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Conference Presentations by Badr-Eddine Boudriki Semlali

International Journal of Embedded and Real-Time Communication Systems, 2019

The world is witnessing important increases in industrial, transport and agriculture activities. ... more The world is witnessing important increases in industrial, transport and agriculture activities. This leads to economic growth, but, on the other hand, causes substantial damage in urban air, due to emissions of harmful gases, mainly CO, SO2, NO2 and the Particular Matter (PM). The World Health Organization (WHO) confirms that daily exposure to pollutants causes approximately three million deaths. It is therefore necessary to assess continuously the air quality. In this context, a Java-based application was developed to acquire data from EUMETSAT geostationary and Polar Orbit satellites, through the Mediterranean Dialogue Earth Observatory (MDEO) terrestrial station. This application filters, subsets, processes and visualizes products covering Morocco zone. Significant correlations were found between emissions and industrial activities related to power thermal plants, factories, transportation and ports.

Remote Sensing: Aspects and Specifications within a Proposed Big Data Architecture, 2017

The important growth of industrial, transport and agriculture activities in Morocco , has lead to... more The important growth of industrial, transport and agriculture activities in Morocco , has lead to many air quality and climate changes issues, due to the emission of harmful gases , particularly: CO, SO2, NO2, and so on. we have used remote sensing technique to monitor air quality, try to expect some natural disasters and help in the decision makers. However remote sensing data are not easy to handle, because of their huge size, high complexity, variety and velocity [1]. In this part of our research we have especially proven that remote sensing data are big data. For this purpose, we proposed a big data architecture, perhaps, will be regarded as a solution of RS big data processing challenge.

Development of a Near Real-time Air Pollution Map of Morocco, 2017

Currently, the world is witnessing important increases of industrial, transport and agriculture a... more Currently, the world is witnessing important increases of industrial, transport and agriculture activities. This leads to environmental changes and issues of air pollution, due to emission of harmful gases such as CO, SO2 and NO2. Therefore it is very important recommended to continuously monitor air quality. For this purpose We developed a Java-based application that acquire data from MDEO (Mediterranean Dialogue Earth Observatory) platform using EUMETCast service of EUMETSAT organization , afterwards the application filter, subsets, process and visualize datasets covering Morocco zone. Finally we find out correlations between emissions and industrial activities sources particularly power thermal plants, Factories and ports Morocco.

Papers by Badr-Eddine Boudriki Semlali

IntechOpen eBooks, May 22, 2024

Geomatics, natural hazards & risk, Apr 9, 2024

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Dec 31, 2023

Natural Hazards and Earth System Sciences, Nov 28, 2023

IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium

&#160;&#160;&#160; Morocco has become one of the most in... more &#160;&#160;&#160; Morocco has become one of the most industrialized feet, not only in Africa but also in the world. This mutation benefits the country's development; however, these industrial activities directly or indirectly impact the impairment grade environment. Remote Sensing (RS) data offer consideration from government projects and commercial applications to academic fields from free-open access data centers. The EUMETSAT NASA, NOAA, ESA, Copernicus, etc., deliver RS data with numerous satellites flying on geostationary and polar orbits. The provided data are massive (Terabytes daily) for environmental monitoring, disaster management, and other applications. RS products are measured with various instruments, for instance, radiometer, spectrometer, hyperspectral, sounder, altimeter, and optical. Wide spectral bands are employed, such as infrared, visible, radar, microwave, etc. The proliferation of RS data also increases the RS data's velocity (thousands of files daily), the data's diversity (NetCDF, HDF5, BUFR, binary, etc.), and higher dimensionality characteristics. Accordingly, RS data can be regarded as Big Data (BD). Thus, it is challenging to acquire, ingest, process, store, query, and visualize RSBD proficiently due to the data and computing-intensive challenges and limitations. As a result, an incredible deal of attention in the field of BD and its analysis has increased, most ambitious from a vast number of research challenges powerfully related to RS applications, such as modeling, pre-processing, analyzing, querying, and mining, in distributed and scalable clusters. &#160;&#160;&#160; This project aims to design and develop an African Earth Open Portal (AfEOP) as a platform for the automatic acquisition, ingestion, processing, and visualization of the massive stream of RS datasets from multiples satellites sensors, ground stations, drones, etc. The proposed platform will solve many environmental issues, notably: (1) supervising the weather parameters in Africa, including the temperature, humidity, pressure, and wind speed, etc. (2) drought assessment, evapotranspiration estimation, water drainage monitoring, and food yield and crop forecasting 3) agriculture and fertilization optimization using Artificial Intelligence (AI) algorithms helping in decision making 4) water use reduction using RS data, AI, and physical models. &#160;&#160;&#160; In this project, we perform BD Analytics by (1) presenting a brief survey of the used data sources and describing the nature of the used satellite sensors' data for environmental applications. (2) designing and developing an ingestion framework for RSBD in a distributed platform for RS data storage and query. (3) incorporating cloud computing and parallel programming techniques to optimize processing. (4) visualizing the results in demand in interactive maps and dashboards. Accordingly, this led us to the following questions: Is the designed architecture of RS data pre-processing efficient to extract only helpful information in a short execution time? Is it possible to make the RS data-friendly with the distributed framework for more processing? Are RS techniques efficient for environmental applications for Africa and notably Morocco?

