A Multi-Sensor Exportable Approach for Automatic Flooded Areas Detection and Monitoring by a Composite Satellite Constellation

Timely and frequently updated information about flood-affected areas and their space-time evolution are often crucial in order to correctly manage the emergency phases. In such a context, optical data provided by meteorological satellites, offering the highest available temporal resolution (from hours to minutes), could have a great potential. As cloud cover often occurs reducing the number of usable optical satellite images, an appropriate integration of observations coming from different satellite systems will surely improve the probability to find cloud-free images over the investigated region. To make this integration effective, appropriate satellite data analysis methodologies, suitable for providing congruent results, regardless of the used sensor, are envisaged. In this paper, a sensor-independent approach (RST, Robust Satellites Techniques-FLOOD) is presented and applied to data acquired by two different satellite systems (Advanced Very High Resolution Radiometer (AVHRR) onboard National Oceanic and Atmospheric Administration platforms and Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Earth Observing System satellites) at different spatial resolutions (from 1 km to 250 m) in the case of Elbe flood event occurred in Germany on August 2002. Results achieved demonstrated as the full integration of AVHRR and MODIS RST-FLOOD products allowed us to double the number of satellite passes daily available, improving continuity of monitoring over flood-affected regions. In addition, the application of RST-FLOOD to higher spatial resolution MODIS (250 m) data revealed to be crucial not only for mapping purposes but also for improving RST-FLOOD capability in identifying flooded areas not previously detected at lower spatial resolution

Design and implementation of flood monitoring and warning system based on internet of things

Floods are unavoidable phenomena that can cause massive loss of people's lives and the destruction of infrastructure. Flash floods rise rapidly in a flood-prone area, which results in property damage, but the impact on human lives is somewhat preventable by the presence of monitoring systems. Although there are many systems widely in practice by disaster management agencies in monitoring flood levels, most of these systems are limited in range. For example, some systems implementing the Long-Range Wide Area Network (LoRaWAN) have a maximum distance of 300m from the gateway. However, the maximum distance that LoRaWAN can reach is 1.5km. Then, the study on the parameter that involved in LoRaWAN for the Flood Monitoring and Warning System (FMWS) is limited. Furthermore, in most developing countries, the conventional flood gates in water canals are manually operated and suffer from the lack of real-time monitoring of water levels which might lead to an overflow in the channels and flash floods. On top of that, the lack of real-time data analysis in the system that can be accessed is one of the limitations in Malaysia. Therefore, this research design and implementation multiple LoRa-based smart sensors with a LoRaWAN gateway as a network testbed for monitoring flood levels and evaluating the parameter of LoRaWAN. Then, the LoRaWAN’s activation was compared and analysed to identify the best activation for the FMWS. Lastly, the real-time assessment of the risk due to the flood level has been enabled on the Tago.IO dashboard for triggering an early flood warning. The proposed FMWS with LoRaWAN uses an ultrasonic sensor with an Arduino microcontroller to measure water level, Long-Range (LoRa) as a communication module, and a single gateway. The end nodes have been tested in several scenarios to test the FMWS’s communication performance in terms of Received Signal Strength Indication (RSSI), Signal Noise Ratio (SNR), delay, and the Percentages of Data Received (PDR). The design of the sensing node involved the hardware and software with the solar panel as the power source. A 3 Dimension (3D) model for the end node was developed for casing the sensing node. The testing area for testing the performance of LoRaWAN is a 2km radius. Throughout the testing, the proposed system communicates up to 2km in single and multiple node cases. On top of that, the multiple nodes have higher overall SNR value compared to the single node where 56% of all result are positive for multiple nodes while the single node exhibit only 50%. In addition, the RSSI and SNR have impact on the PDR. However, the delay inversely perorational with RSSI, SNR and PDR values. The recommended activation for FMWS is Activation By-Personalization, (ABP) since it is over complete control, especially for achieving a high PDR. Lastly, the data on Tago.IO was accessed via webpages and Tago.IO mobile application. In conclusion, the FMWS able to communicate to the gateway at 1.5km distance. However, the higher the SF, the higher the network's performance at long distances. The ABP is the activation that is suitable for the proposed FMWS. Lastly, the warning system will trigger once the water level reaches the warning level

Studies on Sensor Networks with Fiber Optics for Agricultural Environment Monitoring

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