Flood Mapping from Multi-Sensor EO Data for Near Real-Time Infrastructure Impact Assessment: Lessons Learned from the 2017 Spring Flood in Eastern Canada

2020 ◽  
pp. 275-289
Author(s):  
Ian Olthof ◽  
Simon Tolszczuk-Leclerc ◽  
Brad Lehrbass ◽  
Victor Neufeld ◽  
Vincent Decker
Keyword(s):  
Impact Assessment ◽  
Real Time ◽  
Lessons Learned ◽  
Flood Mapping ◽  
Spring Flood ◽  
Eastern Canada

scholarly journals Testing Urban Flood Mapping Approaches from Satellite and In-Situ Data Collected during 2017 and 2019 Events in Eastern Canada

2020 ◽  
Vol 12 (19) ◽  
pp. 3141
Author(s):  
Ian Olthof ◽  
Nicolas Svacina
Keyword(s):  
High Resolution ◽  
Real Time ◽  
Urban Areas ◽  
Cloud Cover ◽  
Data Availability ◽  
Flood Mapping ◽  
Eastern Canada ◽  
Urban Flood ◽  
Water Height

The increasing frequency of flooding worldwide has driven research to improve near real-time flood mapping from remote-sensing data. Improved automation and processing speed to map both open water and vegetated area flooding have resulted from these research efforts. Despite these achievements, flood mapping in urban areas where a significant number of overall impacts are felt remains a challenge. Near real-time data availability, shadowing caused by manmade infrastructure, spatial resolution, and cloud cover inhibiting optical transmission, are all factors that complicate detailed urban flood mapping needed to inform response efforts. This paper uses numerous data sources collected during two major flood events that impacted the same region of Eastern Canada in 2017 and 2019 to test different urban flood mapping approaches presented as case studies in three separate urban boroughs. Cloud-free high-resolution 3 m PlanetLab optical data acquired near peak-flood in 2019 were used to generate a maximum flood extent product for that year. Approaches using new Lidar Digital Elevation Models (DEM)s and water height estimated from nineteen RADARSAT-2 flood maps, point-based flood perimeter observations from citizen geographic information, and simulated traffic camera or other urban sensor network data were tested and verified using independent data. Coherent change detection (CCD) using multi-temporal Interferometric Wide (IW) Sentinel-1 data was also tested. Results indicate that while clear-sky high-resolution optical imagery represents the current gold standard, its availability is not guaranteed due to timely coverage and cloud cover. Water height estimated from 8 to 12.5 m resolution RADARSAT-2 flood perimeters were not sufficiently accurate to flood adjacent urban areas using a Lidar DEM in near real-time, but all nineteen scenes combined captured boroughs that flooded at least once in both flood years. CCD identified flooded boroughs and roughly captured their flood extents, but lacked timeliness and sufficient detail to inform street-level decision-making in near real-time. Point-based flood perimeter observation, whether from in-situ sensors or high-resolution optical satellites combined with Lidar DEMs, can generate accurate full flood extents under certain conditions. Observed point-based flood perimeters on manmade features with low topographic variation produced the most accurate flood extents due to reliable water height estimation from these points.

scholarly journals Role of Laboratory Medicine in SARS-CoV-2 Diagnostics. Lessons Learned from a Pandemic

Healthcare ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 915
Author(s):  
Irena Duś-Ilnicka ◽  
Aleksander Szymczak ◽  
Małgorzata Małodobra-Mazur ◽  
Miron Tokarski
Keyword(s):  
Molecular Biology ◽  
Real Time ◽  
Real Time Pcr ◽  
Laboratory Medicine ◽  
Lessons Learned ◽  
Diagnostic Methods ◽  
Medical Community ◽  
Medical Diagnostic ◽  
Novel Coronavirus ◽  
Available Information

Since the 2019 novel coronavirus outbreak began in Wuhan, China, diagnostic methods in the field of molecular biology have been developing faster than ever under the vigilant eye of world’s research community. Unfortunately, the medical community was not prepared for testing such large volumes or ranges of biological materials, whether blood samples for antibody immunological testing, or salivary/swab samples for real-time PCR. For this reason, many medical diagnostic laboratories have made the switch to working in the field of molecular biology, and research undertaken to speed up the flow of samples through laboratory. The aim of this narrative review is to evaluate the current literature on laboratory techniques for the diagnosis of SARS-CoV-2 infection available on pubmed.gov, Google Scholar, and according to the writers’ knowledge and experience of the laboratory medicine. It assesses the available information in the field of molecular biology by comparing real-time PCR, LAMP technique, RNA sequencing, and immunological diagnostics, and examines the newest techniques along with their limitations for use in SARS-CoV-2 diagnostics.

