Egyptian Journal of Remote Sensing and Space Sciences最新文献

Land surface temperature (LST) is a critical geo-parameter in terrestrial environmental interaction processes, directly related to land cover change (LCC) which modifies surface energy balance. In this study, LST data from 2003 to 2019 were reconstructed in the Sichuan Basin with average R² of 0.85 (daytime) and 0.91 (nighttime), effectively filling in the missing pixels and reducing the noise components. Emerging hot spot analysis (EHSA) and land cover transfer matrix were utilized to analyze the multi-patterns of LST spatiotemporal evolution and responses to LCC. Results indicate that LST hot spots are concentrated in low-altitude basin floor and are dominated by sporadic hot spots. Cold spots are mainly in marginal high-elevation mountains, but the dominant pattern varies with time scale. The largest proportions of hot and cold spots are found in summer (>46 %) and autumn (>29 %), respectively. Moreover, the significant upward and downward trends of LST cold and hot spots are most prominent in western plain and marginal mountains, respectively, and have the largest coverage in summer and autumn, respectively. In total LCC area, cropland-to-forest (CF), cropland-to-impervious (CI), and forest-to-cropland (FC) account for 93.55 %. Among them, CI significantly promotes the aggregation and upward trend of daytime LST hot spots. CF and FC have the strongest effect of aggregating LST cold spots and cooling LST in daytime, with CF being more effective. The information can serve as a reference for regional planning and climate change mitigation measures.

Human-driven Greenhouse gases (GHGs) are the most significant contributor to climate change. World countries and Egypt are moving towards achieving sustainable development goals (SDGs) 2030, and 2050, to reach Net-Zero emissions. Based on satellite observations, this research assesses and monitors the GHG emissions induced by human activities in Egypt. Different satellite sensors were utilized in this study to obtain Methane (CH₄), Carbon Dioxide (CO₂) amounts during 2015–2022. To get a deeper insight into the effects of anthropogenic activities on CO₂ and CH₄ amounts, they were correlated with land use and land cover, fire incidents, and industrial activities in Egypt. Results revealed a noticeable increase in CH₄ and CO₂ emissions over the country with a maximum level in 2022. CO₂ has a seasonal variation mode, with the highest amounts in spring reaching 0.000409 CO₂/mol dry-air. As well, the high CH₄ concentration fluctuates all the year-round, with a peak around 1890 ppbv in August. The high levels of GHGs mostly concentrated in the Nile Delta and Nile Valley, where most of the anthropogenic activities are existing. Fire incidents, industries, and land cover change maps showed a spatial matching with the high emission zones. However, the emissions are increasing in Egypt it does not exceed the global average. In conclusion, unmanaged human activities in Egypt increased GHGs release and affected environmental sustainability. This study attempts to better understand the ambient environment in Egypt and support the decision-makers with full insight into the GHG emission hotspots in the country to mitigate their release into the atmosphere and achieve Net-Zero emissions.

Understanding urban sprawl and its drivers is crucial for sustainable urban development. Most studies on Chinese urbanization have focused on coastal areas, paying little attention to urban centers in western China. This study examines urban expansion based on the Google Earth Engine (GEE), remotely sensed image, urban expansion model, and analysis of buffer and quadrant location in the Geographic Information System (GIS). Additionally, driving forces of urban expansion are examined based on the principle component analysis (PCA). Results indicate that urban land area increased more than 5.60 times, reaching 124,723 ha, an increase of over 400 % during 1990–2020. The urban expansion rate and intensity significantly increased and exhibited spatio-temporal heterogeneity. We identified that urban spatial expansion patterns changed from patch filling to patch border expansion, and urban expansion direction was mainly in the southern, northeastern, southwestern, and northwestern regions, extending along the traffic corridor, ring road, and adjacent cities. We suggest that economic development, population, and urbanization have become the driving factors of urban expansion. The GEE provides a new geographic processing algorithm based on massive image datasets, facilitating remote sensing processing. The results revealed that Chengdu is following trends witnessed in coastal cities of China; however, the significance of various drivers of urban expansion in these cities differs from that of the eastern cities. This study will help formulate policies for better urban land management and sustainable land development.

