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37 pages, 15804 KiB

Open AccessArticle

Ground Electric Field, Atmospheric Weather and Electric Grid Variations in Northeast Greece Influenced by the March 2012 Solar Activity and the Moderate to Intense Geomagnetic Storms

by Georgios Anagnostopoulos, Anastasios Karkanis, Athanasios Kampatagis, Panagiotis Marhavilas, Sofia-Anna Menesidou, Dimitrios Efthymiadis, Stefanos Keskinis, Dimitar Ouzounov, Nick Hatzigeorgiu and Michael Danikas

Remote Sens. 2024, 16(6), 998; https://doi.org/10.3390/rs16060998 - 12 Mar 2024

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Abstract

In a recent paper, we extended a previous study on the solar solar influence to the generation of the March 2012 heatwave in the northeastern USA. In the present study we check the possible relationship of solar activity with the early March 2012 [...] Read more.

In a recent paper, we extended a previous study on the solar solar influence to the generation of the March 2012 heatwave in the northeastern USA. In the present study we check the possible relationship of solar activity with the early March 2012 bad weather in northeast Thrace, Greece. To this end, we examined data from various remote sensing instrumentation monitoring the Sun (SDO satellite), Interplanetary space (ACE satellite), the Earth’s magnetosphere (Earth-based measurements, NOAA-19 satellite), the top of the clouds (Terra and Aqua satellites), and the near ground atmosphere. Our comparative data analysis suggests that: (i) the winter-like weather (rainfall, fast winds, decreased temperature) in Thrace started on 6 March 2012, the same day as the heatwave started in USA, (ii) during the March 2012 winter-like event in Thrace (6–15 March), the ACE satellite recorded enhanced fluxes of solar energetic particles (SEPs), while SOHO and PAMELA recorded solar protons at very high energies (>500 MeV), (iii) Between 3–31 March, the temperature in Alexandoupoli and the ACE/EPAM solar high energy (1.88–4.70 MeV) proton flux were strongly anticorelated (r = −0.75, p = 0.5). (iv) Thrace experienced particularly intense cyclonic circulation, during periods of magnetic storms on 8–10 and 12–13 March, which occurred after the arrival at ACE of two interplanetary shock waves, on March 8 and March 11, respectively, (v) at the beginning of the two above mentioned periods large atmospheric electric fields were recorded, with values ranging between ~−2000 V/m and ~1800 V/m on 8 March, (vi) the winter-like weather on 8–10 March 2012 occurred after the detection of the main SEP event related with a coronal mass ejection released in interplanetary space as a result of intense solar flare activity observed by SDO on 7 March 2012, (vi) the 8–10 March weather was related with a deep drop of ~63 °C in the cloud top temperature measured by MODIS/Terra, which favors strong precipitation. Finally, we analyzed data from the electric power network in Thrace (~41°N) and we found, for the first time sudden voltage changes of ~3.5 kV in the electric grid in Greece, during the decay phase of the March 2012 storm series. We discuss the winter-like March 2012 event in Thrace regarding the influence of solar cosmic rays on the low troposphere mediated by positive North Atlantic Oscillation (NAO). Finally, we infer that the novel finding of the geomagnetic effects on the electric power grid in Thrace may open a new window into space weather applications research. Full article

(This article belongs to the Special Issue Space-Based Earth Observations for Disaster Risk and Emergency Monitoring)

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25 pages, 6575 KiB

Open AccessArticle

Development of an Index for Forest Fire Risk Assessment Considering Hazard Factors and the Hazard-Formative Environment

by Adu Gong, Zhiqing Huang, Longfei Liu, Yuqing Yang, Wanru Ba and Haihan Wang

Remote Sens. 2023, 15(21), 5077; https://doi.org/10.3390/rs15215077 - 24 Oct 2023

Viewed by 1350

Abstract

Forest fires are characterized by a rapid and devastating nature, underscoring the practical significance of forest fire risk monitoring. Currently, forest fire risk assessments inadequately account for non-meteorological hazard factors, lack the hazard-formative environment and contextual disaster knowledge for fire occurrence mechanisms. In [...] Read more.

