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Sofiane Khelifa Bachir Gourine Habib Taibi Hicham Dekkiche 《Arabian Journal of Geosciences》2018,11(12):329
Several methods of time series analysis and forecasting require data at regular time intervals. But in space geodesy, most datasets are often full of gaps, resulting for example from hardware issue, modification of models, change of analysis strategy, and local geophysical phenomenon. The purpose of this paper is to fill the gaps in time series of space-geodetic station positions, by the use of two different approaches: the iterative singular spectrum analysis (ISSA) and the generalized regression neural network (GRNN). In order to test the efficiency of the proposed methods to properly process missing data, we created synthetic gaps at random points in regular time series (i.e., time series without gaps) of Global Positioning System (GPS) and Doppler Orbitography and Radiopositioning Integrated by Satellite (DORIS) station positions with data span longer than 4 years. For each analyzed time series, we created gaps (by removing successive points) of different lengths ranging from 1 to 52 gaps, and then, we filled these gaps by ISSA, GRNN, and other classical methods of interpolation such as nearest neighbor, linear, and cubic interpolations.The interpolation precision was evaluated by the technique of cross-validation which compares the estimated values with the original data. After several simulations on position time series with different lengths, we found that the ISSA technique provides better results in terms of root mean square error. 相似文献
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Fethi Medjani Belkacem Aissani Sofiane Labar Mohamed Djidel Danielle Ducrot Antoine Masse C. Mei-Ling Hamilton 《Arabian Journal of Geosciences》2017,10(7):176
Supervised and unsupervised satellite image classifications have progressed greatly in recent years. However, discrimination difficulties still remain among classes that directly affecting data extraction and surface mapping accuracy. The Ouargla region in southeastern Algeria is intersected by wadis, where direct communication between the shallow groundwater table and these dry, overlying ephemeral stream beds exists. Underflowing groundwater exfiltrates into low-lying aeolian blowouts or endorheic basins forming oases, chotts, and sebkhas, commonly known as saline wetlands. These wetlands are becoming increasingly vulnerable to anthropogenic stress, resulting in significant water degradation. Wetland microclimates are very important to arid regions, as they promote oasis ecosystem sustainability and preservation. High water salinity in these ecosystems, however, directly affects flourishing habitat and undermines successful desert oasis development. The objective of this work is to choose the best classification method to identify saline wetlands by comparison between the different results of land use mapping within the Ouargla basin. Landsat ETM+ (2000) satellite imagery, using visual analysis with colored compositions, has identified various forms of saline wetlands in the Ouargla region desert environment in southeast Algeria. The results show that supervised classification is validated in the identification of Saharan saline wetlands, and that support vector machine (SVM) algorithm presents the best overall accuracy. 相似文献
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Mehdi A. Guemache Djamel Machane Hamoud Beldjoudi Sofiane Gharbi Leila Djadia Sihem Benahmed Hayet Ymmel 《Natural Hazards》2010,54(2):273-288
On March 20, 2006, an earthquake (M
w = 5.3; SED) struck the mountainous region of the Babors chain (Wilaya of Bejaia, northeast Algeria). The seismic epicenter
was located near the Kherrata village. This earthquake was felt on a large area of the northeastern part of Algeria. It reached
an intensity of VII (EMS scale) at the Laalam village, situated at about 20 km northeast of Kherrata. Here, many old and recent
houses were damaged or collapsed totally, four people died and 68 were injured. Field investigations revealed that these casualties
were caused by a landslide triggered by the earthquake. Many fissures were visible on ground throughout the site. They were
generated by both sliding and settling phenomena. The Laalam site is prone to landslide, as revealed by some evidences on
old instabilities. This is due to two main factors: local geomorphology and geology. These factors intervene synchronously
for reducing the slope instability at the Laalam village. The March 20, 2006 Kherrata earthquake was the trigger that released
the Laalam landslide. 相似文献
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RÉSUMÉL’Algérie, depuis longtemps, souffre d’une pénurie des ressources en eau. La stratégie de l’état algérien consiste à augmenter les stocks d’eau en adoptant plusieurs solutions, parmi lesquelles, il y a la construction des barrages et des retenues d’eau. Mais cette solution est confrontée aux conditions météorologiques qui favorisent les pertes par évaporation, surtout dans les régions arides. Ce travail consiste à présenter les premiers essais algériens sur la préservation des plans d’eau, et augmenter ses stocks par la réduction de l’évaporation, en utilisant des substances chimiques à longue chaîne, capable de former une pellicule à l’interface air/eau, appelée « film mono-moléculaire ».Les résultats obtenus ont permis d’enregistrer des taux de réduction de l’évaporation significatifs. Ces taux varient en fonction de la substance utilisée, la durée entre deux applications de la substance et des conditions météorologiques de la région d’étude. 相似文献
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The main purpose of this paper is to apply the singular spectrum analysis (SSA), based on the phase space, and the wavelet multiresolution analysis (WMA), based on the frequency space, to the weekly time series of global sea level anomaly (GSLA) derived from satellite altimetry data over 1993–2013, in order to assess its nonlinear trends and its seasonal signals. The SSA results show that the GSLA time series is mainly dominated by a nonlinear trend explaining 89.89 % of the total GSLA variability, followed by annual and semi-annual signals with an explained variance of 9.15 and 0.32 %, respectively. For the annual signal, both methods give similar results. Its amplitude is less than 14 mm with an average of about 11 mm, and its minimum and maximum occur in April and October, respectively. The calculation of sea level trend, by both methods, is direct without removing the seasonal signals from the original GSLA time series as the most commonly used in the literature. The global sea level trend obtained from the WMA is about 2.52 ± 0.01 mm/year which is in good agreement with 2.94 ± 0.05 mm/year estimated from the SSA. Furthermore, the SSA method is most suitable for seasonal adjustment, and the WMA method is more useful for providing the different rates of sea level rise. Indeed, the WMA reveals that the global sea level has risen with the rate of 3.43 ± 0.01 mm/year from January/1993 to January/1998, 0.66 ± 0.01 mm/year from February/1998 to May/2000, 5.71 ± 0.03 mm/year from June/2000 to October/2003, and 1.57 ± 0.01 mm/year since January/2004. 相似文献
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