Egyptian Journal of Remote Sensing and Space Sciences最新文献

{"title":"GNSS geodetic velocity prediction using ensemble tree models in Abu-Dabbab, Egypt","authors":"Alshimaa Y. Abo Gharbia ,&nbsp;Ahmed Gomaa ,&nbsp;Mohamed Saleh ,&nbsp;Ashraf Elkutb Mousa ,&nbsp;Ibrahim Atiatallah Abbas ,&nbsp;Moatamad R. Hassan","doi":"10.1016/j.ejrs.2025.05.008","DOIUrl":"10.1016/j.ejrs.2025.05.008","url":null,"abstract":"<div><div>Estimating Global Navigation Satellite System (GNSS) velocities is essential for understanding crustal deformation and motion. This work employs the Random Forest (RF) and Gradient Boosting Machines (GBM), two machine learning (ML) techniques, to estimate horizontal velocities at specific locations using GNSS data. Crustal deformation data were acquired through Global Positioning System (GPS) techniques, with positions of eleven stations determined from eight GPS measurement campaigns. Eighty percent of the GNSS velocity data from stations in the Abu-Dabbab region were used for training, while twenty percent were reserved for testing the models. RF demonstrated superior performance in estimating east geodetic GPS velocities with the lowest mean absolute error (MAE), while GBM excelled in predicting north geodetic GPS velocities, also achieving the lowest MAE. The maximum differences between model-predicted and reference velocities were 0.09 mm/year for RF and 0.1 mm/year for GBM, underscoring the precision of these methods. Despite data constraints the study confirms the efficacy of ML techniques, particularly RF and GBM, in providing accurate GNSS velocity estimates.</div></div>","PeriodicalId":48539,"journal":{"name":"Egyptian Journal of Remote Sensing and Space Sciences","volume":"28 2","pages":"Pages 337-347"},"PeriodicalIF":3.7,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144106304","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}

{"title":"Enhancing motion compensation in spaceborne SAR imaging","authors":"Shimaa Abd El-Monem ,&nbsp;Ahmed Azouz ,&nbsp;Alaaeldin S. Hassan ,&nbsp;El-Sayed Soliman A. Said ,&nbsp;Abdelhady A. Ammar","doi":"10.1016/j.ejrs.2025.05.005","DOIUrl":"10.1016/j.ejrs.2025.05.005","url":null,"abstract":"<div><div>Synthetic Aperture Radar (SAR) is a widely utilized remote sensing technology, offering robust operational efficiency under all weather conditions and independent of daylight. Ideally, the SAR platform maintains a linear trajectory at a constant altitude and velocity. However, this idealization is compromised for spaceborne SAR systems, such as those in low Earth orbit (LEO), due to the satellite’s elliptical orbit, which introduces motion errors that degrade image focusing quality. This paper presents a novel approach to enhance first-order motion compensation (MOCO) by addressing the motion errors caused by elliptical orbital dynamics and perturbations. The proposed methodology involves applying three distinct fitting techniques to the invariant range error, a critical parameter in first-order MOCO, and optimizing phase gradients to determine the optimal coefficients for improving image quality metrics. Real-raw SAR data from the Sentinel-1 Level-0 dataset is processed to validate the proposed techniques, and the results are benchmarked against the corresponding Sentinel-1 Level-1 Single Look Complex (SLC) image. The validation is conducted through two approaches: first, image quality assessment using sharpness, contrast, and entropy metrics; and second, quantitative evaluation of azimuth-integrated sidelobe ratio (AISLR), azimuth peak sidelobe ratio (APSLR), and impulse response width (IRW) at two prominent reflective points. The findings indicate a marked enhancement in the image quality parameters, demonstrating the efficacy of the proposed motion compensation and optimization framework.</div></div>","PeriodicalId":48539,"journal":{"name":"Egyptian Journal of Remote Sensing and Space Sciences","volume":"28 2","pages":"Pages 322-336"},"PeriodicalIF":3.7,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144069842","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}

