Pub Date : 2025-04-25DOI: 10.1016/j.ejrs.2025.04.003
Osman Abdelghany , Abdel-Rahman Fowler , Karim Abdelmalik , Abdelaziz Al Azzani , Mahmoud Abu Saima
SENTINEL-2 remote sensing data for Jabal Hafit mountain, south of Al Ain, UAE, were obtained for the purpose of mapping the stratigraphic units in this monotonous carbonate-dominant Lower Eocene to Oligocene sequence. The data was processed using spectral reflectance curves collected from representative rock samples. After resampling of measured spectral curves of studied samples, guided by an algorithm to find the sensitive bands, a Principal Component-based false-colour image was obtained and then improved by Decorrelation Stretch (DS). The resulting image was interpreted in a small study area in Oman where the geology was uninterrupted by human activities. Correlation of colour bands in the study area with known stratigraphic units for the region was applied to the DS image for the entire Jabal Hafit mountain area. The results show excellent discrimination of the formations and members of the Hafit Paleogene succession. Other features revealed include the extent and lateral facies changes shown by these units.
{"title":"Role of sentinel-2 remotely sensed data in assisting stratigraphic subdivision of a Paleogene carbonate sequence, Jabal Hafit, UAE-Oman","authors":"Osman Abdelghany , Abdel-Rahman Fowler , Karim Abdelmalik , Abdelaziz Al Azzani , Mahmoud Abu Saima","doi":"10.1016/j.ejrs.2025.04.003","DOIUrl":"10.1016/j.ejrs.2025.04.003","url":null,"abstract":"<div><div>SENTINEL-2 remote sensing data for Jabal Hafit mountain, south of Al Ain, UAE, were obtained for the purpose of mapping the stratigraphic units in this monotonous carbonate-dominant Lower Eocene to Oligocene sequence. The data was processed using spectral reflectance curves collected from representative rock samples. After resampling of measured spectral curves of studied samples, guided by an algorithm to find the sensitive bands, a Principal Component-based false-colour image was obtained and then improved by Decorrelation Stretch (DS). The resulting image was interpreted in a small study area in Oman where the geology was uninterrupted by human activities. Correlation of colour bands in the study area with known stratigraphic units for the region was applied to the DS image for the entire Jabal Hafit mountain area. The results show excellent discrimination of the formations and members of the Hafit Paleogene succession. Other features revealed include the extent and lateral facies changes shown by these units.</div></div>","PeriodicalId":48539,"journal":{"name":"Egyptian Journal of Remote Sensing and Space Sciences","volume":"28 2","pages":"Pages 228-239"},"PeriodicalIF":3.7,"publicationDate":"2025-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143870168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-22DOI: 10.1016/j.ejrs.2025.04.001
Karen Escalona , Rodrigo Abarca-del-Río , María Pedreros-Guarda , Oscar Parra
Aquatic plant invasions endanger lake biodiversity and ecosystem services, resulting in significant economic losses for local communities. Therefore, it is crucial to accurately delineate the extent and frequency of development, but traditional methods are costly and in remote areas. Cost-effective methods, such as satellite monitoring are required. This study uses a Random Forest classification model in the Google Earth Engine (GEE) with Landsat 7 and 8 images to monitoring aquatic vegetation invasion in freshwater ecosystems. The methodology automates the selection of training samples through a dynamic adjustment that incorporates the Otsu-Canny Edge algorithms applied to a vegetation index, allowing for monthly updates while minimizing human bias. Applying this methodology to Lake Maracaibo, Venezuela, between 2013 and 2021, there was a significant increase in floating aquatic vegetation cover, from ≤10 % in 2013 to 25.63 % in 2021, particularly along the northwest coast and the Strait of Maracaibo. This increase could be attributed to a combination of natural processes like precipitation patterns and increased anthropogenic inputs from human activities. The model achieved high accuracy (>0.80), as evidenced by the confusion matrix and cross-sensor comparison. This approach provides a tool for continuous long-term monitoring that can be applied to other eutrophic lakes, improving our understanding of the effects of invasive vegetation, and assisting resource managers and policymakers in developing sustainable management strategies.
