Defining a retracking manifold within a radargram stack to improve satellite altimetric water level over coastal seas: A feasibility study

2020 ◽  
Author(s):  
Nico Sneeuw ◽  
Omid Elmi ◽  
Maximilian Eitel ◽  
Mohammad Tourian
Keyword(s):  
Water Level ◽  
Wadden Sea ◽  
Tide Gauge ◽  
Inland Waters ◽  
Coastal Zones ◽  
New Approach ◽  
3D Data ◽  
Waveform Retracking ◽  
Spatio Temporal ◽  
Processing Steps

<p>Single-waveform retracking for satellite altimetry applications over coastal zones has reached its limits, obtaining decimeter-level accuracy. The existing retracking methods find a retracker offset in a waveform by analyzing the variation in backscattered power along the bin coordinate. This makes the retracking procedure strongly dependent on noise in backscattered power. Moreover, the success of such methods is only guaranteed for certain waveform types requiring cumbersome pre-processing steps including waveform classification. </p><p>With the launch of the operational Sentinel-3 series of the European Copernicus programme, the algorithms to obtain highly precise water level estimates over inland waters and coastal seas need to become more robust, efficient and fit for automated use. Therefore, the main objective of this study is to demonstrate the potential of developing a next-level retracking algorithm and, consequently, improve altimetric water level determination over coastal regions. To this end, neighboring waveforms are collected into a (single-pass) radargram and, then, such radargrams are stacked over time. These so-called (multi-pass) radargram stacks contain, unlike single waveforms, the full information on spatio-temporal variation of backscattered power over water surfaces.</p><p>The radargram stack eases the recognition of patterns like retracking gate, shoreline, tides, etc. Instead of a retracking gate as a point in the 1D waveform, in a 3D radargram stack a surface referred to as retracking manifold is to be determined.</p><p>The potential of our new approach will be demonstrated using Sentinel 3B data, pass number 655, over the Cuxhaven tide gauge station at the Wadden Sea.</p><p>The idea of waveform retracking by analyzing its spatio-temporal behavior in a 3D data structure opens new pathways for achieving robust and more accurate water level estimates from operational missions, e.g. Sentinel 3, and from future missions, e.g. SWOT, over inland waters and coastal seas.</p>

scholarly journals DAHITI – an innovative approach for estimating water level time series over inland waters using multi-mission satellite altimetry

2015 ◽  
Vol 19 (10) ◽  
pp. 4345-4364 ◽  
Author(s):  
C. Schwatke ◽  
D. Dettmering ◽  
W. Bosch ◽  
F. Seitz
Keyword(s):  
Time Series ◽  
Water Level ◽  
Satellite Altimetry ◽  
Water Levels ◽  
Altimeter Data ◽  
Inland Waters ◽  
New Approach ◽  
Inland Water ◽  
Rivers And Lakes

Abstract. Satellite altimetry has been designed for sea level monitoring over open ocean areas. However, for some years, this technology has also been used to retrieve water levels from reservoirs, wetlands and in general any inland water body, although the radar altimetry technique has been especially applied to rivers and lakes. In this paper, a new approach for the estimation of inland water level time series is described. It is used for the computation of time series of rivers and lakes available through the web service "Database for Hydrological Time Series over Inland Waters" (DAHITI). The new method is based on an extended outlier rejection and a Kalman filter approach incorporating cross-calibrated multi-mission altimeter data from Envisat, ERS-2, Jason-1, Jason-2, TOPEX/Poseidon, and SARAL/AltiKa, including their uncertainties. The paper presents water level time series for a variety of lakes and rivers in North and South America featuring different characteristics such as shape, lake extent, river width, and data coverage. A comprehensive validation is performed by comparisons with in situ gauge data and results from external inland altimeter databases. The new approach yields rms differences with respect to in situ data between 4 and 36 cm for lakes and 8 and 114 cm for rivers. For most study cases, more accurate height information than from other available altimeter databases can be achieved.

scholarly journals A New Approach for Approximate Solution of ADE: Physical-Based Modeling of Carriers in Doping Region