Forest fires are characterized by a rapid and devastating nature, underscoring the practical significance of forest fire risk monitoring. Currently, forest fire risk assessments inadequately account for non-meteorological hazard factors, lack the hazard-formative environment and contextual disaster knowledge for fire occurrence mechanisms. In response, based on MODIS products, we augmented the FFDI (forest fire danger index) with the RDST (regional disaster system theory) and selected various fire risk indicators, including lightning. MOD14 was used for the correlation analysis of fire and its indicators. Through the amalgamation of the analytic hierarchy process (AHP), the entropy method, and the minimal relative entropy theory, we formulated the CFFRI (composite forest fire risk index) and assessed forest fire risks spanning from 2010 to 2019 in Southwest China, which were validated with historical disaster data and MCD64. The findings revealed that the CFFRI yields consistently higher overall fire risk values, with 89% falling within the high-risk category and 11% within the moderate-risk category. In contrast, the FFDI designated 56% of cases as fourth-tier fire risks and 44% as third-tier fire risks. Notably, the CFFRI achieved an accuracy of 85% in its calculated results, while the FFDI attained 76%. These outcomes robustly demonstrate a superior applicability of the CFFRI compared with the traditional FFDI. Full article

(This article belongs to the Special Issue Space-Based Earth Observations for Disaster Risk and Emergency Monitoring)

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22 pages, 10124 KiB

Open AccessArticle

Vegetation Dynamics and Its Response to Extreme Climate on the Inner Mongolian Plateau during 1982–2020

by Rihan Su, Enliang Guo, Yongfang Wang, Shan Yin, Yulong Bao, Zhongyi Sun, Naren Mandula and Yuhai Bao

Remote Sens. 2023, 15(15), 3891; https://doi.org/10.3390/rs15153891 - 06 Aug 2023

Cited by 2 | Viewed by 957

Abstract

The impact of extreme climate change on terrestrial ecosystems continues to intensify. This study was conducted to understand extreme climate–vegetation interactions under exacerbated frequency, severity, and duration of extreme climatic events. The Inner Mongolian Plateau (IMP) was selected due to its sensitive natural [...] Read more.

The impact of extreme climate change on terrestrial ecosystems continues to intensify. This study was conducted to understand extreme climate–vegetation interactions under exacerbated frequency, severity, and duration of extreme climatic events. The Inner Mongolian Plateau (IMP) was selected due to its sensitive natural location, which is particularly vulnerable to climate change. Based on the Normalized Difference Vegetation Index (NDVI) and daily meteorological station data from 1982 to 2020, changes in the patterns of vegetation and extreme climate in the three ecological zones (forest, steppe, and desert steppe) of the IMP were identified. Furthermore, the effects of extreme climate on vegetation were quantified using correlation analysis and a geographical detector. The results showed that the annual NDVI of 95.1%, 50.6%, and 19.5% of the area increased significantly in the forest, steppe, and desert steppe, respectively. The Tx90p (warm days) and Tn90p (warm nights) increased significantly at the rate of 0.21 and 0.235 day·yr⁻¹, respectively, while the Tx10p (cold days) and Tn10p (cold nights) showed a significantly decreasing trend at the rate of −0.105 and −0.117 day·yr⁻¹. An extreme warming phenomenon was observed in all extreme temperature indices on the IMP. The results of both the correlation analysis and factor detector indicated that extreme temperature intensity and frequency greatly affected forest vegetation. In contrast, extreme precipitation intensity and frequency were relatively more important to the vegetation of the desert steppe. The lag in NDVI response to extreme temperature intensity was not less than three months in the IMP; however, extreme precipitation intensity exhibited a two-month time lag in the NDVI. This study can improve our understanding of extreme climate–vegetation interactions, provide theoretical support for disaster mitigation, and aid in understanding the ecological environment of the IMP. Full article