A Novel Workflow for Geosteering a Horizontal Well in a Low Resistivity Contrast Anisotropic Environment: A Case Study in Semoga Field, Indonesia

2021 ◽  
Author(s):  
Yessica Fransisca ◽  
Karinka Adiandra ◽  
Vinda Manurung ◽  
Laila Warkhaida ◽  
M. Aidil Arham ◽  
...  
Keyword(s):  
Real Time ◽  
Horizontal Well ◽  
Gamma Ray ◽  
Lessons Learned ◽  
Electrical Anisotropy ◽  
Anisotropy Ratio ◽  
Well Placement ◽  
Low Contrast ◽  
Low Resistivity ◽  
The Subject

Abstract This paper describes the combination of strategies deployed to optimize horizontal well placement in a 40 ft thick isotropic sand with very low resistivity contrast compared to an underlying anisotropic shale in Semoga field. These strategies were developed due to previously unsuccessful attempts to drill a horizontal well with multiple side-tracks that was finally drilled and completed as a high-inclined well. To maximize reservoir contact of the subject horizontal well, a new methodology on well placement was developed by applying lessons learned, taking into account the additional challenges within this well. The first approach was to conduct a thorough analysis on the previous inclined well to evaluate each formation layer’s anisotropy ratio to be used in an effective geosteering model that could better simulate the real time environment. Correct selections of geosteering tools based on comprehensive pre-well modelling was considered to ensure on-target landing section to facilitate an effective lateral section. A comprehensive geosteering pre-well model was constructed to guide real-time operations. In the subject horizontal well, landing strategy was analysed in four stages of anisotropy ratio. The lateral section strategy focused on how to cater for the expected fault and maintain the trajectory to maximize reservoir exposure. Execution of the geosteering operations resulted in 100% reservoir contact. By monitoring the behaviour of shale anisotropy ratio from resistivity measurements and gamma ray at-bit data while drilling, the subject well was precisely landed at 11.5 ft TVD below the top of target sand. In the lateral section, wellbore trajectory intersected two faults exhibiting greater associated throw compared to the seismic estimate. Resistivity geo-signal and azimuthal resistivity responses were used to maintain the wellbore attitude inside the target reservoir. In this case history well with a low resistivity contrast environment, this methodology successfully enabled efficient operations to land the well precisely at the target with minimum borehole tortuosity. This was achieved by reducing geological uncertainty due to anomalous resistivity data responding to shale electrical anisotropy. Recognition of these electromagnetic resistivity values also played an important role in identifying the overlain anisotropic shale layer, hence avoiding reservoir exit. This workflow also helped in benchmarking future horizontal well placement operations in Semoga Field. Technical Categories: Geosteering and Well Placement, Reservoir Engineering, Low resistivity Low Contrast Reservoir Evaluation, Real-Time Operations, Case Studies

Telecommunications- and Information Technology–Inspired Analyses: Review of an Intelligent Transportation Systems Experience

2017 ◽  
Vol 2658 (1) ◽  
pp. 44-55 ◽  
Author(s):  
Yupo Chan
Keyword(s):  
Information Technology ◽  
Big Data ◽  
Real Time ◽  
Traffic Management ◽  
Transportation Systems ◽  
Lessons Learned ◽  
Connected Vehicles ◽  
Ongoing Research ◽  
Real Time Information ◽  
Time Information