Mathematics ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 458
Author(s):  
Leobardo Hernandez-Gonzalez ◽  
Jazmin Ramirez-Hernandez ◽  
Oswaldo Ulises Juarez-Sandoval ◽  
Miguel Angel Olivares-Robles ◽  
Ramon Blanco Sanchez ◽  
...  
Keyword(s):  
Differential Equation ◽  
Approximate Solution ◽  
Analytic Solution ◽  
Order Differential Equation ◽  
Electric Circuit ◽  
New Approach ◽  
In Doping ◽  
Electric Behavior ◽  
Spatio Temporal ◽  
Physical Phenomena

The electric behavior in semiconductor devices is the result of the electric carriers’ injection and evacuation in the low doping region, N-. The carrier’s dynamic is determined by the ambipolar diffusion equation (ADE), which involves the main physical phenomena in the low doping region. The ADE does not have a direct analytic solution since it is a spatio-temporal second-order differential equation. The numerical solution is the most used, but is inadequate to be integrated into commercial electric circuit simulators. In this paper, an empiric approximation is proposed as the solution of the ADE. The proposed solution was validated using the final equations that were implemented in a simulator; the results were compared with the experimental results in each phase, obtaining a similarity in the current waveforms. Finally, an advantage of the proposed methodology is that the final expressions obtained can be easily implemented in commercial simulators.

scholarly journals Spectral Complexity of Hyperspectral Images: A New Approach for Mangrove Classification

2021 ◽  
Vol 13 (13) ◽  
pp. 2604
Author(s):  
Patrick Osei Darko ◽  
Margaret Kalacska ◽  
J. Pablo Arroyo-Mora ◽  
Matthew E. Fagan
Keyword(s):  
Statistical Physics ◽  
Near Infrared ◽  
Information Gain ◽  
Hyperspectral Imagery ◽  
Full Range ◽  
Surface Reflectance ◽  
Mangrove Species ◽  
New Approach ◽  
Spatio Temporal ◽  
Shortwave Infrared

Hyperspectral remote sensing across multiple spatio-temporal scales allows for mapping and monitoring mangrove habitats to support urgent conservation efforts. The use of hyperspectral imagery for assessing mangroves is less common than for terrestrial forest ecosystems. In this study, two well-known measures in statistical physics, Mean Information Gain (MIG) and Marginal Entropy (ME), have been adapted to high spatial resolution (2.5 m) full range (Visible-Shortwave-Infrared) airborne hyperspectral imagery. These two spectral complexity metrics describe the spatial heterogeneity and the aspatial heterogeneity of the reflectance. In this study, we compare MIG and ME with surface reflectance for mapping mangrove extent and species composition in the Sierpe mangroves in Costa Rica. The highest accuracy for separating mangroves from forest was achieved with visible-near infrared (VNIR) reflectance (98.8% overall accuracy), following by shortwave infrared (SWIR) MIG and ME (98%). Our results also show that MIG and ME can discriminate dominant mangrove species with higher accuracy than surface reflectance alone (e.g., MIG–VNIR = 93.6% vs. VNIR Reflectance = 89.7%).

scholarly journals Monitoring of rhythms in laser speckle data

2014 ◽  
Vol 07 (03) ◽  
pp. 1450015 ◽  
Author(s):  
D. E. Postnov ◽  
A. Y. Neganova ◽  
D. D. Postnov ◽  
A. R. Brazhe
Keyword(s):  
Blood Flow ◽  
Graphics Processing Units ◽  
Surrogate Data ◽  
Laser Speckle ◽  
Tubuloglomerular Feedback ◽  
Additional Information ◽  
3D Data ◽  
Kidney Blood Flow ◽  
Rhythm Analysis ◽  
Spatio Temporal