(This article belongs to the Special Issue Space-Based Earth Observations for Disaster Risk and Emergency Monitoring)

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18 pages, 7948 KiB

Open AccessArticle

Monitoring Glacier Lake Outburst Flood (GLOF) of Lake Merzbacher Using Dense Chinese High-Resolution Satellite Images

by Changjun Gu, Suju Li, Ming Liu, Kailong Hu and Ping Wang

Remote Sens. 2023, 15(7), 1941; https://doi.org/10.3390/rs15071941 - 05 Apr 2023

Cited by 5 | Viewed by 2478

Abstract

Establishing an effective real-time monitoring and early warning system for glacier lake outburst floods (GLOFs) requires a full understanding of their occurrence mechanism. However, the harsh conditions and hard-to-reach locations of these glacial lakes limit detailed fieldwork, making satellite imagery a critical tool [...] Read more.

Establishing an effective real-time monitoring and early warning system for glacier lake outburst floods (GLOFs) requires a full understanding of their occurrence mechanism. However, the harsh conditions and hard-to-reach locations of these glacial lakes limit detailed fieldwork, making satellite imagery a critical tool for monitoring. Lake Mercbacher, an ice-dammed lake in the central Tian Shan mountain range, poses a significant threat downstream due to its relatively high frequency of outbursts. In this study, we first monitored the daily changes in the lake area before the 2022 Lake Mercbacher outburst. Additionally, based on historical satellite images from 2014 to 2021, we calculated the maximum lake area (MLA) and its changes before the outburst. Furthermore, we extracted the proportion of floating ice and water area during the period. The results show that the lake area of Lake Mercbacher would first increase at a relatively low speed (0.01 km²/day) for about one month, followed by a relatively high-speed increase (0.04 km²/day) until reaching the maximum, which would last for about twenty days. Then, the lake area would decrease slowly until the outburst, which would last five days and is significant for early warning. Moreover, the floating ice and water proportion provides more information about the outburst signals. In 2022, we found that the floating ice area increased rapidly during the early warning stage, especially one day before the outburst, accounting for about 50% of the total lake area. Historical evidence indicates that the MLA shows a decreasing trend, and combining it with the outburst date and climate data, we found that the outburst date shows an obvious advance trend (6 days per decade) since 1902, caused by climate warming. Earlier melting results in an earlier outburst. This study provides essential references for monitoring Lake Mercbacher GLOFs and building an effective early warning system. Full article

(This article belongs to the Special Issue Space-Based Earth Observations for Disaster Risk and Emergency Monitoring)

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28 pages, 9498 KiB

Open AccessArticle

Air Pollution Patterns Mapping of SO₂, NO₂, and CO Derived from TROPOMI over Central-East Europe

by Beata Wieczorek

Remote Sens. 2023, 15(6), 1565; https://doi.org/10.3390/rs15061565 - 13 Mar 2023

Cited by 3 | Viewed by 3487

Abstract

The analysis of changes in the level of air pollution concentration allows for the control of air quality and its compliance with the normative requirements. Currently, every country in Europe implements air quality monitoring. However, during emergencies in areas that are often difficult [...] Read more.