{"title":"Employing both full and partial sub-pixel mapping methods to delineate hydrothermal alteration zones associated with porphyry copper deposits","authors":"Yousef Bahrami,&nbsp;Hossein Hassani,&nbsp;Abbas Maghsoudi","doi":"10.1016/j.ejrs.2025.05.007","DOIUrl":"10.1016/j.ejrs.2025.05.007","url":null,"abstract":"<div><div>The southeastern portion of the Urumieh–Dokhtar magmatic arc (UDMA), known as Kerman Cenozoic magmatic arc (KCMA), is a major host to world-class giant to subeconomic small porphyry copper deposits (PCDs) in Iran. As the KCMA is characterized by well-exposed rocks and sparsely vegetated surfaces, it is an intriguing region for geological remote sensing studies. In particular, mixed pixels are a key source of annoyance in traditional image classification because of a sensor’s immediate field of view restriction and the variety of land cover classes. By evaluating the observed spectrum of mixed pixels, sub-pixel mapping techniques can decompose each mixed pixel and determine the proportion of each component class, and so a classification map with a finer resolution is attainable. This paper endeavors to assess the capability and accuracy of linear spectral unmixing (LSU), multiple endmember spectral mixture analysis (MESMA), and mixture tuned target constrained interference minimized filter analysis (MTTCIMF) to investigate how well these sub-pixel algorithms could identify and map key hydrothermal alteration zones linked with PCDs in the Pariz–Chahargonbad area. Previous works have applied these algorithms widely to hyperspectral data, but few previous works have applied them to multispectral data such as ASTER. In this work, these algorithms were found helpful in the accurate identification of argillic, phyllic, and propylitic alteration zones per validation with field observations, petrographic studies and X-ray diffraction analysis of rock samples.</div></div>","PeriodicalId":48539,"journal":{"name":"Egyptian Journal of Remote Sensing and Space Sciences","volume":"28 2","pages":"Pages 303-321"},"PeriodicalIF":3.7,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144069841","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}

{"title":"Examining social disparities in urban heat exposure in New Orleans, US","authors":"Juthi Rani Mitra ,&nbsp;Md Sariful Islam","doi":"10.1016/j.ejrs.2025.05.006","DOIUrl":"10.1016/j.ejrs.2025.05.006","url":null,"abstract":"<div><div>The urban heat island (UHI) effect is a major concern in large cities, particularly as many cities have experienced extended heatwaves in recent years. This study focuses on disparities in urban heat exposure within the city of New Orleans. Using multitemporal Landsat imagery, this research developed an Urban Heat Risk Index (UHRI) at the block group level. In addition to satellite imagery, this study incorporated socioeconomic and demographic data from the American Community Survey (ACS). To examine the relationship between UHRI and explanatory variables, a spatial lag model was applied with the maximum likelihood (ML) estimation method. The analysis revealed a positive and significant association between UHRI and population density. In contrast, the median household income, the percentage of the population aged five and under, the percentage of owner-occupied homes, and the percentage receiving cash public assistance or food stamps all exhibited a negative and significant relationship with UHRI. This study highlights significant disparities in heat exposure among different socioeconomic groups, with important implications for urban planning and public health. By identifying neighborhoods at higher risk for extreme heat, the findings can inform strategies to reduce vulnerability to heat stress, promote equitable access to green spaces, and guide policies for environmental justice. These insights can support city planners, policymakers, and community leaders in developing interventions that prioritize the needs of vulnerable populations, fostering a more resilient and just urban environment.</div></div>","PeriodicalId":48539,"journal":{"name":"Egyptian Journal of Remote Sensing and Space Sciences","volume":"28 2","pages":"Pages 295-302"},"PeriodicalIF":3.7,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143941532","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}

{"title":"Remote sensing techniques for mapping hydrothermal alteration zones of volcanogenic massive sulfide deposits in Red Sea Hills, NE Sudan","authors":"Musa M.M. Mina ,&nbsp;Ahmed A.A. Osman ,&nbsp;Mohammed A.M. Alnour ,&nbsp;Rowida A.M. Abdalla ,&nbsp;Khalid A.E. Zeinelabdein ,&nbsp;Samia Abdelrahman ,&nbsp;Hassan K.E. Elawad ,&nbsp;Gábor Kovács ,&nbsp;Gabriella B. Kiss","doi":"10.1016/j.ejrs.2025.05.003","DOIUrl":"10.1016/j.ejrs.2025.05.003","url":null,"abstract":"<div><div>The area of our research lies in the Red Sea Hills region in NE Sudan and occupies a central position in the Nubian part of the late Proterozoic Nubian-Arabian Shield. The Red Sea Hills have received considerable studies in structural and remote sensing aspects in the past decades. Most of the studies were conducted to understand the structural evolution and the tectonic development of the Nubian-Arabian Shield in northeast Sudan. However, the link between the structural elements and the mineralization in the area is not well established, and in several parts of the region the identification of mineral deposits is also not well known. Therefore, the present study deals mainly with the determination of mineralization zones and highlights the structural elements of the study area. The processing of Landsat 8 OLI images has included different methods such as band rationing, density slicing, and featured oriented principal component analysis. These methods allowed us to identify the zones of hydrothermal alteration, which could be associated with ore mineralization within the study area. These mapped alteration zones were verified with the aid of the obtained field and geochemical data. Interpretation of the detailed geochemical data set of the study area revealed the presence of Au/Cu/Zn anomalies at most of the perspective locations outlined in the hydrothermal composite map, uniquely supporting the usefulness of remote sensing methods. The structural analysis of the brittle deformation manifestations revealed that the NE–SW fracture system represents the main controlling factor on the occurrence of the mineralization in our research area.</div></div>","PeriodicalId":48539,"journal":{"name":"Egyptian Journal of Remote Sensing and Space Sciences","volume":"28 2","pages":"Pages 280-294"},"PeriodicalIF":3.7,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143927431","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}