The acquisition of landslide inventory represents a pivotal challenge in landslide susceptibility mapping. Existing landslide susceptibility maps(LSMs) predominantly rely on manually obtained landslide inventories, leading to an overdependence on expert insights and susceptibilities to topographic and geomorphic influences. In regions characterized by steep terrain, obtaining a landslide inventory can be arduous or even unattainable, subsequently constraining the utility of LSMs. Addressing the limitations of conventional LSMs, this study introduces an innovative method for landslide inventory compilation and LSM creation, utilizing Small Baselines Subset Interferometry Synthetic Aperture Radar(SBAS-InSAR) technology. The study area selected for illustration is the Dongchuan district, notorious for frequent landslide occurrences. The application of SBAS-InSAR facilitated the extraction of surface deformation data, subsequently enabling the selection of landslide deformation points as samples. These samples underwent analysis through a particle swarm optimization-backpropagation neural network(PSO-BPNN) guided by deformation thresholds and the landslide developmental environment. This produced the LSM for the Dongchuan district. Subsequent validation of the LSM employed both qualitative and quantitative measures. Results elucidate that the LSM, as derived from the presented approach, primarily highlights high to very high susceptibility zones in landslide-prone areas, mirroring the spatial distribution of historical landslides. The method also achieved a commendable accuracy(ACC) of 79.59% and an area under the curve(AUC) value of 0.88. Notably, the landslide density exhibited a direct correlation with increasing susceptibility class. Such findings align with previous studies, endorsing the feasibility and reliability of the proposed approach.

The article develops a methodology for analyzing the noise immunity of satellite communication systems under small-scale disturbances of the ionosphere, taking into account the possibility of general and time-selective fading of received signals Differential Phase Shift Keying. The refined dependences of the intervals of time and space correlation of fading in the transionospheric radio channel on the parameters of transmitted signals and the state of the ionosphere are obtained. The analytical dependence of the probability of erroneous reception of signals with Differential Phase Shift Keying on the average signal-to-noise ratio at the receiver input, the frequency-time parameters of the signals and the characteristics of small-scale ionospheric inhomogeneities was obtained.

Climate change is increasingly affecting the Red Sea-related terrains in Egypt and Saudi Arabia with a notable increase in heavy precipitation events. This highly vulnerable region to flashfloods and other climate change-driven hazards encompasses rough terrains with more than 11,000 basins/subbasins, which necessitates the accurate estimation of their hydrological and geomorphological parameters among which the hypsometric analysis. In this regard, The study examines the accuracy of the hypsometric analysis extracted using open source SRTM-1, ASTER-GDEM, Copernicus-GLO30, ALOS-DEM against high-resolution Topo-1 m and Topo-2.8 m DEMs for Talat Hamdh basin in Egypt and Wadi El-Salwely basin in Saudi Arabia, respectively. Copernicus-GLO30 shows the highest accuracy among all DEMs with the root-mean-squared–error (RMSE), mean elevation error, standard deviation, maximum and minimum absolute errors of 3.03, 2.0, 2.3, 11.7 and 0.1 m, respectively for Talat Hamdh basin. The findings also show that, regardless of the geology and geomorphic evolution of the basin, the hypsometric analysis is sensitive to the DEM type rather than the spatial resolution as Copernicus DEM yields similar basin numbers (a single basin) and area (1.366 and 141.9 km²) compared to the reference DEMs (1.408 and 154.4 km²) for Talat Hamdh and Wadi El-Salwely basins, respectively. Contrariwise, other open source DEMs yield multiple basins and thus significantly smaller basin area. Given the DEM-type dependence of the hypsometric analysis, the study recommends that large-scale hydrological and geomorphological analyses should consider using a high-resolution reference DEM on a local-scale basin to examine the accuracy of open source DEMs prior to conducting the analysis.