The analysis of changes in the level of air pollution concentration allows for the control of air quality and its compliance with the normative requirements. Currently, every country in Europe implements air quality monitoring. However, during emergencies in areas that are often difficult to monitor, the only source of information is geospatial data obtained by means of Earth observation techniques. The aims of this study were to estimate the amounts of pollutant concentrations and develop a pattern of spatiotemporal changes in Central and Eastern Europe in Poland and Ukraine. Due to the ongoing military operations in Ukraine, it is an area that is difficult to access. Pollution from industrial facilities, fires, collapsed buildings, and the use of explosive weapons poses a threat to air quality. Additionally, the impact of war on air pollution concentration levels remains unclear. This work characterized the changes in the distribution of sulfur dioxide, nitrogen dioxide and carbon monoxide concentrations in 2018–2022 in local zones in both countries. Publicly available TROPOMI-S5 satellite data were used for this study, which were compared with measurements from ground stations in Poland. It has been estimated that the concentration of NO₂ (+0.67 ± 0.47 µmol/m²) in Poland has increased and the level of SO₂ and CO have decreased in both studied areas: in Poland (−161.67 ± 5.48 µmol/m², −470.85 ± 82.81 µmol/m²) and in Ukraine (−32.56 ± 23.51 µmol/m², −438.04 ± 80.76 µmol/m²). The concentration of NO₂ in Ukraine has decreased by −0.28 ± 0.21 µmol/m². Full article

(This article belongs to the Special Issue Space-Based Earth Observations for Disaster Risk and Emergency Monitoring)

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20 pages, 15565 KiB

Open AccessArticle

Mapping of Flood-Prone Areas Utilizing GIS Techniques and Remote Sensing: A Case Study of Duhok, Kurdistan Region of Iraq

by Aumed Rahman M Amen, Andam Mustafa, Dalshad Ahmed Kareem, Hasan Mohammed Hameed, Ayub Anwar Mirza, Michał Szydłowski and Bala Kawa M. Saleem

Remote Sens. 2023, 15(4), 1102; https://doi.org/10.3390/rs15041102 - 17 Feb 2023

Cited by 11 | Viewed by 5534

Abstract

One of the most common types of natural disaster, floods can happen anywhere on Earth, except in the polar regions. The severity of the damage caused by flooding can be reduced by putting proper management and protocols into place. Using remote sensing and [...] Read more.

One of the most common types of natural disaster, floods can happen anywhere on Earth, except in the polar regions. The severity of the damage caused by flooding can be reduced by putting proper management and protocols into place. Using remote sensing and a geospatial methodology, this study attempts to identify flood-vulnerable areas of the central district of Duhok, Iraq. The analytical hierarchy process (AHP) technique was used to give relative weights to 12 contributing parameters, including elevation, slope, distance from the river, rainfall, land use land cover, soil, lithology, topographic roughness index, topographic wetness index, aspect, the sediment transport index, and the stream power index in order to calculate the Flood Hazard Index (FHI). The relative importance of each criterion was revealed by a sensitivity analysis of the parameter values. This research developed a final flood susceptibility map and identified high-susceptible zones. This was classified anywhere from very low to very high classifications for its potential flood hazard. The generated map indicates that 44.72 km² of the total land area of the study area in Duhok city has a very high susceptibility to flooding, and that these areas require significant attention from government authorities in order to reduce flood vulnerability. Full article

(This article belongs to the Special Issue Space-Based Earth Observations for Disaster Risk and Emergency Monitoring)

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17 pages, 5073 KiB

Open AccessArticle

An Influence of Snow Covers on the Radar Interferometry Observations of Industrial Infrastructure: Norilsk Thermal Power Plant Case

by Alexander Zakharov and Liudmila Zakharova

Remote Sens. 2023, 15(3), 654; https://doi.org/10.3390/rs15030654 - 22 Jan 2023

Cited by 1 | Viewed by 1276

Abstract

This manuscript presents the results of the study of snow covers’ influence on the interferometric measurements of the stability of industrial infrastructure in the vicinity of Norilsk city, Russia. Fuel tanks of the Norilsk thermal power plant (TPP) were selected as an object [...] Read more.

