies that respond to strain by changes in pore pressure. Crustal deformation due to volcanic processes induces pore pressure variations that are mirrored in well water levels. Here, we investigate water level changes in the Belham valley on Montserrat over the course of 2 yr (2004–2006). Using finite element analysis, we simulate crustal deformation due to different volcanic strain sources and the dynamic poroelastic aquifer response. While some additional hydrological drivers cannot be excluded, we suggest that a poroelastic strain response of the aquifer system in the Belham valley is a possible explanation for the observed water level changes. According to our simulations, the shallow Belham aquifer responds to a steadily increasing sediment load due to repeated lahar sedimentation in the valley with rising aquifer pressures. A wholesale dome collapse in May 2006 on the other hand induced dilatational strain and thereby a short-term water level drop in a deeper-seated aquifer, which caused groundwater leakage from the Belham aquifer and thereby induced a delayed water level fall in the wells. The system thus responded to both gradual and rapid transient strain associated with the eruption of Soufrière Hills Volcano (Montserrat). This case study gives field evidence for theoretical predictions on volcanic drivers behind hydrological transients, demonstrating the potential of hydrological data for volcano monitoring. Interrogation of such data can provide valuable constraints on stress evolution in volcanic systems and therefore complement other monitoring systems. The presented models and inferred results are conceptually applicable to volcanic areas worldwide.


2019 ◽  
Vol 11 (20) ◽  
pp. 2389 ◽  
Author(s):  
Deodato Tapete ◽  
Francesca Cigna

Illegal excavations in archaeological heritage sites (namely “looting”) are a global phenomenon. Satellite images are nowadays massively used by archaeologists to systematically document sites affected by looting. In parallel, remote sensing scientists are increasingly developing processing methods with a certain degree of automation to quantify looting using satellite imagery. To capture the state-of-the-art of this growing field of remote sensing, in this work 47 peer-reviewed research publications and grey literature are reviewed, accounting for: (i) the type of satellite data used, i.e., optical and synthetic aperture radar (SAR); (ii) properties of looting features utilized as proxies for damage assessment (e.g., shape, morphology, spectral signature); (iii) image processing workflows; and (iv) rationale for validation. Several scholars studied looting even prior to the conflicts recently affecting the Middle East and North Africa (MENA) region. Regardless of the method used for looting feature identification (either visual/manual, or with the aid of image processing), they preferred very high resolution (VHR) optical imagery, mainly black-and-white panchromatic, or pansharpened multispectral, whereas SAR is being used more recently by specialist image analysts only. Yet the full potential of VHR and high resolution (HR) multispectral information in optical imagery is to be exploited, with limited research studies testing spectral indices. To fill this gap, a range of looted sites across the MENA region are presented in this work, i.e., Lisht, Dashur, and Abusir el Malik (Egypt), and Tell Qarqur, Tell Jifar, Sergiopolis, Apamea, Dura Europos, and Tell Hizareen (Syria). The aim is to highlight: (i) the complementarity of HR multispectral data and VHR SAR with VHR optical imagery, (ii) usefulness of spectral profiles in the visible and near-infrared bands, and (iii) applicability of methods for multi-temporal change detection. Satellite data used for the demonstration include: HR multispectral imagery from the Copernicus Sentinel-2 constellation, VHR X-band SAR data from the COSMO-SkyMed mission, VHR panchromatic and multispectral WorldView-2 imagery, and further VHR optical data acquired by GeoEye-1, IKONOS-2, QuickBird-2, and WorldView-3, available through Google Earth. Commonalities between the different image processing methods are examined, alongside a critical discussion about automation in looting assessment, current lack of common practices in image processing, achievements in managing the uncertainty in looting feature interpretation, and current needs for more dissemination and user uptake. Directions toward sharing and harmonization of methodologies are outlined, and some proposals are made with regard to the aspects that the community working with satellite images should consider, in order to define best practices of satellite-based looting assessment.


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