Big data and remote sensing: A new software of ingestion

Semlali, B.E. Boudriki; Amrani, Chaker El

doi:10.11591/ijece.v11i2.pp1521-1530

Cited by 8 publications

(5 citation statements)

References 22 publications

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“…Statistical downscaling (Wang Q. et al, 2020) helps to find the external variables of Mourtzios et al (2021) consumption patterns identified based on remote sensing and is comparable with the results of satellite image-based analyzes (Semlali and El Amrani, 2021). And comparable to other approaches (Jimenez et al, 2019), which strengthens confidence in the models (Qin and Chi, 2020).…”

Section: The Importance Of the System Of Systems Approachsupporting

confidence: 67%

“…Agricultural satellite imagery applications (Majidi et al, 2021) can be transferred to air quality satellite monitoring (Semlali and El Amrani, 2021), or time-series data (Ise et al, 2020) can be used to plan better agricultural interventions. By implication, satellitebased support plays an important role in modeling agricultural water management (Ismail et al, 2020), but disaster news (Park et al, 2020) also helps provide a deeper understanding of social involvement.…”

Section: The Importance Of the System Of Systems Approachmentioning

confidence: 99%

“…Climate-friendly urban planning (Milojevic-Dupont et al, 2020), monitoring the energy demand of buildings (Gouveia and Palma, 2019), and defining disaster resilience (Sasaki et al, 2020) play an important role in achieving sustainable cities and communities (SDG11). The Climate Action goal (SDG13) tackles most data gaps, so research such as linking satellite images to Semlali and El Amrani (2021) with air quality, preprocessing them (Meraner et al, 2020;Qin and Chi, 2020;Semlali et al, 2020), the analysis of time series data (Ise et al, 2020) and its exploration (Joshi et al, 2019), downscaling (Wang Q. et al, 2020) techniques, enrichment of precipitation and temperature data (Jimenez et al, 2019), tracking the movement of clouds (Xie Y. et al, 2019), or just using IoT sensors (Mabrouki et al, 2021) are all key in creating a strategy to support the achievement of the climate goal. For the sustainability of life below water (SDG14), marine life prediction models (Coro et al, 2020) and human coastal activity (Kubo et al, 2020) can be integrated.…”

Section: The Importance Of the System Of Systems Approachmentioning

confidence: 99%

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The Applicability of Big Data in Climate Change Research: The Importance of System of Systems Thinking

Sebestyén

Czvetkó

Abonyi

2021

Front. Environ. Sci.

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The aim of this paper is to provide an overview of the interrelationship between data science and climate studies, as well as describes how sustainability climate issues can be managed using the Big Data tools. Climate-related Big Data articles are analyzed and categorized, which revealed the increasing number of applications of data-driven solutions in specific areas, however, broad integrative analyses are gaining less of a focus. Our major objective is to highlight the potential in the System of Systems (SoS) theorem, as the synergies between diverse disciplines and research ideas must be explored to gain a comprehensive overview of the issue. Data and systems science enables a large amount of heterogeneous data to be integrated and simulation models developed, while considering socio-environmental interrelations in parallel. The improved knowledge integration offered by the System of Systems thinking or climate computing has been demonstrated by analysing the possible inter-linkages of the latest Big Data application papers. The analysis highlights how data and models focusing on the specific areas of sustainability can be bridged to study the complex problems of climate change.

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Section: The Importance Of the System Of Systems Approachsupporting

confidence: 67%

Section: The Importance Of the System Of Systems Approachmentioning

confidence: 99%

Section: The Importance Of the System Of Systems Approachmentioning

confidence: 99%

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The Applicability of Big Data in Climate Change Research: The Importance of System of Systems Thinking

Sebestyén

Czvetkó

Abonyi

2021

Front. Environ. Sci.

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“…The collected data have been ingested following the following steps. First, the SNR data is extracted from the NetCDF [36] files using the SAT-ETL-Integrator software [37], [38], and data filtering is conducted for ocean-only pixels. Erroneous and poor-quality data are filtered out, and then S4 is derived from the SNR, as explained in Step 5.…”

Section: Figure 1 the General Architecture Of S4 Data Processing And ...mentioning

confidence: 99%

On the Correlation Between Earthquakes and Prior Ionospheric Scintillations Over the Ocean: A Study Using GNSS-R Data Between 2017 and 2021

Boudriki Semlali,

Molina,

Park

et al. 2024

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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From 1980 to 2021, earthquakes have caused more than 846,000 casualties and about US$ 661 billion in economic losses. At present, there are no reliable earthquake precursors to generate alerts. Currently, the link between earthquakes and Total Electron Content (TEC) variations measured by Global Navigation Satellite Systems (GNSS) monitoring ground stations has been studied. However, GNSS ground-based monitoring stations are irregularly disseminated around the globe with significant gaps, particularly in the ocean's regions. In this study, we analyze ionospheric intensity scintillation anomalies as potential proxies of earthquakes. NASA CYGNSS GNSS-R (Reflectometry) acquired by CYGNSS/DDMI (Delay Doppler Mapping Instrument) from 2017 to 2021 have been used to calculate and analyze the anomalies in the S4 parameter over ocean areas affected by earthquakes. More than 30,000 ocean earthquakes within ±40° in latitude and with a magnitude larger than M4 have been examined.The daily planetary geomagnetic index Kp was used to discard data that may be disturbed due to space weather conditions. Additionally, a daily sea wind speed mask was used to eliminate sea states that impact the signal reflectivity. The Standard Deviation (STD) and the Interquartile (IQT) time series methods have been used to detect these S4 anomalies. The confusion matrix, the Receiver Operating Curve (ROC), and some other Figures of Merit (FoM) have been used for the first time to evaluate and improve the performance of the prediction parameters and identify the optimum configuration to be used as a potential proxy of earthquake occurrence. As a result, a small, but detectable positive S4 anomaly was detected between 1 and 7 days before the earthquakes under study.

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“…These instruments have different spatial (SPR), spectral (STR), and temporal resolutions (TMR) [22], as detailed in Table 1. Step 2: Data acquisition from the Earth Observing System Data and Information System (EOSDIS) of the National Aeronautics and Space Administration (NASA) [23]. This operation takes approximately 15 to 30 min, depending on the data transfer rate and the internet bandwidth [24], depending on the satellite sensor's data latency, and the availability of the data center and data transmission [21].…”

Section: General Architecture For Data Acquisition and Processingmentioning

confidence: 99%

First Results on the Systematic Search of Land Surface Temperature Anomalies as Earthquakes Precursors

et al. 2023

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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.

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Big data and remote sensing: A new software of ingestion

Cited by 8 publications

References 22 publications

The Applicability of Big Data in Climate Change Research: The Importance of System of Systems Thinking

The Applicability of Big Data in Climate Change Research: The Importance of System of Systems Thinking

On the Correlation Between Earthquakes and Prior Ionospheric Scintillations Over the Ocean: A Study Using GNSS-R Data Between 2017 and 2021

First Results on the Systematic Search of Land Surface Temperature Anomalies as Earthquakes Precursors

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