Applied sciences, Nov 11, 2021

2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 2021

Remote Sensing

Remote Sensing, 2023

Every year, earthquakes cause thousands of casualties and high economic losses. For example, in t... more Every year, earthquakes cause thousands of casualties and high economic losses. For example, in the time frame from 1998 to 2018, the total number of casualties due to earthquakes was larger than 846 thousand people, and the recorded economic losses were about USD 661 billion. At present, there are no earthquake precursors that can be used to trigger a warning. However, some studies have analyzed land surface temperature (LST) anomalies as a potential earthquake precursor. In this study, a large database of global LST data from the Geostationary Operational Environmental Satellite (GOES) and AQUA satellites during the whole year 2020 has been used to study the LST anomalies in the areas affected by earthquakes. A total of 1350 earthquakes with a magnitude larger than M4 were analyzed. Two methods widely used in the literature have been used to detect LST anomalies in the detrended LST time series: the interquartile (IQT) method and the standard deviation (STD). To the authors' knowledge, it is the first time that the confusion matrix (CM), the receiver operating characteristic curve (ROC), and some other figures of merit (FoM) are used to assess and optimize the performance of the methods, and to select the optimum combination that could be used as a proxy for their occurrence. A positive anomaly was found a few days before the studied earthquakes, followed by the LST decrease after the event. Further studies over larger regions and more extended periods will be needed to consolidate these encouraging results.

. Ionospheric disturbances induced by seismic activity have been studied in the last years by man... more . Ionospheric disturbances induced by seismic activity have been studied in the last years by many authors, showing an impact both before and after the occurrence of earthquakes. In this study, the ionospheric scintillation produced by the 2021 La Palma volcano eruption is analyzed. The "Cumbre Vieja" volcano was active from September 19th to December 13th, 2021, and many magnitude 3–4 earthquakes were recorded, with some of them reaching magnitude 5. In this study the three methods: GNSS reference monitoring, GNSS Reflectometry (GNSS-R) from NASA CYGNSS, and GNSS Radio Occultation (GNSS-RO) from COSMIC and Spire constellations, are used, allowing us to compare and evaluate their performance in the same conditions. To compare the seismic activity with ionospheric scintillation, earthquakes’ generated energy, and percentile 95 % of the intensity scintillation parameter (S4), measurements have been computed every 6 h intervals for the whole duration of the volcanic eruption. GNSS-RO has shown the best correlation between earthquakes’ energy and S4, with values up to 0.09 when the perturbations occur around 18 h after the seismic activity. GNSS reference monitoring stations data also shows some correlation 18 h after and 7–8 days after. As expected, GNSS-R is the one that shows the smallest correlation, as the ionospheric signatures get masked by the signature of the surface where the reflection is taking place. Additionally, as expected as well, the three methods show a smaller correlation during the week before earthquakes.