{"title":"Spatiotemporal variations of aquatic vegetation in Maracaibo Lake: Remote sensing and machine learning approach with Google Earth Engine","authors":"Karen Escalona , Rodrigo Abarca-del-Río , María Pedreros-Guarda , Oscar Parra","doi":"10.1016/j.ejrs.2025.04.001","DOIUrl":"10.1016/j.ejrs.2025.04.001","url":null,"abstract":"<div><div>Aquatic plant invasions endanger lake biodiversity and ecosystem services, resulting in significant economic losses for local communities. Therefore, it is crucial to accurately delineate the extent and frequency of development, but traditional methods are costly and in remote areas. Cost-effective methods, such as satellite monitoring are required. This study uses a Random Forest classification model in the Google Earth Engine (GEE) with Landsat 7 and 8 images to monitoring aquatic vegetation invasion in freshwater ecosystems. The methodology automates the selection of training samples through a dynamic adjustment that incorporates the Otsu-Canny Edge algorithms applied to a vegetation index, allowing for monthly updates while minimizing human bias. Applying this methodology to Lake Maracaibo, Venezuela, between 2013 and 2021, there was a significant increase in floating aquatic vegetation cover, from ≤10 % in 2013 to 25.63 % in 2021, particularly along the northwest coast and the Strait of Maracaibo. This increase could be attributed to a combination of natural processes like precipitation patterns and increased anthropogenic inputs from human activities. The model achieved high accuracy (>0.80), as evidenced by the confusion matrix and cross-sensor comparison. This approach provides a tool for continuous long-term monitoring that can be applied to other eutrophic lakes, improving our understanding of the effects of invasive vegetation, and assisting resource managers and policymakers in developing sustainable management strategies.</div></div>","PeriodicalId":48539,"journal":{"name":"Egyptian Journal of Remote Sensing and Space Sciences","volume":"28 2","pages":"Pages 214-227"},"PeriodicalIF":3.7,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143860265","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-16DOI: 10.1016/j.ejrs.2025.04.002
Durmuş Ali Çelik , Arif Oguz Altunel
Alterations in land-cover significantly influence global climate fluctuations. To utilize land resources rationally and sustainably, it is essential to identify the open-source remote sensing capabilities, the resulting products, and assess their geographical accuracies. This study conceptualized over Kastamonu province in northwestern Türkiye, focused on comparing three of the high-resolution (10 m) land-cover products; Environmental Systems Research Institute (ESRI) 2022, European Space Agency (ESA) World-Cover 2021 and Google-The World Resources Institute, Dynamic Word (DW) 2022, and 2022 Google Earth imagery were utilized for spatial comparisons. The overall accuracy (OA) and Kappa coefficient were computed, along with additional accuracy assessment metrics. OAs of land-cover maps (local accuracy), from highest to lowest, were ESRI2022; 76 %, ESA2021; 75.8 % and DW2022; 73.4 %. The Kappa coefficients for the three land-cover maps were calculated as 0.703 (very good) for ESA2021 and 0.69 and 0.68 (very good) for ESRI2022 and DW2022, respectively. The maximum user accuracy value was recorded at 92.23 % for the crops and 92.21 % for the built area classes in ESA2021. A comparison was also conducted among the corresponding class definitions. The most exemplary portrayal was observed in the categories of water, trees, and crops. Consequently, ESRI, ESA, and DW datasets were found to be fairly comparable to one another and can serve as auxiliary data in research pertaining to water, forestry and cultivated land resources.
{"title":"Is dynamic world a contender in global land-cover making race? A swift field assessment from Kastamonu, Türkiye","authors":"Durmuş Ali Çelik , Arif Oguz Altunel","doi":"10.1016/j.ejrs.2025.04.002","DOIUrl":"10.1016/j.ejrs.2025.04.002","url":null,"abstract":"<div><div>Alterations in land-cover significantly influence global climate fluctuations. To utilize land resources rationally and sustainably, it is essential to identify the open-source remote sensing capabilities, the resulting products, and assess their geographical accuracies. This study conceptualized over Kastamonu province in northwestern Türkiye, focused on comparing three of the high-resolution (10 m) land-cover products; Environmental Systems Research Institute (ESRI) 2022, European Space Agency (ESA) World-Cover 2021 and Google-The World Resources Institute, Dynamic Word (DW) 2022, and 2022 Google Earth imagery were utilized for spatial comparisons. The overall accuracy (OA) and Kappa coefficient were computed, along with additional accuracy assessment metrics. OAs of land-cover maps (local accuracy), from highest to lowest, were ESRI2022; 76 %, ESA2021; 75.8 % and DW2022; 73.4 %. The Kappa coefficients for the three land-cover maps were calculated as 0.703 (very good) for ESA2021 and 0.69 and 0.68 (very good) for ESRI2022 and DW2022, respectively. The maximum user accuracy value was recorded at 92.23 % for the crops and 92.21 % for the built area classes in ESA2021. A comparison was also conducted among the corresponding class definitions. The most exemplary portrayal was observed in the categories of water, trees, and crops. Consequently, ESRI, ESA, and DW datasets were found to be fairly comparable to one another and can serve as auxiliary data in research pertaining to water, forestry and cultivated land resources.</div></div>","PeriodicalId":48539,"journal":{"name":"Egyptian Journal of Remote Sensing and Space Sciences","volume":"28 2","pages":"Pages 205-213"},"PeriodicalIF":3.7,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143837895","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-26DOI: 10.1016/j.ejrs.2025.03.002
Ameereh Seyedzadeh , Mohamed Okasha , Alia Alblooshi , Wan Faris Aizat , Abdul Halim Jallad , Erwin Sulaeman