While the laser speckle imaging (LSI) is a powerful tool for multiple biomedical applications, such as monitoring of the blood flow, in many cases it can provide additional information when combined with spatio-temporal rhythm analysis. We demonstrate the application of Graphics Processing Units (GPU)-based rhythm analysis for the post processing of LSI data, discuss the relevant structure of GPU-based computations, test the proposed technique on surrogate 3D data, and apply this approach to kidney blood flow autoregulation. Experiments with surrogate data demonstrate the ability of the method to extract information about oscillation patterns from noisy data, as well as to detect the moving source of the rhythm. The analysis of kidney data allow us to detect and to localize the dynamics arising from autoregulation processes at the level of individual nephrons (tubuloglomerular feedback (TGF) rhythm), as well as to distinguish between the TGF-active and the TGF-silent zones.

scholarly journals Determining Extreme Still Water Levels for Design and Planning Purposes Incorporating Sea Level Rise: Sydney, Australia

Atmosphere ◽  
2022 ◽  
Vol 13 (1) ◽  
pp. 95
Author(s):  
Phil J. Watson
Keyword(s):  
Sea Level Rise ◽  
Water Level ◽  
Sea Level ◽  
Tide Gauge ◽  
Water Levels ◽  
Extreme Value Analysis ◽  
Tide Gauge Record ◽  
Value Analysis ◽  
Mean Sea Level ◽  
The Impact

This paper provides an Extreme Value Analysis (EVA) of the hourly water level record at Fort Denison dating back to 1915 to understand the statistical likelihood of the combination of high predicted tides and the more dynamic influences that can drive ocean water levels higher at the coast. The analysis is based on the Peaks-Over-Threshold (POT) method using a fitted Generalised Pareto Distribution (GPD) function to estimate extreme hourly heights above mean sea level. The analysis highlights the impact of the 1974 East Coast Low event and rarity of the associated measured water level above mean sea level at Sydney, with an estimated return period exceeding 1000 years. Extreme hourly predictions are integrated with future projections of sea level rise to provide estimates of relevant still water levels at 2050, 2070 and 2100 for a range of return periods (1 to 1000 years) for use in coastal zone management, design, and sea level rise adaptation planning along the NSW coastline. The analytical procedures described provide a step-by-step guide for practitioners on how to develop similar baseline information from any long tide gauge record and the associated limitations and key sensitivities that must be understood and appreciated in applying EVA.

scholarly journals Spatio-Temporal Deforestation Measurement Using Automatic Clustering

2016 ◽  
Vol 4 (1) ◽  
Author(s):  
Irene Erlyn Wina Rachmawan ◽  
Ali Ridho Barakbah ◽  
Tri Harsono
Keyword(s):  
Experimental Study ◽  
Satellite Images ◽  
New Approach ◽  
Deforestation Rate ◽  
Automatic Interpretation ◽  
Automatic Clustering ◽  
Landsat 7 ◽  
Spatio Temporal ◽  
Temporal Measurement ◽  
World Records

Deforestation is one of the crucial issues in Indonesia. In 2012, deforestation rate in Indonesia reached 0.84 million hectares, exceeding Brazil. According to the 2009 Guinness World Records, Indonesia's deforestation rate was 1.8 million hectares per year between 2000 and 2005. An interesting view is the fact that Indonesia government denied the deforestation rate in those years and said that the rate was only 1.08 million hectares per year in 2000 and 2005. The different problem is on the technique how to deal with the deforestation rate. In this paper, we proposed a new approach for automatically identifying the deforestation area and measuring the deforestation rate. This approach involves differential image processing for detecting Spatio-temporal nature changes of deforestation. It consists series of important features extracted from multiband satellite images which are considered as the dataset of the research. These data are proceeded through the following stages: (1) Automatic clustering for multiband satellite images, (2) Reinforcement Programming to optimize K-Means clustering, (3) Automatic interpretation for deforestation areas, and (4) Deforestation measurement adjusting with elevation of the satellite. For experimental study, we applied our proposed approach to analyze and measure the deforestation in Mendawai, South Borneo. We utilized Landsat 7 to obtain the multiband images for that area from the year 2001 to 2013. Our proposed approach is able to identify the deforestation area and measure the rate. The experiment with our proposed approach made a temporal measurement for the area and showed the increasing deforestation size of the area 1.80 hectares during those years.