This paper reviews both the author’s experience with managing highway network traffic on a real-time basis and the ongoing research into harnessing the potential of telecommunications and information technology (IT). On the basis of the lessons learned, this paper speculates about how telecommunications and IT capabilities can respond to current and future developments in traffic management. Issues arising from disruptive telecommunications technologies include the ready availability of real-time information, the crowdsourcing of information, the challenges of big data, and the need for information quality. Issues arising from transportation technologies include autonomous vehicles and connected vehicles and new taxi-like car- and bikesharing. Illustrations are drawn from the following core functions of a traffic management center: ( a) detecting and resolving an incident (possibly through crowdsourcing), ( b) monitoring and forecasting traffic (possibly through connected vehicles serving as sensors), ( c) advising motorists about routing alternatives (possibly through real-time information), and ( d) configuring traffic control strategies and tactics (possibly though big data). The conclusion drawn is that agility is the key to success in an ever-evolving technological scene. The solid guiding principle remains innovative and rigorous analytical procedures that build on the state of the art in the field, including both hard and soft technologies. The biggest modeling and simulation challenge remains the unknown, including such rapidly emerging trends as the Internet of things and the smart city.

scholarly journals Multihazard simulation for coastal flood mapping: Bathtub versus numerical modelling in an open estuary, Eastern Canada

2018 ◽  
Vol 12 (S1) ◽  
Author(s):  
David Didier ◽  
Jérémy Baudry ◽  
Pascal Bernatchez ◽  
Dany Dumont ◽  
Mojtaba Sadegh ◽  
...  
Keyword(s):  
Numerical Modelling ◽  
Flood Mapping ◽  
Eastern Canada ◽  
Coastal Flood

scholarly journals Lessons Learned From Implementing a Novel Bayesian Adaptive Dose-Finding Design in Advanced Pancreatic Cancer

2021 ◽  
pp. 1719-1726
Author(s):  
Rebecca S. S. Tidwell ◽  
Peter F. Thall ◽  
Ying Yuan
Keyword(s):  
Pancreatic Cancer ◽  
Real Time ◽  
Late Onset ◽  
Locally Advanced ◽  
Advanced Pancreatic Cancer ◽  
Lessons Learned ◽  
Dose Finding ◽  
Random Assignment ◽  
Trial Conduct ◽  
Trial Efficiency

PURPOSE Novel Bayesian adaptive designs provide an effective way to improve clinical trial efficiency. These designs are superior to conventional methods, but implementing them can be challenging. The aim of this article was to describe what we learned while applying a novel Bayesian phase I-II design in a recent trial. METHODS The primary goal of the trial was to optimize radiation therapy (RT) dose among three levels (low, standard, and high), given either with placebo (P) or an investigational agent (A), for treating locally advanced, radiation-naive pancreatic cancer, deemed appropriate for RT rather than surgery. Up to 48 patients were randomly assigned fairly between RT plus P and RT plus A, with RT dose-finding done within each arm using the late-onset efficacy-toxicity design on the basis of two coprimary end points, tumor response and dose-limiting toxicity, both evaluated at up to 90 days. The random assignment was blinded, but within each arm, unblinded RT doses were chosen adaptively using software developed within the institution. RESULTS Implementing the design involved double-blind balance-restricted random assignment, real-time assessment of patient outcomes to evaluate the efficacy-toxicity trade-off for each RT dose in each arm to optimize each patient's RT dose adaptively, and transition from a single-center trial to a multicenter trial. We present lessons learned and illustrative documentation. CONCLUSION Implementing novel Bayesian adaptive trial designs requires close collaborations between physicians, pharmacists, statisticians, data managers, and sponsors. The process is difficult but manageable and essential for efficient trial conduct. Close collaboration during trial conduct is a key component of any trial that includes real-time adaptive decision rules.

scholarly journals Patients, Families, and Communities COVID-19 Impact Assessment: Lessons Learned and Compelling Needs

2021 ◽  
Vol 11 ◽  
Author(s):  
Frederick Isasi ◽  
◽  
Mary D. Naylor ◽  
David Skorton ◽  
David Grabowski ◽  
...  
Keyword(s):  
Impact Assessment ◽  
Lessons Learned

Lessons Learned: A Pilot Project for Secondary Process Real Time Monitoring at MSDGC

2014 ◽  
Vol 2014 (9) ◽  
pp. 3317-3326
Author(s):  
Ting Lu ◽  
Beth Hinzman ◽  
Ryan Welsh ◽  
Andrew Sampson ◽  
Donald Linn ◽  
...  
Keyword(s):  
Real Time ◽  
Pilot Project ◽  
Lessons Learned ◽  
Secondary Process ◽  
Real Time Monitoring
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