Development of a method for flood detection based on Sentinel‐1 images and classifier algorithms

2020 ◽  
Author(s):  
Alireza Sharifi
Keyword(s):  
Flood Detection ◽  
Classifier Algorithms

Automatic flood detection using sentinel-1 images on the google earth engine

2021 ◽  
Vol 193 (5) ◽  
Author(s):  
Meysam Moharrami ◽  
Mohammad Javanbakht ◽  
Sara Attarchi
Keyword(s):  
Google Earth ◽  
Google Earth Engine ◽  
Flood Detection

scholarly journals Applicability of NGGM near-real time simulations in flood detection

2019 ◽  
Vol 9 (1) ◽  
pp. 111-126
Author(s):  
A. F. Purkhauser ◽  
J. A. Koch ◽  
R. Pail
Keyword(s):  
European Space Agency ◽  
Earth System ◽  
The Earth ◽  
Future Mission ◽  
Space Agency ◽  
Flood Detection ◽  
The One ◽  
Real Time Simulations ◽  
Grace Mission ◽  
Gravity Mission

Abstract The GRACE mission has demonstrated a tremendous potential for observing mass changes in the Earth system from space for climate research and the observation of climate change. Future mission should on the one hand extend the already existing time series and also provide higher spatial and temporal resolution that is required to fulfil all needs placed on a future mission. To analyse the applicability of such a Next Generation Gravity Mission (NGGM) concept regarding hydrological applications, two GRACE-FO-type pairs in Bender formation are analysed. The numerical closed loop simulations with a realistic noise assumption are based on the short arc approach and make use of the Wiese approach, enabling a self-de-aliasing of high-frequency atmospheric and oceanic signals, and a NRT approach for a short latency. Numerical simulations for future gravity mission concepts are based on geophysical models, representing the time-variable gravity field. First tests regarding the usability of the hydrology component contained in the Earth System Model (ESM) by the European Space Agency (ESA) for the analysis regarding a possible flood monitoring and detection showed a clear signal in a third of the analysed flood cases. Our analysis of selected cases found that detection of floods was clearly possible with the reconstructed AOHIS/HIS signal in 20% of the tested examples, while in 40% of the cases a peak was visible but not clearly recognisable.

The analysis of using satellite soil moisture observations for flood detection, evaluating over the Thailand’s Great Flood of 2011

2021 ◽  
Author(s):  
Natthachet Tangdamrongsub ◽  
Chalita Forgotson ◽  
Chandana Gangodagamage ◽  
Joshua Forgotson
Keyword(s):  
Soil Moisture ◽  
Flood Detection

A telemedicine tool framework for lung sounds classification using ensemble classifier algorithms

Measurement ◽  
2020 ◽  
Vol 162 ◽  
pp. 107883
Author(s):  
Mustafa Musa Jaber ◽  
Sura Khalil Abd ◽  
P.Mohamed Shakeel ◽  
M.A. Burhanuddin ◽  
Mohammed Abdulameer Mohammed ◽  
...  
Keyword(s):  
Ensemble Classifier ◽  
Lung Sounds ◽  
Classifier Algorithms

scholarly journals Evaluation of the satellite-based Global Flood Detection System for measuring river discharge: influence of local factors

2014 ◽  
Vol 18 (11) ◽  
pp. 4467-4484 ◽  
Author(s):  
B. Revilla-Romero ◽  
J. Thielen ◽  
P. Salamon ◽  
T. De Groeve ◽  
G. R. Brakenridge
Keyword(s):  
Real Time ◽  
River Discharge ◽  
Detection System ◽  
Poor Performance ◽  
Model Verification ◽  
Area Index ◽  
General Terms ◽  
Skill Scores ◽  
Flood Detection ◽  
Discharge Measurements