This manuscript presents the results of the study of snow covers’ influence on the interferometric measurements of the stability of industrial infrastructure in the vicinity of Norilsk city, Russia. Fuel tanks of the Norilsk thermal power plant (TPP) were selected as an object of study due to a well-known accident when about 20,000 tons of diesel fuel spilled from one of the tanks. Sentinel-1 synthetic aperture radar data acquired over the territory of Norilsk TPP were used in the DInSAR study of the possible displacements of the tanks that could be the cause of the tank’s damage. For twelve days, radar interferograms that were generated in the study covered the cold and warm seasons of 2018–2020, including the catastrophic event—the rupture of the tank with diesel fuel—in order to shed light on the possible impact of the area subsidence because of permafrost thaw under the tanks. As the tank walls and adjacent concrete base constituted the virtual dihedral corner reflector, the accumulation of snow on the surface near the tanks created a distorting effect on the results of monitoring the stability of the tank’s location. Three models of snow layer within the dihedral proposed could help explain the deviations in the signal amplitude and phase in the case of snowfalls occurring between radar observations. We propose three ways to minimize the influence of snow on interferometric measurements. One of them, the selection of the radar data acquired in proper observation conditions, made it possible to assess the stability of the mutual location of the tanks. Among the most important processing and analysis results in the paper is a conclusion about the high stability of the fuel tank’s location on the yearly time interval, including the troubleshooting tank. Full article

(This article belongs to the Special Issue Space-Based Earth Observations for Disaster Risk and Emergency Monitoring)

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34 pages, 3832 KiB

Open AccessArticle

Susceptibility Assessment of Flash Floods: A Bibliometrics Analysis and Review

by Le Duan, Chao Liu, Hui Xu, Pan Huali, Haizhi Liu, Xufeng Yan, Tiegang Liu, Zhengli Yang, Gang Liu, Xiaoai Dai, Donghui Zhang, Xiao Fu, Xuemei Liu and Heng Lu

Remote Sens. 2022, 14(21), 5432; https://doi.org/10.3390/rs14215432 - 28 Oct 2022

Cited by 5 | Viewed by 2472

Abstract

A flash flood disaster is one of the most destructive natural disasters. With the increase in extreme rainfall events, more and more areas will be threatened by flash floods. The flash flood susceptibility assessment is the basis of flash flood risk assessment and [...] Read more.

A flash flood disaster is one of the most destructive natural disasters. With the increase in extreme rainfall events, more and more areas will be threatened by flash floods. The flash flood susceptibility assessment is the basis of flash flood risk assessment and is also an important step in flash flood disaster management. Based on Citespace analysis tools, this study made a bibliometric and visualized analysis of 305 documents collected in the core collection of Web of Science in the past 15 years, including the analysis of the number of publications and citation frequency, influence analysis, keyword analysis, author co-citation analysis, and institutional co-operation analysis. This paper summarizes the current research status and future development trend of flash flood susceptibility assessment from five key research subfields, including assessment scale, assessment unit, assessment index, assessment model, and model assessment method, discusses the analysis of the application of remote sensing and GIS in flash flood susceptibility assessment, discusses the problems encountered in the current research of the five subfields, and provides suggestions for flash flood hazard control. Full article

(This article belongs to the Special Issue Space-Based Earth Observations for Disaster Risk and Emergency Monitoring)

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13 pages, 32664 KiB

Open AccessTechnical Note

Three-Dimensional Deformation of the 2023 Turkey Mw 7.8 and Mw 7.7 Earthquake Sequence Obtained by Fusing Optical and SAR Images

by Qi An, Guangcai Feng, Lijia He, Zhiqiang Xiong, Hao Lu, Xiuhua Wang and Jianchao Wei

Remote Sens. 2023, 15(10), 2656; https://doi.org/10.3390/rs15102656 - 19 May 2023

Cited by 10 | Viewed by 2992

Abstract

In February 2023, Mw 7.8 and Mw 7.7 earthquakes struck southeastern Turkey. Generating a coseismic 3D deformation field that can directly reflect the characteristics of surface deformation is important for revealing the movement mode of a seismogenic fault and analyzing the focal mechanism. [...] Read more.

