排序方式： 共有8条查询结果，搜索用时 15 毫秒
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Hickmat Hossen Mona G. Ibrahim Wael Elham Mahmod Abdelazim Negm Kazuo Nadaoka Oliver Saavedra 《Arabian Journal of Geosciences》2018,11(5):93
This study assesses the changes in surface area of Manzala Lake, the largest coastal lake in Egypt, with respect to changes in land use and land cover based on a multi-temporal classification process. A regression model is provided to predict the temporal changes in the different detected classes and to assess the sustainability of the lake waterbody. Remote sensing is an effective method for detecting the impact of anthropogenic activities on the surface area of a lagoon such as Manzala Lake. The techniques used in this study include unsupervised classification, Mahalanobis distance supervised classification, minimum distance supervised classification, maximum likelihood supervised classification, and normalized difference water index. Data extracted from satellite images are used to predict the future temporal change in each class, using a statistical regression model and considering calibration, validation, and prediction phases. It was found that the maximum likelihood classification technique has the highest overall accuracy of 93.33%. This technique is selected to observe the changes in the surface area of the lake for the period from 1984 to 2015. Study results show that the waterbody surface area of the lake declined by 46% and the area of floating vegetation, islands, and land agriculture increased by 153.52, 42.86, and 42.35% respectively during the study period. Linear regression model prediction indicates that the waterbody surface area of the lake will decrease by 25.24% during the period from 2015 to 2030, which reflects the negative impact of human activities on lake sustainability represented by a severe reduction of the waterbody area. 相似文献
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Samy Ismail Elmahdy Shattri Mansor Bujang B. K. Huat Ahmed Rodzi Mahmod 《Environmental Earth Sciences》2012,66(8):2185-2195
Geotechnical engineering and unpredictable piling problems of highly urbanized areas underlain by intensive geological fracture zones require a better understanding of their spatial pattern and developments. Unlike traditional techniques which use geophysical survey and visual interpretation of optical satellite images, this study presents a modified approach to revealing the buried geological fractures in karst terrain, which incorporates Wood??s algorithm. The algorithm binary maps were modified by applying additional Soble filter with 10% threshold and equalization enhancement. These modifications have proven good discrimination for morphological linear and curvilinear derived from DEM. Results of the modified method were compared to the existing geological map and validated by conducting field observations. The analysis of the results and corresponding geological and topographical maps showed the effectiveness of the method to recognize the pattern of buried geological fractures. The results obtained demonstrated that maps of the modified method can be used as a reference map prior to any site investigation. 相似文献
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Elsadek Wael M. Ibrahim Mona G. Mahmod Wael Elham Kanae Shinjiro 《Natural Hazards》2019,95(3):739-767
Natural Hazards - Many parts of Upper Egypt as Sinai and Red Sea areas were hit by severe flash floods since 1976. Wadi Qena is considered one of the most watersheds that suffers from floods in Red... 相似文献
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Arsalan Ghorbanian Mahmod Reza Sahebi Ali Mohammadzadeh 《Comptes Rendus Geoscience》2019,351(4):332-339
This study suggests a novel approach to the retrieval of soil surface parameters using a single-acquisition single-configuration synthetic-aperture radar (SAR) system. Soil surface parameters such as soil moisture and surface roughness are key elements for many environmental studies, including Earth surface water cycles, energy exchange, agriculture, and geology. Remote sensing techniques, especially SAR data, are commonly used to retrieve such soil surface parameters over large areas. Several backscattering models have been proposed for soil surface parameters retrieval from SAR data. However, commonly, these backscattering models require multi configuration SAR data, including multi-polarization, multi-frequency, and multi-incidence angle. Here we propose a methodology that employs single-acquisition single-configuration SAR data for the retrieval of soil surface parameters. The originality is to use single-acquisition single-configuration SAR data to retrieve the soil surface parameters using an optimization approach by the genetic algorithm (GA); we have used the modified Dubois model (MDM) in HH polarization as the backscattering model. Three HH polarization and C band data sets from Quebec (Radarsat-1), Ontario (SIR-C), and Oklahoma (AIRSAR) were analyzed. The retrieved values of soil moisture and soil surface roughness were then compared to ground truth measurements with corresponding parameters. We employed diverse criteria, including the mean absolute error (MAE), the root mean square error (RMSE), the coefficient of performance (CP), and the correlation coefficient to investigate the performance of the proposed methodology. This analysis suggests the capability of the GA for the retrieval of soil surface parameters. Based on our findings, this method presents a viable alternative approach to the retrieval of soil surface parameters when only single-acquisition single-configuration SAR data is available. 相似文献
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Karim Nassar Wael Elham Mahmod Hassan Fath Ali Masria Kazuo Nadaoka Abdelazim Negm 《Marine Georesources & Geotechnology》2019,37(1):81-95
This study focuses on the shoreline change detection along the North Sinai coast in Egypt using geographic information system and digital shoreline analysis system (DSAS) during the elapsed period from 1989 to 2016. The measurement of shoreline variation is mainly described for three zones: zone I, El-Tinah plain bay; zone II, El-Bardawil Lake; zone III, El-Arish valley. The rates of shoreline changes in the form of erosion and accretion patterns are automatically quantified by four statistical parameters functioned in DSAS namely endpoint rate, net shoreline movement, linear regression rate (LRR), and least median of squares. LRR results elucidate that the western seaside of El-Tinah plain bay has experienced an extremely dynamic feature with an average erosion rate of ?8.17?m/year. The littoral drifts have been driven by eastward alongshore currents toward the east side of the bay to be accreted with an average rate of +4.28?m/year. Moreover, the shoreline has progressed west of El-Bardawil inlet (1), El-Bardawil inlet (2), and El-Arish harbor. Subsequently, the corresponding average beach growth rates are found to be +2.7, +8.5, and +6.5?m/year, respectively. In contrast, the shoreline on the down-drift side to the east has negatively retreated, and the corresponding beaches have regressed at rates of ?4.5, ?8.65, and ?2.9?m/year, respectively. 相似文献
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Zeynab Ghanbari Mahmod R. Sahebi 《Journal of the Indian Society of Remote Sensing》2014,42(4):689-699
The intensity-hue-saturation method is used frequently in image fusion due to its efficiency and high spatial quality. The main shortage is its spectral distortion stemmed from replacement of intensity band with higher resolution image. In this study, a new method is introduced to improve the spectral quality of the Intensity-Hue-Saturation (IHS) algorithm. The goal of this study is to produce the fused image that has a better spectral and spatial quality with respect to the original images in term of visual comparison and the classification result. In this regard, an improved statistical approach is developed to combine an intensity band from IHS algorithm and an input high resolution image such as SAR or Panchromatic image. Then the intensity image is replaced by the combined image band. Final fused images are attained using the inverse IHS algorithm. The proposed fusion algorithm is tested on two data sets of: a) panchromatic and multi spectral bands of IKONOS image with the same acquisition date, and b) multi spectral and HH bands of IKONOS and TerraSAR-X images respectively with different acquisition dates. Moreover, the obtained results are compared with other fusion methods like IHS, Gungor, Brovey and synthetic variable ratio. The results show less spectral discrepancy of the proposed method comparing to other methods. Finally, the outcome of proposed method is classified and classification overall accuracy is improved by 5.6 and 2 percentage for data set ‘a’ and ‘b’ respectively. 相似文献
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