This study examines the thermal management strategies employed by AlAinSat-1 to endure extreme space conditions. It provides an in-depth analysis of the satellite’s thermal behavior through numerical simulations and validates its ability to function in space using experimental testing. AlAinSat-1 is a nanosatellite designed in the shape of a cube, equipped with an Earth observation payload. The thermal analysis was performed using Siemens NX software, following a structured process that included idealization, meshing, and the application of boundary conditions. Simulations were conducted to evaluate the CubeSat’s performance in the worst-case hot and cold scenarios, predicting the temperature range required for mission success. Simulation results confirm that AlAinSat-1 can withstand extreme space conditions, with all components remaining within their operational temperature ranges. To validate these findings, bakeout and thermal vacuum cycling tests were performed using a small Thermal Vacuum Chamber (TVAC). The bakeout test, conducted at 50 °C for five hours, aimed to eliminate volatile contaminants from the CubeSat’s sensitive components, reducing the risk of outgassing. This test achieved a 0.1 % total mass loss, indicating success. The thermal vacuum cycling test involved four cycles ranging from −20 °C to + 50 °C, with a dwell time of one hour per cycle. These tests confirmed the operational temperature range of the CubeSat’s components. The experimental results were consistent with the simulations, demonstrating that all components of AlAinSat-1 functioned effectively within their designated temperature limits. This alignment validates the thermal management approach and ensures the CubeSat’s readiness for space deployment.
{"title":"Thermal analysis and experimental validation of the thermal subsystem of AlAinSat-1","authors":"Ameereh Seyedzadeh , Mohamed Okasha , Alia Alblooshi , Wan Faris Aizat , Abdul Halim Jallad , Erwin Sulaeman","doi":"10.1016/j.ejrs.2025.03.002","DOIUrl":"10.1016/j.ejrs.2025.03.002","url":null,"abstract":"<div><div>This study examines the thermal management strategies employed by AlAinSat-1 to endure extreme space conditions. It provides an in-depth analysis of the satellite’s thermal behavior through numerical simulations and validates its ability to function in space using experimental testing. AlAinSat-1 is a nanosatellite designed in the shape of a cube, equipped with an Earth observation payload. The thermal analysis was performed using Siemens NX software, following a structured process that included idealization, meshing, and the application of boundary conditions. Simulations were conducted to evaluate the CubeSat’s performance in the worst-case hot and cold scenarios, predicting the temperature range required for mission success. Simulation results confirm that AlAinSat-1 can withstand extreme space conditions, with all components remaining within their operational temperature ranges. To validate these findings, bakeout and thermal vacuum cycling tests were performed using a small Thermal Vacuum Chamber (TVAC). The bakeout test, conducted at 50 °C for five hours, aimed to eliminate volatile contaminants from the CubeSat’s sensitive components, reducing the risk of outgassing. This test achieved a 0.1 % total mass loss, indicating success. The thermal vacuum cycling test involved four cycles ranging from −20 °C to + 50 °C, with a dwell time of one hour per cycle. These tests confirmed the operational temperature range of the CubeSat’s components. The experimental results were consistent with the simulations, demonstrating that all components of AlAinSat-1 functioned effectively within their designated temperature limits. This alignment validates the thermal management approach and ensures the CubeSat’s readiness for space deployment.</div></div>","PeriodicalId":48539,"journal":{"name":"Egyptian Journal of Remote Sensing and Space Sciences","volume":"28 2","pages":"Pages 185-204"},"PeriodicalIF":3.7,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143705505","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-20DOI: 10.1016/j.ejrs.2025.03.001
Amanda Tri Persada , Yulius , Syamsul B. Agus , Hadiwijaya L. Salim , Ira Dillenia , Taslim Arifin , Aida Heriati , Joko Prihantono , Dini Purbani , Sri Endah Purnamaningtyas , Didik Wahju Hendro Tjahjo , Muhammad Ramdhan , Siti Hajar Suryawati , Ary Wahyono , Ulung Jantama Wisha , Zulfiandi , Fery Kurniawan
The significance of this research lies in its contribution to Olipier cultural site vulnerability caused by coastal erosion and climate change impacts in East Belitung, Indonesia. Therefore, this study employs the Coastal Vulnerability Index (CVI) and Cultural Resource Vulnerability (CRV) methods to assess coastal vulnerability and site susceptibility, which integrates physical parameters, such as elevation, beach slope, geomorphology, land use, tidal range, significant wave height, shoreline change, distance from shoreline to sites, and sea-level rise. The CVI analysis results indicate that approximately 12.68 km of the observed coastline is very highly vulnerable, 8.72 km is highly vulnerable, and the remnant 10.91 km coastline is categorized as low vulnerability. On the other hand, the CRV method emphasizes specific vulnerable locations, identifying that approximately 53.34 % oil refineries are highly vulnerable zones due to their proximity to the shoreline, low elevation, and slope. This study also underscores the importance of proactive conservation measures, whereby implementing coastal protection structures, mangrove rehabilitation, and coral reef transplantation are possible. Collaboration between local and central governments is essential for effective coastal management and conservation of cultural heritage sites. Overall, this research provides valuable insights for coastal management strategies to mitigate risks and preserve cultural heritage in East Belitung Regency.