In February 2023, Mw 7.8 and Mw 7.7 earthquakes struck southeastern Turkey. Generating a coseismic 3D deformation field that can directly reflect the characteristics of surface deformation is important for revealing the movement mode of a seismogenic fault and analyzing the focal mechanism. Optical image sub-pixel correlation (SPC) only captures deformation in the horizontal direction, and SAR image pixel offset tracking (POT) obtains range deformation that is not sensitive to north–south deformation signals. Thus, neither of them can capture the complete 3D deformation alone. Combining them may be able to allow the monitoring of 3D deformation. In this study, we used Sentinel-2 optical images to obtain the horizontal deformation (east–west and north–south) and Sentinel-1 and ALOS-2 data to extract the range and azimuth offsets. The least-squares method was used to fuse the optical and SAR offsets to obtain the 3D deformation field of the 2023 Turkey earthquake sequence, which indicates that the two events were both left-lateral strike-slip earthquakes. The surface deformation caused by the two large earthquakes is mainly in the east–west direction. In the vertical direction, the two earthquakes caused a small-magnitude uplift and subsidence. The findings in this paper can be used as a reference for the study of coseismic 3D deformation. Full article

(This article belongs to the Special Issue Space-Based Earth Observations for Disaster Risk and Emergency Monitoring)

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17 pages, 26072 KiB

Open AccessTechnical Note

Drought Vulnerability Curves Based on Remote Sensing and Historical Disaster Dataset

by Huicong Jia, Fang Chen, Enyu Du and Lei Wang

Remote Sens. 2023, 15(3), 858; https://doi.org/10.3390/rs15030858 - 03 Feb 2023

Viewed by 1801

Abstract

As drought vulnerability assessment is fundamental to risk management, it is urgent to develop scientific and reasonable assessment models to determine such vulnerability. A vulnerability curve is the key to risk assessment of various disasters, connecting analysis of hazard and risk. To date, [...] Read more.

As drought vulnerability assessment is fundamental to risk management, it is urgent to develop scientific and reasonable assessment models to determine such vulnerability. A vulnerability curve is the key to risk assessment of various disasters, connecting analysis of hazard and risk. To date, the research on vulnerability curves of earthquakes, floods and typhoons is relatively mature. However, there are few studies on the drought vulnerability curve, and its application value needs to be further confirmed and popularized. In this study, on the basis of collecting historical disaster data from 52 drought events in China from 2009 to 2013, three drought remote sensing indexes were selected as disaster-causing factors; the affected population was selected to reflect the overall disaster situation, and five typical regional drought vulnerability curves were constructed. The results showed that (1) in general, according to the statistics of probability distribution, most of the normalized difference vegetation index (NDVI) and the temperature vegetation drought index (TVDI) variance ratios were concentrated between 0 and ~0.15, and most of the enhanced vegetation index (EVI) variance ratios were concentrated between 0.15 and ~0.6. From a regional perspective, the NDVI and EVI variance ratio values of the northwest inland perennial arid area (NW), the southwest mountainous area with successive years of drought (SW), and the Hunan Hubei Jiangxi area with sudden change from drought to waterlogging (HJ) regions were close and significantly higher than the TVDI variance ratio values. (2) Most of the losses (drought at-risk populations, DRP) were concentrated in 0~0.3, with a cumulative proportion of about 90.19%. At the significance level, DRP obeys the Weibull distribution through hypothesis testing, and the parameters are optimal. (3) The drought vulnerability curve conformed to the distribution rule of the logistic curve, and the line shape was the growth of the loss rate from 0 to 1. It was found that the arid and ecologically fragile area in the farming pastoral ecotone (AP) region was always a high-risk area with high vulnerability, which should be the focus of drought risk prevention and reduction. The study reduces the difficulty of developing the vulnerability curve, indicating that the method can be widely used to other regions in the future. Furthermore, the research results are of great significance to the accurate drought risk early warning or whether to implement the national drought disaster emergency rescue response. Full article

(This article belongs to the Special Issue Space-Based Earth Observations for Disaster Risk and Emergency Monitoring)

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