{"title":"A q-learning approach for enhanced routing in dynamic LEO satellite networks","authors":"Ahmed E. Riyad ,&nbsp;Medhat Mokhtar ,&nbsp;Mohamed A. Belal ,&nbsp;Mahmoud Mohamed Bahloul","doi":"10.1016/j.ejrs.2025.05.002","DOIUrl":"10.1016/j.ejrs.2025.05.002","url":null,"abstract":"<div><div>As global communication demand rises, Low Earth Orbit (LEO) satellite systems offer high-speed data transmission and extensive coverage options but face routing challenges due to dynamic topologies. This paper introduces a Q-Learning-based routing approach that converts dynamic networks into virtually static topologies at different snapshot intervals. Simulation results on a 66-satellite Starlink constellation demonstrate that Q-Learning outperforms Dijkstra’s algorithm, achieving faster convergence and reduced latency. These findings highlight the potential for Q-Learning in enhancing efficient, cost-effective satellite communications.</div></div>","PeriodicalId":48539,"journal":{"name":"Egyptian Journal of Remote Sensing and Space Sciences","volume":"28 2","pages":"Pages 272-279"},"PeriodicalIF":3.7,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143922132","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}

{"title":"Examining human activities in response to land surface temperature in Sekota watershed, northern Ethiopia","authors":"Mulat Amare Tshayu ,&nbsp;Teshome Betru Tadesse ,&nbsp;Kindu Setalem Meshesha ,&nbsp;Mohammed Habib Afkea ,&nbsp;Mohammed Motuma Assen","doi":"10.1016/j.ejrs.2025.05.004","DOIUrl":"10.1016/j.ejrs.2025.05.004","url":null,"abstract":"<div><div>The alteration of land use/land cover change (LULCC) is an environmental issue that impacts affects ecosystems by increasing the land surface temperature (LST). This study aimed to investigate the influence of human activities on LST in the Sekota watershed northern Ethiopia. This study used Landsat images and a supervised support vector machine (SVM) classification algorithm to map LU/LC and estimate LST. The findings revealed that farmland exhibited the most substantial expansion, with a net gain of 16,970.84 ha, while shrubland experienced the most significant decline, with a net loss of 20,768.57 ha. Moreover, forest cover by 329.73 ha, bare land by 2048.97 ha, and settlements by 131.07 ha increased from 2000 to 2022. The mean LST increased from 32.31 °C in 2000 to 36.01 °C in 2014, followed by a gradual decrease to 34.18 °C in 2022. The overall accuracy and kappa coefficients of the LULC maps were 87.6 % (0.8421), 91.5 % (0.8901), and 92 % (0.8973) in 2000, 2014, and 2022, respectively. This study also investigated the correlation between the normalized difference vegetation index (NDVI) and LST. The results demonstrated a negative relationship, with correlation coefficient R² values of 0.70, 0.65, and 0.75 for 2000, 2014, and 2022, respectively. This indicates that non-vegetated e areas had higher LST levels than forested areas. As a result, it is recommended that government agencies and local communities focus on preserving vegetation cover and adopting practices such as planting perennial fruit crops and implementing agroforestry systems in the study area.</div></div>","PeriodicalId":48539,"journal":{"name":"Egyptian Journal of Remote Sensing and Space Sciences","volume":"28 2","pages":"Pages 261-271"},"PeriodicalIF":3.7,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143921672","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}