{"title":"Olipier cultural site vulnerability analysis in East Belitung, Indonesia: Cultural resources vulnerability (CRV) methods","authors":"Amanda Tri Persada , Yulius , Syamsul B. Agus , Hadiwijaya L. Salim , Ira Dillenia , Taslim Arifin , Aida Heriati , Joko Prihantono , Dini Purbani , Sri Endah Purnamaningtyas , Didik Wahju Hendro Tjahjo , Muhammad Ramdhan , Siti Hajar Suryawati , Ary Wahyono , Ulung Jantama Wisha , Zulfiandi , Fery Kurniawan","doi":"10.1016/j.ejrs.2025.03.001","DOIUrl":"10.1016/j.ejrs.2025.03.001","url":null,"abstract":"<div><div>The significance of this research lies in its contribution to Olipier cultural site vulnerability caused by coastal erosion and climate change impacts in East Belitung, Indonesia. Therefore, this study employs the Coastal Vulnerability Index (CVI) and Cultural Resource Vulnerability (CRV) methods to assess coastal vulnerability and site susceptibility, which integrates physical parameters, such as elevation, beach slope, geomorphology, land use, tidal range, significant wave height, shoreline change, distance from shoreline to sites, and sea-level rise. The CVI analysis results indicate that approximately 12.68 km of the observed coastline is very highly vulnerable, 8.72 km is highly vulnerable, and the remnant 10.91 km coastline is categorized as low vulnerability. On the other hand, the CRV method emphasizes specific vulnerable locations, identifying that approximately 53.34 % oil refineries are highly vulnerable zones due to their proximity to the shoreline, low elevation, and slope. This study also underscores the importance of proactive conservation measures, whereby implementing coastal protection structures, mangrove rehabilitation, and coral reef transplantation are possible. Collaboration between local and central governments is essential for effective coastal management and conservation of cultural heritage sites. Overall, this research provides valuable insights for coastal management strategies to mitigate risks and preserve cultural heritage in East Belitung Regency.</div></div>","PeriodicalId":48539,"journal":{"name":"Egyptian Journal of Remote Sensing and Space Sciences","volume":"28 2","pages":"Pages 167-184"},"PeriodicalIF":3.7,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143682320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-12DOI: 10.1016/j.ejrs.2025.02.003
Muhammad Zainuddin Lubis , Muhammad Ghazali , Andrean V.H. Simanjuntak , Nelly F. Riama , Gumilang R. Pasma , Asep Priatna , Husnul Kausarian , Made Wedanta Suryadarma , Sri Pujiyati , Fredrich Simanungkalit , Batara , Kutubuddin Ansari , Punyawi Jamjareegulgarn
Our study investigates the decadal and seasonal variability of sea surface height (SSH) and sea surface temperature (SST) in the Gulf of Thailand (GoT) using data from CMEMS from 1993 to 2021. We employed statistical analyses utilizing GLM and GAM to assess the variables comprehensively. The reveals a significant upward trend in SSH, increasing from ∼0.79 m in 1993–1998 to ∼0.89 m in 2017–2021, highlighting the impacts of climate change. SST analysis revealed fluctuations, with a maximum reaching ∼30.6 °C in 2019–2020, correlating with climatic events such as El Niño. Our study results at station 1 (near Bangkok) showed that the average SSH in 1998 during strong El Niño years was equal to 0.82 m, while the maximum SST was equal to 29.89 °C. Seasonal patterns indicated SSH peaks in DJF and SON at ∼0.92 m, while SST peaked in spring MAM and summer JJA at ∼30.7 °C. Volume transport analysis showed significant variability, with 0.3634 Sv (0–55 m) at longitude 99°E-107° E and latitude 6° N, indicating complex circulation patterns influenced by bathymetry and wind. Time series analysis revealed an average SSH increase of 0.0038 m/year, with a high pseudo-R-squared of 0.99. Our findings underscore the critical influence of climate variability on oceanographic conditions in the GoT, emphasizing the need for ongoing monitoring to address the implications of rising sea levels and temperature fluctuations. In conjunction with increased SSH, the rising SST heightens the risk of flooding in low-lying areas, exacerbating vulnerabilities for local populations and necessitating adaptive management strategies to mitigate these impacts.