Remote Sensing

Ionospheric perturbations affect the propagation of electromagnetic waves. These perturbations, b... more Ionospheric perturbations affect the propagation of electromagnetic waves. These perturbations, besides being a problem for space communications, satellite navigation, and Earth observation techniques, could also be used as another Earth observation tool. Several recent studies showed correlations with earthquakes with ionospheric anomalies, but almost all of them use ground stations to measure the Total Electron Content (TEC) variations, and, in particular, the ones occurring after an earthquake. Here, a preliminary study is presented on how the ionospheric scintillation measured with GNSS-R instruments over oceanic regions shows a small, but detectable correlation with the occurrence of earthquakes, which in some cases occurs before the earthquakes. This study uses GNSS-R data from NASA CYGNSS Mission to measure the ionospheric amplitude scintillation (S4) for 6 months from March 2019 to August 2019, applying a statistical analysis based on confusion matrixes, and the Receiver Ope...

International Journal of Embedded and Real-Time Communication Systems, 2019

Remote Sensing: Aspects and Specifications within a Proposed Big Data Architecture, 2017

Development of a Near Real-time Air Pollution Map of Morocco, 2017

IntechOpen eBooks, May 22, 2024

Geomatics, natural hazards & risk, Apr 9, 2024

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Dec 31, 2023

Natural Hazards and Earth System Sciences, Nov 28, 2023

IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium

Applied sciences, Nov 11, 2021

2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 2021

Remote Sensing

Remote Sensing, 2023

Remote Sensing

This data are the Input, output of the developed software SAT-CEP-Monitor and the generated inter... more This data are the Input, output of the developed software SAT-CEP-Monitor and the generated interactive maps of Morocco and Spain of the EPA AQI.

Advanced Intelligent Systems for Sustainable Development (AI2SD’2020)

There is no doubt that air pollution harms human health. Municipal areas are the most affected by... more There is no doubt that air pollution harms human health. Municipal areas are the most affected by the degradation of the air quality by discharging anthropogenic gases from transport and industrial activities. This research collected remote sensing data from numerous satellite sensors to efficiently monitor the air quality in near-real-time. This paper deliberates the developed software based on the complex event processing calculating in streaming the air quality level in Morocco and Spain. Therefore, this computer program extracts only useful information rapidly from remote sensing big data helping decision-makers. This investigation takes up also a validation between the air quality measured by the ground station data of Andalucía and Madrid regions and the used satellite sensors data.

Currently, many environmental applications take advantage of remote sensing techniques, particula... more Currently, many environmental applications take advantage of remote sensing techniques, particularly air quality monitoring, climate changes overseeing, and natural disasters prediction. However, a massive volume of remote sensing data is generated in near-real-time; such data are complex and are provided with high velocity and variety. This study aims to confirm that satellite data are big data and proposes a new big data architecture for satellite data processing. In this paper, we mainly focused on the ingestion layer enabling an efficient remote sensing big data preprocessing. As a result, the developed ingestion layer removed eighty-six percent of the unnecessary daily files. Moreover, it eliminated about twenty percent of the erroneous and inaccurate plots, therefore, reducing storage consumption and improving satellite data accuracy. Finally, the processed data was efficiently integrated into a Hadoop storage system.

At present, there is no clear scientific evidence of reliable earthquake precursors that can be u... more At present, there is no clear scientific evidence of reliable earthquake precursors that can be used as an early warning system. However, many studies have also reported the existence of faint signatures that appear to be coupled to the occurrence of earthquakes. These anomalies have traditionally been detected using data from in-situ sensors near high-seismicity regions. On the other hand, remote sensors offer the potential of large spatial coverage and frequent revisit time, allowing the observation of remote areas such as deserts, mountains, polar caps, or the ocean. This chapter revises the state-of-the-art of the understanding of lithosphere-atmosphere-ionosphere coupling. It also presents recent studies by the authors' ongoing investigation on short-to-midterm earthquake precursors. The Earth observation variables discussed are (1) surface temperature anomalies from thermal infrared or microwave radiometer measurements, (2) atmospheric signatures, (3) ionospheric total electron density fluctuations or scintillation measured from GNSS signals, and (4) other geophysical variables, including geomagnetic field fluctuations, changes in the Schumann resonance frequency, or low-frequency electromagnetic radiation. However, despite the seismic hazard risk models that exist and the results shown by these studies, it is still very difficult to predict the occurrence of earthquakes.