{"title":"Integrating PRISMA hyperspectral data with Sentinel-1, Sentinel-2 and Landsat data for mapping crop types and land cover in northeast Thailand","authors":"Savittri Ratanopad Suwanlee ,&nbsp;Zahid Naeem Qaisrani ,&nbsp;Jaturong Som-ard ,&nbsp;Surasak Keawsomsee ,&nbsp;Kemin Kasa ,&nbsp;Narissara Nuthammachot ,&nbsp;Siwa Kaewplang ,&nbsp;Sarawut Ninsawat ,&nbsp;Enrico Borgogno Mondino ,&nbsp;Samuele De Petris ,&nbsp;Filippo Sarvia","doi":"10.1016/j.ejrs.2025.04.005","DOIUrl":"10.1016/j.ejrs.2025.04.005","url":null,"abstract":"<div><div>Accurate crop types and land cover maps are pivotal for effective land management and agricultural policy, particularly in regions with complex agricultural landscapes and small field sizes. Northeast Thailand, a significant agricultural hub, faces challenges in crop classification due to its diverse crop patterns, cloud cover, and smallholder plots. This study integrates satellite data from PRISMA, Sentinel-1 (S1), Sentinel-2 (S2), and Landsat-8/9 (L8/9) imagery to address these challenges. A total of 1305 reference point were randomly collected between November and December 2022 to train and validate the proposed crop classification. Specifically, 15 different combinations using a random forest (RF) classifier were tested. The combination of all datasets achieved the highest overall accuracy (OA) of 91.5 %, followed by S1 + S2 + L8/9 (89.8 %), while PRISMA alone yielded a lower accuracy (63.8 %). The study identified nine dominant land cover classes, with cassava, rice, and sugarcane as primary crops. A strong correlation (r = 0.91) with the official Land Development Department (LDD) statistics demonstrates the robustness of the method. This research highlights the technical advantage of multi-sensor integration in overcoming the limitations of single-sensor data, providing a reliable tool for accurate crop mapping, and supporting sustainable agricultural practices in challenging environments.</div></div>","PeriodicalId":48539,"journal":{"name":"Egyptian Journal of Remote Sensing and Space Sciences","volume":"28 2","pages":"Pages 252-260"},"PeriodicalIF":3.7,"publicationDate":"2025-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143902008","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}

{"title":"Integrating GNSS/IMU and DEM data for precise aerial triangulation: Insights from airborne hybrid systems in upper Egypt","authors":"Abdelrahman Ali Wahba ,&nbsp;Ibrahim Fouad Ahmed ,&nbsp;Mohamed Amin Abdelfatah ,&nbsp;Ashraf Mohammed Ahmed Sahrawi ,&nbsp;Gamal Saber El-Fiky","doi":"10.1016/j.ejrs.2025.04.004","DOIUrl":"10.1016/j.ejrs.2025.04.004","url":null,"abstract":"<div><div>Digital photogrammetry primarily aims to extract three-dimensional coordinates (X, Y, Z or E, N, H) of feature points, which is crucial for mapping applications. The Aerial Triangulation (AT) process for aerial images must be adjusted with high precision to achieve accurate measurements. Enhancing the accuracy of Global Navigation Satellite System (GNSS) and Inertial Measurement Unit (IMU) sensors significantly improves the AT process. Additionally, Airborne Light Detection and Ranging (LiDAR) data can produce a high-resolution Digital Elevation Model (DEM), which aids in initializing the aerial triangulation process. Modern services, such as Real-Time eXtended (RTX), are also used for GNSS/IMU corrections, further refining their accuracy.</div><div>The novelty of the current research is based on an end-to-end procedure for enhancing AT accuracy, especially in variable terrain height regions, using a hybrid airborne system. The scope is to use GNSS/IMU data coupled with a DEM from airborne LiDAR to initialize the AT process. The study cases were based in Maghagha City, Minia Governorate, Egypt, where a flight mission was carried out in 2017 using the Trimble AX60 system. This system integrates a photogrammetric camera and laser scanner with GNSS/IMU sensors. The aerial triangulation of the images was processed using MATCH-AT software. The accuracy of the results was evaluated using checkpoints. The findings indicate that AT using GNSS/IMU corrected data yields the best accuracy in AT, particularly in the Z direction, with an accuracy enhancement in check points residuals, compared with AT without using GNSS/IMU. Consequently, the final Root Mean Square (RMS) improved from 0.25 m to 0.17 m in E, from 0.2 m to 0.17 m in N, and from 3 m to 0.5 m in H. That demonstrates the significant benefit of incorporating GNSS/IMU data in improving the precision of three-dimensional spatial measurements. In addition, the DEM initialization improved the RMS slightly, also, the matching between aerial images during the triangulation process gets better values along the iteration time.</div></div>","PeriodicalId":48539,"journal":{"name":"Egyptian Journal of Remote Sensing and Space Sciences","volume":"28 2","pages":"Pages 240-251"},"PeriodicalIF":3.7,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143873676","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}

{"title":"Role of sentinel-2 remotely sensed data in assisting stratigraphic subdivision of a Paleogene carbonate sequence, Jabal Hafit, UAE-Oman","authors":"Osman Abdelghany ,&nbsp;Abdel-Rahman Fowler ,&nbsp;Karim Abdelmalik ,&nbsp;Abdelaziz Al Azzani ,&nbsp;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}