{"title":"Decadal and seasonal oceanographic trends influenced by climate changes in the Gulf of Thailand","authors":"Muhammad Zainuddin Lubis , Muhammad Ghazali , Andrean V.H. Simanjuntak , Nelly F. Riama , Gumilang R. Pasma , Asep Priatna , Husnul Kausarian , Made Wedanta Suryadarma , Sri Pujiyati , Fredrich Simanungkalit , Batara , Kutubuddin Ansari , Punyawi Jamjareegulgarn","doi":"10.1016/j.ejrs.2025.02.003","DOIUrl":"10.1016/j.ejrs.2025.02.003","url":null,"abstract":"<div><div>Our study investigates the decadal and seasonal variability of sea surface height (SSH) and sea surface temperature (SST) in the Gulf of Thailand (GoT) using data from CMEMS from 1993 to 2021. We employed statistical analyses utilizing GLM and GAM to assess the variables comprehensively. The reveals a significant upward trend in SSH, increasing from ∼0.79 m in 1993–1998 to ∼0.89 m in 2017–2021, highlighting the impacts of climate change. SST analysis revealed fluctuations, with a maximum reaching ∼30.6 °C in 2019–2020, correlating with climatic events such as El Niño. Our study results at station 1 (near Bangkok) showed that the average SSH in 1998 during strong El Niño years was equal to 0.82 m, while the maximum SST was equal to 29.89 °C. Seasonal patterns indicated SSH peaks in DJF and SON at ∼0.92 m, while SST peaked in spring MAM and summer JJA at ∼30.7 °C. Volume transport analysis showed significant variability, with 0.3634 Sv (0–55 m) at longitude 99°E-107° E and latitude 6° N, indicating complex circulation patterns influenced by bathymetry and wind. Time series analysis revealed an average SSH increase of 0.0038 m/year, with a high pseudo-R-squared of 0.99. Our findings underscore the critical influence of climate variability on oceanographic conditions in the GoT, emphasizing the need for ongoing monitoring to address the implications of rising sea levels and temperature fluctuations. In conjunction with increased SSH, the rising SST heightens the risk of flooding in low-lying areas, exacerbating vulnerabilities for local populations and necessitating adaptive management strategies to mitigate these impacts.</div></div>","PeriodicalId":48539,"journal":{"name":"Egyptian Journal of Remote Sensing and Space Sciences","volume":"28 2","pages":"Pages 151-166"},"PeriodicalIF":3.7,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143611517","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-01DOI: 10.1016/j.ejrs.2025.02.002
Nirmawana Simarmata , Ketut Wikantika , Trika Agnestasia Tarigan , Muhammad Aldyansyah , Rizki Kurnia Tohir , Adam Irwansyah Fauzi , Anggita Rahma Fauzia
Ineffective land use in coastal areas negatively impacts the environment and destroys mangrove ecosystems, contributing to increasing greenhouse gas emissions and decreasing carbon sequestration. This study aimed to monitor the land use changes in mangrove areas with Landsat data using several machine learning (ML) methods. According to the random forest (RF), gradient tree boosting (GTB), and classification and regression trees algorithms (CART), the mangrove area exhibited significant fluctuations over the study period, with the largest expansion observed from 1999 to 2008 (4,240.57 ha), followed by a slight increase in 2023 (368.36 ha from 2019). Accuracy assessment revealed distinct performance levels across the models. The RF algorithm demonstrated the highest overall accuracy (OA) of 98.8 %, with kappa values ranging from 0.96 to 0.98, indicating high consistency and reliable predictions over time. The CART algorithm, while accurate, showed more variability, especially between 1991 and 1994, with an OA ranging from 85.3 % to 92.5 % and kappa values between 0.92 and 0.96. The GTB algorithm had moderate performance, with OA values between 85.6 % and 95.7 % and kappa values ranging from 0.92 to 0.96, suggesting reliable results but with some inconsistency compared to RF. The RF algorithm’s superior OA and consistency make it the most suitable long-term land cover monitoring method. Future studies can benefit from incorporating RF in assessing ecosystem changes, including carbon sequestration potential in mangrove forests.