Abstract. One of the main challenges for global hydrological modelling is the limited availability of observational data for calibration and model verification. This is particularly the case for real-time applications. This problem could potentially be overcome if discharge measurements based on satellite data were sufficiently accurate to substitute for ground-based measurements. The aim of this study is to test the potentials and constraints of the remote sensing signal of the Global Flood Detection System for converting the flood detection signal into river discharge values. The study uses data for 322 river measurement locations in Africa, Asia, Europe, North America and South America. Satellite discharge measurements were calibrated for these sites and a validation analysis with in situ discharge was performed. The locations with very good performance will be used in a future project where satellite discharge measurements are obtained on a daily basis to fill the gaps where real-time ground observations are not available. These include several international river locations in Africa: the Niger, Volta and Zambezi rivers. Analysis of the potential factors affecting the satellite signal was based on a classification decision tree (random forest) and showed that mean discharge, climatic region, land cover and upstream catchment area are the dominant variables which determine good or poor performance of the measure\\-ment sites. In general terms, higher skill scores were obtained for locations with one or more of the following characteristics: a river width higher than 1km; a large floodplain area and in flooded forest, a potential flooded area greater than 40%; sparse vegetation, croplands or grasslands and closed to open and open forest; leaf area index > 2; tropical climatic area; and without hydraulic infrastructures. Also, locations where river ice cover is seasonally present obtained higher skill scores. This work provides guidance on the best locations and limitations for estimating discharge values from these daily satellite signals.

scholarly journals Internet-Based Flood Detection System (Iot) and Telegram Messenger Using Mcu Node and Water Level Sensor

2020 ◽  
Vol 4 (1) ◽  
pp. 230-235
Author(s):  
Novianda Nanda Nanda ◽  
Rizalul Akram ◽  
Liza Fitria
Keyword(s):  
Water Level ◽  
Early Warning ◽  
High Intensity ◽  
Rainy Season ◽  
Early Warning System ◽  
Detection System ◽  
Warning System ◽  
Level Sensor ◽  
Flood Detection ◽  
Internet Of Thing

During the rainy season, several regions in Indonesia experienced floods even to the capital of Indonesia also flooded. Some of the causes are the high intensity of continuous rain, clogged or non-smooth drainage, high tides to accommodate the flow of water from rivers, other causes such as forest destruction, shallow and full of garbage and other causes. Every flood disaster comes, often harming the residents who experience it. The late anticipation from the community and the absence of an early warning system or information that indicates that there will be a flood so that the community is not prepared to face floods that cause a lot of losses. Therefore it is necessary to have a detection system to provide early warning if floods will occur, this is very important to prevent material losses from flooded residents. From this problem the researchers designed an internet-based flood detection System of Things (IoT). This tool can later be controlled via a smartphone remotely and can send messages Telegram messenger to citizens if the detector detects a flood will occur.Keywords: Flooding, Smartphone, Telegram messenger, Internet of Thing (IoT).

scholarly journals Perancangan Sistem Monitoring Ketinggian Air Sebagai Pendeteksi Banjir Berbasis IoT Menggunakan Sensor Ultrasonik

2020 ◽  
Vol 4 (1) ◽  
pp. 117
Author(s):  
Nicko Pratama ◽  
Ucuk Darusalam ◽  
Novi Dian Nathasia
Keyword(s):  
Surface Water ◽  
Rainy Season ◽  
Water Surface ◽  
Reading Error ◽  
The Public ◽  
Surface Distance ◽  
Distance Data ◽  
Flood Detection ◽  
Level Monitoring ◽  
Water Level Monitoring

High rainfall in the rainy season can last about six months, this makes it rain continuously and cause an increase in the volume of water that has the potential for flooding. While the public does not get information or notice directly when it will happen. To anticipate these problems, the design of a water level monitoring system as an early flood detection based on IoT is considered efficient. The system will detect the distance of the sensor to the surface of the water, if the distance of the surface water approaches the sensor, the system will sound the siren as a sign of flooding. The system will display the alert status that occurs and the water surface distance in realtime.. From 100 data of water surface distance with ultrasonic sensors that have been tested, get 6 times the distance reading error. In testing of several water surface distances with sensors, the system can store all distance data into a database.

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