Satellite-Based Systems for Flood Monitoring and Warning

The development of Internet of Things (IoT) systems is a rapidly evolving scenario, thanks also to newly available low-power wide area network (LPWAN) technologies that are utilized for environmental monitoring purposes and to prevent potentially dangerous situations with smaller and less expensive physical structures. This paper presents the design, implementation and test results of a flood-monitoring system based on LoRa technology, tested in a real-world scenario. The entire system is designed in a modular perspective, in order to have the capability to interface different types of sensors without the need for making significant hardware changes to the proposed node architecture. The information is stored through a device equipped with sensors and a microcontroller, connected to a LoRa wireless module for sending data, which are then processed and stored through a web structure where the alarm function is implemented in case of flooding.

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An Open Source Approach for Watershed's Delimitation to Support Flood Monitoring

International Journal of Distributed Systems and Technologies ◽

10.4018/ijdst.2016100105 ◽

2016 ◽

Vol 7 (4) ◽

pp. 77-88

Author(s):

Tiago Carvalho ◽

Leonardo B. L. Santos ◽

Eduardo F. P. Luz ◽

Rogério Ishibashi ◽

Aurelienne A. S. Jorge ◽

...

Keyword(s):

Open Source ◽

Open Source Software ◽

Disaster Risk Reduction ◽

Methodological Approach ◽

Disaster Risk ◽

Extreme Weather Events ◽

Suggested Approach ◽

Weather Events ◽

Flood Monitoring ◽

Extreme Rain

In the last years, natural disasters have become more frequent and their impacts have reached a large number of people. When these events happen in unprepared regions, they can cause human and material losses. The consequences can be even more catastrophic when the responsible entities are not properly prepared. To minimize the impacts of extreme weather events, especially extreme rain which can trigger severe floods, this paper proposes a methodological approach to monitor floods through open source software, based on watershed's delineation. The suggested approach can be a tool to support disaster risk reduction planning.

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Real-Time Flash-Flood Monitoring, Alerting and Forecasting System using Data Mining and wireless sensor Network

2015 International Conference on Communications and Signal Processing (ICCSP) ◽

10.1109/iccsp.2015.7322851 ◽

2015 ◽

Cited By ~ 3

Author(s):

Sagar Sudhakar Mane ◽

M.K. Mokashi

Keyword(s):

Data Mining ◽

Wireless Sensor Network ◽

Real Time ◽

Sensor Network ◽

Flash Flood ◽

Wireless Sensor ◽

Flood Monitoring ◽

Forecasting System ◽

Using Data

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The Wide Area Grid Testbed for Flood Monitoring Using Earth Observation Data

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing ◽

10.1109/jstars.2012.2201447 ◽

2012 ◽

Vol 5 (6) ◽

pp. 1746-1751 ◽

Cited By ~ 20

Author(s):

Nataliia N. Kussul ◽

Andrii Yu. Shelestov ◽

Sergii V. Skakun ◽

Guoqing Li ◽

Olga M. Kussul

Keyword(s):

Earth Observation ◽

Wide Area ◽

Observation Data ◽

Flood Monitoring ◽

Earth Observation Data

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Assessing The Quality of Water Depth Derived From Volunteered Geographic Information (VGI) For Flood Monitoring. A Case Study of Hurricane Harvey In Harris County, Texas

10.21203/rs.3.rs-644550/v1 ◽

2021 ◽

Author(s):

Abdullatif Alyaqout ◽

T. Edwin Chow ◽

Alexander Savelyev

Keyword(s):

Water Depth ◽

Temporal Distribution ◽

Volunteered Geographic Information ◽

Temporal Variations ◽

Geographic Information ◽

Text Messages ◽

Quality Of Water ◽

Significant Difference ◽

Flood Monitoring

Abstract The primary objectives of this study are to 1) assess the quality of each volunteered geographic information (VGI) data modality (text, pictures, and videos), and 2) evaluate the quality of multiple VGI data sources, especially the multimedia that include pictures and videos, against synthesized water depth (WD) derived from remote sensing (RS) and authoritative data (e.g. stream gauges and depth grids). The availability of VGI, such as social media and crowdsourced data, empowered the researchers to monitor and model floods in near-real-time by integrating multi-sourced data available. Nevertheless, the quality of VGI sources and its reliability for flood monitoring (e.g. WD) is not well understood and validated by empirical data. Moreover, existing literature focuses mostly on text messages but not the multimedia nature of VGI. Therefore, this study measures the differences in synthesized WD from VGI modalities in terms of (1) spatial and (2) temporal variations, (3) against WD derived from RS, and (4) against authoritative data including (a) stream gauges and (b) depth grids. The results of the study show that there are significant differences in terms of spatial and temporal distribution of VGI modalities. Regarding VGI and RS comparison, the results show that there is a significant difference in WD between VGI and RS. In terms of VGI and authoritative data comparison, the analysis revealed that there is no significant difference in WD between VGI and stream gauges, while there is a significant difference between the depth grids and VGI.

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