{"title":"Comparison of random forest, gradient tree boosting, and classification and regression trees for mangrove cover change monitoring using Landsat imagery","authors":"Nirmawana Simarmata , Ketut Wikantika , Trika Agnestasia Tarigan , Muhammad Aldyansyah , Rizki Kurnia Tohir , Adam Irwansyah Fauzi , Anggita Rahma Fauzia","doi":"10.1016/j.ejrs.2025.02.002","DOIUrl":"10.1016/j.ejrs.2025.02.002","url":null,"abstract":"<div><div>Ineffective land use in coastal areas negatively impacts the environment and destroys mangrove ecosystems, contributing to increasing greenhouse gas emissions and decreasing carbon sequestration. This study aimed to monitor the land use changes in mangrove areas with Landsat data using several machine learning (ML) methods. According to the random forest (RF), gradient tree boosting (GTB), and classification and regression trees algorithms (CART), the mangrove area exhibited significant fluctuations over the study period, with the largest expansion observed from 1999 to 2008 (4,240.57 ha), followed by a slight increase in 2023 (368.36 ha from 2019). Accuracy assessment revealed distinct performance levels across the models. The RF algorithm demonstrated the highest overall accuracy (OA) of 98.8 %, with kappa values ranging from 0.96 to 0.98, indicating high consistency and reliable predictions over time. The CART algorithm, while accurate, showed more variability, especially between 1991 and 1994, with an OA ranging from 85.3 % to 92.5 % and kappa values between 0.92 and 0.96. The GTB algorithm had moderate performance, with OA values between 85.6 % and 95.7 % and kappa values ranging from 0.92 to 0.96, suggesting reliable results but with some inconsistency compared to RF. The RF algorithm’s superior OA and consistency make it the most suitable long-term land cover monitoring method. Future studies can benefit from incorporating RF in assessing ecosystem changes, including carbon sequestration potential in mangrove forests.</div></div>","PeriodicalId":48539,"journal":{"name":"Egyptian Journal of Remote Sensing and Space Sciences","volume":"28 1","pages":"Pages 138-150"},"PeriodicalIF":3.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143551910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-07DOI: 10.1016/j.ejrs.2025.02.001
Jamal A.H. Doski
The deformation of Earth’s surface caused by earthquakes stands as a critical geological hazard in regions characterized by active tectonic structures. This study investigates the impact of a low-to-moderate magnitude earthquake (Mw 4.9) that occurred on January 26, 2021, in the Sinjar – Hasakah area (N Iraq and NE Syria). This seismic event marks the most significant occurrence in the study area over the past 48 years. The earthquake’s moment tensor solution suggests the presence of a right-lateral (dextral) strike-slip fault. 4 Sentinel-1A SAR images were processed by the DInSAR technique to analyze the surface deformation and identify the seismogenic fault of the 26 January 2021 earthquake. The most significant deformation observed along these active faults ranged from – 7.56 cm (subsidence) to + 3.75 cm (uplift) in the ascending orbit, and from – 4.56 cm (subsidence) to + 4.61 cm (uplift) in the descending orbit along the Line of Sight (LOS). It is inferred that the Hasakah seismogenic fault is responsible for the 26 January 2021 earthquake. This fault is a NW-trending, steeply dipping seismically active dextral strike-slip basement fault that formed during the Late Pliocene structural inversion. It extends over 120 km from the vicinity of Hasakah city in the northwest into the epicentral area in the southeast, traversing the boundary between the Sinjar and Abd El Aziz uplifts. Moreover, this seismogenic fault intersects with an active E-trending, S-dipping thrust basement fault that cuts through the northern limbs of both the Abd El Aziz and Sinjar anticlines.