Short-term growth (RNA/DNA ratio) of yellow perch (Perca flavescens) in relation to environmental influences and spatio-temporal variation in a shallow fluvial lake

2007 ◽  
Vol 64 (12) ◽  
pp. 1646-1655 ◽  
Author(s):  
Hélène Glémet ◽  
Marco A Rodríguez
Keyword(s):  
Temporal Variation ◽  
Water Level ◽  
Yellow Perch ◽  
Perca Flavescens ◽  
Negative Influence ◽  
Water Levels ◽  
Short Term ◽  
Ecological Processes ◽  
Flood Pulse Concept ◽  
Spatio Temporal

Shallow fluvial lakes are heterogeneous ecosystems in which marked spatio-temporal variation renders difficult the analysis of key ecological processes, such as growth. In this study, we used generalized additive modelling of the RNA/DNA ratio, an index of short-term growth, to investigate the influence of environmental variables and spatio-temporal variation on growth of yellow perch (Perca flavescens) in Lake St. Pierre, Quebec, Canada. Temperature and water level had seemingly stronger effects on short-term growth than seasonal change or spatial variation between and along the lakeshores. Consistent with previous studies, the maximum RNA/DNA ratio was found at 20.5 °C, suggesting that our approach provides a useful tool for estimating thermal optima for growth in the field. The RNA/DNA ratio showed a positive relationship with water level, as predicted by the flood pulse concept, a finding with implications for ecosystem productivity in fluvial lakes. The RNA/DNA ratio was more variable along the north than the south shore, possibly reflecting exposure to more differentiated water masses. The negative influence of both high temperatures and low water levels on growth points to potential impacts of climatic change on fish production in shallow fluvial lakes.

The Digital Earth Viewer: A new visualization approach for geospatial time series data

2021 ◽  
Author(s):  
Valentin Buck ◽  
Flemming Stäbler ◽  
Everardo Gonzalez ◽  
Jens Greinert
Keyword(s):  
Time Series Data ◽  
Environmental Data ◽  
Series Data ◽  
Multiple Sources ◽  
Data Types ◽  
New Approach ◽  
Digital Earth ◽  
Spatio Temporal ◽  
Diverse Data

<p>The study of the earth’s systems depends on a large amount of observations from homogeneous sources, which are usually scattered around time and space and are tightly intercorrelated to each other. The understanding of said systems depends on the ability to access diverse data types and contextualize them in a global setting suitable for their exploration. While the collection of environmental data has seen an enormous increase over the last couple of decades, the development of software solutions necessary to integrate observations across disciplines seems to be lagging behind. To deal with this issue, we developed the Digital Earth Viewer: a new program to access, combine, and display geospatial data from multiple sources over time.</p><p>Choosing a new approach, the software displays space in true 3D and treats time and time ranges as true dimensions. This allows users to navigate observations across spatio-temporal scales and combine data sources with each other as well as with meta-properties such as quality flags. In this way, the Digital Earth Viewer supports the generation of insight from data and the identification of observational gaps across compartments.</p><p>Developed as a hybrid application, it may be used both in-situ as a local installation to explore and contextualize new data, as well as in a hosted context to present curated data to a wider audience.</p><p>In this work, we present this software to the community, show its strengths and weaknesses, give insight into the development process and talk about extending and adapting the software to custom usecases.</p>

scholarly journals Methodology of designing integrated technological processes for manufacturing CNC machined parts

2018 ◽  
Vol 224 ◽  
pp. 01057
Author(s):  
Viktor I. Guzeev ◽  
Danil Yu. Pimenov
Keyword(s):  
Simulation Modeling ◽  
Metal Cutting ◽  
Cutting Tool ◽  
New Approach ◽  
Integrated Production ◽  
Technological Processes ◽  
Machined Parts ◽  
Processing Accuracy ◽  
Processing Steps ◽  
Production Conditions

The article presents a new approach to the design of technological processes of processing parts on metal cutting machines in the integrated production conditions based on the expected forecast of the parts processing accuracy. The stages of choosing the parameters of processing steps are combined with determining the parameters of the cutting tool and machining attachments by simulation modeling. The design sequence begins with the first operation.

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