{"title":"Surface deformation of the 26 January 2021 earthquake in the Sinjar – Hasakah Area, N Iraq and NE Syria, from Sentinel‑1A InSAR images","authors":"Jamal A.H. Doski","doi":"10.1016/j.ejrs.2025.02.001","DOIUrl":"10.1016/j.ejrs.2025.02.001","url":null,"abstract":"<div><div>The deformation of Earth’s surface caused by earthquakes stands as a critical geological hazard in regions characterized by active tectonic structures. This study investigates the impact of a low-to-moderate magnitude earthquake (Mw 4.9) that occurred on January 26, 2021, in the Sinjar – Hasakah area (N Iraq and NE Syria). This seismic event marks the most significant occurrence in the study area over the past 48 years. The earthquake’s moment tensor solution suggests the presence of a right-lateral (dextral) strike-slip fault. 4 Sentinel-1A SAR images were processed by the DInSAR technique to analyze the surface deformation and identify the seismogenic fault of the 26 January 2021 earthquake. The most significant deformation observed along these active faults ranged from – 7.56 cm (subsidence) to + 3.75 cm (uplift) in the ascending orbit, and from – 4.56 cm (subsidence) to + 4.61 cm (uplift) in the descending orbit along the Line of Sight (LOS). It is inferred that the Hasakah seismogenic fault is responsible for the 26 January 2021 earthquake. This fault is a NW-trending, steeply dipping seismically active dextral strike-slip basement fault that formed during the Late Pliocene structural inversion. It extends over 120 km from the vicinity of Hasakah city in the northwest into the epicentral area in the southeast, traversing the boundary between the Sinjar and Abd El Aziz uplifts. Moreover, this seismogenic fault intersects with an active E-trending, S-dipping thrust basement fault that cuts through the northern limbs of both the Abd El Aziz and Sinjar anticlines.</div></div>","PeriodicalId":48539,"journal":{"name":"Egyptian Journal of Remote Sensing and Space Sciences","volume":"28 1","pages":"Pages 128-137"},"PeriodicalIF":3.7,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143298435","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-27DOI: 10.1016/j.ejrs.2024.11.003
Mohamed I. Abdelaal , Min Bao , Mohamed Saleh , Mengdao Xing
Harnessing high-precision spaceborne InSAR data, this study investigates the seismic impacts of the Ms 6.9 Menyuan earthquake in Qinghai, China, on January 8, 2022. The earthquake occurred at the intersection of the Lenglongling (LLLF) and Tuolaishan (TLSF) faults within the Qilian Haiyuan Fault (QL-HYF) zone, causing extensive infrastructure damage but no fatalities. Previous studies explored the step-over rupture zone and slip distribution of the Menyuan event but often relied on oversimplified rectangular dislocation models, insufficient for capturing complex fault ruptures. This simplification impedes accurate representation of curved fault segments in the QL-HYF zone, leading to unclear slip distribution estimates, particularly at the transition from LLLF strike-slip to TLSF thrust behavior. To address these limitations, this study employs a 3D triangulated angular dislocation slip-inversion approach in an isotropic half-space, enabling precise modeling of curved fault geometries. Leveraging Differential InSAR (D-InSAR) and Pixel Offset Tracking (POT), we reconstructed the earthquake’s 3D displacement field and extracted surface fault traces, informing our angular dislocation model for accurate coseismic slip distribution. Our results revealed significant horizontal displacement, with 38.5 cm of left-lateral movement accompanied by a 4 cm downward thrust. The slip model showed 2.7 m of slip along the LLLF and 0.8 m along the TLSF, concentrated at shallow depths between 2 and 7 km, highlighting surface rupture. The transition zone between the faults acted as a valve, modulating rupture progression and controlling energy release. These findings refine the understanding of coseismic deformation and slip distribution, supporting seismic hazard mitigation and emergency response strategies.
{"title":"New insights into the Menyuan Ms6.9 Earthquake, China: 3D slip inversion and fault modeling based on InSAR remote sensing approach","authors":"Mohamed I. Abdelaal , Min Bao , Mohamed Saleh , Mengdao Xing","doi":"10.1016/j.ejrs.2024.11.003","DOIUrl":"10.1016/j.ejrs.2024.11.003","url":null,"abstract":"<div><div>Harnessing high-precision spaceborne InSAR data, this study investigates the seismic impacts of the Ms 6.9 Menyuan earthquake in Qinghai, China, on January 8, 2022. The earthquake occurred at the intersection of the Lenglongling (LLLF) and Tuolaishan (TLSF) faults within the Qilian Haiyuan Fault (QL-HYF) zone, causing extensive infrastructure damage but no fatalities. Previous studies explored the step-over rupture zone and slip distribution of the Menyuan event but often relied on oversimplified rectangular dislocation models, insufficient for capturing complex fault ruptures. This simplification impedes accurate representation of curved fault segments in the QL-HYF zone, leading to unclear slip distribution estimates, particularly at the transition from LLLF strike-slip to TLSF thrust behavior. To address these limitations, this study employs a 3D triangulated angular dislocation slip-inversion approach in an isotropic half-space, enabling precise modeling of curved fault geometries. Leveraging Differential InSAR (D-InSAR) and Pixel Offset Tracking (POT), we reconstructed the earthquake’s 3D displacement field and extracted surface fault traces, informing our angular dislocation model for accurate coseismic slip distribution. Our results revealed significant horizontal displacement, with 38.5 cm of left-lateral movement accompanied by a 4 cm downward thrust. The slip model showed 2.7 m of slip along the LLLF and 0.8 m along the TLSF, concentrated at shallow depths between 2 and 7 km, highlighting surface rupture. The transition zone between the faults acted as a valve, modulating rupture progression and controlling energy release. These findings refine the understanding of coseismic deformation and slip distribution, supporting seismic hazard mitigation and emergency response strategies.</div></div>","PeriodicalId":48539,"journal":{"name":"Egyptian Journal of Remote Sensing and Space Sciences","volume":"28 1","pages":"Pages 116-127"},"PeriodicalIF":3.7,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143101573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-24DOI: 10.1016/j.ejrs.2025.01.003
Carolle Fomekong Lambou , Carolle Fomekong Lambou , Jorelle Larissa Meli’i , Harlin Ekoro Nkoungou , Kasi Njeudjang , Andre Michel Pouth Nkoma , Philippe Njandjock Nouck
The development of remote sensing, with its many applications, combined with field data collected by geologists, geophysicists and geotechnical scientists, is now contributing to sustainable development in the mining, infrastructure and civil protection sectors. This study integrates remote sensing and the audiomagnetotelluric (AMT) method to identify faults lubricated or potentially lubricated by water in the vicinity of a dam. The data set includes SRTM_DEM images and AMT data from seven stations collected in the study area. The results from remote sensing show 284 lineaments with a main NE-SW direction, including 17 corresponding to existing faults in the area. The lineament density map shows that stations A1, A3 and A7 are located in the most fractured zones. The Bahr dimensional analysis shows that, at the same frequencies, Swift skew values of less than 0.1 and two-dimensionality parameter values of greater than 0.1 are observed at stations A3, A5 and A7, suggesting the presence of 2D structures correlating with the faults at these stations, oriented NE-SW, NE-SW and NNE-SSW respectively. In addition, the 2D and 3D resistivity models make it possible to distinguish at what depth the faults highlighted can be lubricated by water in the study area containing a total of 39 faults, 17 of which are normal and may be partially or fully lubricated depending on whether they interact with the hydrographic or drainage network. These identified lubricated faults need further study, as they could induce weak earthquakes.
{"title":"Identifying water-lubricated faults in the vicinity of a dam","authors":"Carolle Fomekong Lambou , Carolle Fomekong Lambou , Jorelle Larissa Meli’i , Harlin Ekoro Nkoungou , Kasi Njeudjang , Andre Michel Pouth Nkoma , Philippe Njandjock Nouck","doi":"10.1016/j.ejrs.2025.01.003","DOIUrl":"10.1016/j.ejrs.2025.01.003","url":null,"abstract":"<div><div>The development of remote sensing, with its many applications, combined with field data collected by geologists, geophysicists and geotechnical scientists, is now contributing to sustainable development in the mining, infrastructure and civil protection sectors. This study integrates remote sensing and the audiomagnetotelluric (AMT) method to identify faults lubricated or potentially lubricated by water in the vicinity of a dam. The data set includes SRTM_DEM images and AMT data from seven stations collected in the study area. The results from remote sensing show 284 lineaments with a main NE-SW direction, including 17 corresponding to existing faults in the area. The lineament density map shows that stations A1, A3 and A7 are located in the most fractured zones. The Bahr dimensional analysis shows that, at the same frequencies, Swift skew values of less than 0.1 and two-dimensionality parameter values of greater than 0.1 are observed at stations A3, A5 and A7, suggesting the presence of 2D structures correlating with the faults at these stations, oriented NE-SW, NE-SW and NNE-SSW respectively. In addition, the 2D and 3D resistivity models make it possible to distinguish at what depth the faults highlighted can be lubricated by water in the study area containing a total of 39 faults, 17 of which are normal and may be partially or fully lubricated depending on whether they interact with the hydrographic or drainage network. These identified lubricated faults need further study, as they could induce weak earthquakes.</div></div>","PeriodicalId":48539,"journal":{"name":"Egyptian Journal of Remote Sensing and Space Sciences","volume":"28 1","pages":"Pages 99-115"},"PeriodicalIF":3.7,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143101572","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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