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11.
The evaluation of agricultural sustainability status helps in identifying specific indicators that constrain the achievement of sustainable agriculture. The agricultural sector in Egypt is facing major sustainability constraints such as scarce land and water resources, environmental degradation, and rapid population growth as well as institutional arrangement including land tenure and farm fragmentation, agricultural administration, lack of infrastructure, and credit utilization and high interest rates. This study aims to evaluate the agricultural sustainability in some areas in Kafr El-Sheikh governorate, north of the Nile Delta; the international framework for evaluating sustainable land management was used for realizing this objective. The map of the physiographic soils of the studied area was produced depending upon Landsat ETM+ images analysis; the results indicate that the area includes three main landscapes, i.e., alluvial, lacustrine, and marine plains. The characteristics of productivity, security, protection, economic viability, and social acceptability in the different mapping units were assessed. The obtained results show that the studied area includes two different class types, the first are the lands that are marginally below the requirement of sustainability and the second are those lands that do not meet sustainability requirements. The former class is represented by the physiographic units of alluvial plain, whereas the latter class is represented by the physiographic units of the lacustrine and marine plains. The sustainability constrains in the studied area are related to the soil productivity, economic viability, and social acceptability.  相似文献   
12.
Understanding the behavior of colloids in groundwater is critical as some are pathogenic while others may facilitate or inhibit the transport of dissolved contaminants. Colloid behavior in saturated fractured aquifers is governed by the physical and chemical properties of the groundwater-particle-fracture system. The interaction between these properties is nonlinear, and there is a need for a mathematical model describing the relationship between them to advance the mechanistic understanding of colloid transport in fractures and facilitate modeling in fractured environments. This paper coupled genetic programming and linear regression within a multigene genetic programming framework to develop a robust mathematical model describing the relationship between colloid retention in fractures and the physical and chemical parameters that describe the system. The data employed for model development and validation were collected from a series of 75 laboratory-scale colloid tracer experiments conducted under a range of conditions in three laboratory-induced discrete dolomite fractures and their epoxy replicas. The model sufficiently reproduced the observed data with coefficients of determination (R2) of 0.92 and 0.80 for model development and validation, respectively. A cross-validation demonstrated the model generality to 86% of the observed data. A variance-based global sensitivity analysis confirmed that attachment is the primary retention mechanism in the systems employed in this work. The model developed in this study provides a tool describing colloid retention in factures, which furthers the understanding of groundwater-particle-fracture system conditions contributing to the retention of colloids and can aid in the design of groundwater remediation strategies and development of groundwater management plans.  相似文献   
13.
Estimation of reference evapotranspiration (ET0) in urban areas is challenging but essential in arid urban climates. To evaluate ET0 in an urban environment and non-urban areas, air temperature and relative humidity were measured at five different sites across the arid city of Isfahan, Iran, over 4 years. Wind speed and sunshine hours were obtained from an urban surrounding weather station over the same period and used to estimate ET0. Calculated ET0 was compared with satellite-based ET0 retrieved from the MOD16A2 PET product. Although MODIS PET was strongly correlated with the Valiantzas equation, it overestimated ET0 and showed average accuracy (r = 0.93–0.94, RMSE = 1.18–1.28 mm/day, MBE = 0.73–0.84 mm/day). The highest ET0 differences between an urban green space and a non-urban area were 1.1 and 0.87 mm/day, which were estimated by ground measurements and MODIS PET, respectively. The sensitivity of ET0 to wind speed and sunshine hours indicated a significant effect on cumulative ET0 at urban sites compared to the non-urban site, which has a considerable impact on the amount of irrigation required in those areas. Although MODIS PET requires improvement to accurately reflect field level microclimate conditions affecting ET0, it is beneficial to hydrological applications and water resource managers especially in areas where data is limited. In addition, our results indicated that using limited data methods or meteorological data from regional weather stations, leads to incorrect estimation of ET0 in urban areas. Therefore, decision-makers and urban planners should consider the importance of precisely estimating ET0 to optimize management of urban green space irrigation, especially in arid and semi-arid climates such as the city of Isfahan.  相似文献   
14.
Due to the various influencing factors on river suspended sediment transportation, determining an appropriate input combination for developing the suspended sediment load forecasting model is very important for water resources management. The influence of pre-processing of input variables by Gamma Test (GT) was investigated on performance of Support Vector Machine (SVM) with two kernels; Radial Basis Function (RBF) and polynomial in order to forecast daily suspended sediment amount in the period between 1983 and 2014 at Korkorsar basin, northern Iran. The best input combination was identified using GT and correlation coefficient analysis. Then, the SVM model was developed and the suspended sediment amount was forecasted with RBF and polynomial kernels. The obtained results in testing phase showed that GT-SVM (RBF kernel) model can estimate suspended sediment more accurately with the lowest RMSE (14.045 ton/day), highest correlation coefficient (0.88) and highest NSEC coefficient (0.88) than SVM (RBF kernel) model (RMSE?=?18.36ton/day, \( {R}^2=0.79, \) \( NSEC=0.73 \)) and had a better performance than the other models. The results indicated that in forecasting the first nine maximum values of suspended sediment load, GT-SVM (RBF) had a higher capability than the other models and could provide a more accurate estimation from the maximum rate of suspended sediment. The results of this study showed the capability of identifying the priority of the input parameters can change GT to a useful and technical test for input variables pre-processing to forecast the amount of suspended sediments.  相似文献   
15.
ABSTRACT

The ubiquity of personal sensing devices has enabled the collection of large, diverse, and fine-grained spatio-temporal datasets. These datasets facilitate numerous applications from traffic monitoring and management to location-based services. Recently, there has been an increasing interest in profiling individuals' movements for personalized services based on fine-grained trajectory data. Most approaches identify the most representative paths of a user by analyzing coarse location information, e.g., frequently visited places. However, even for trips that share the same origin and destination, individuals exhibit a variety of behaviors (e.g., a school drop detour, a brief stop at a supermarket). The ability to characterize and compare the variability of individuals' fine-grained movement behavior can greatly support location-based services and smart spatial sampling strategies. We propose a TRip DIversity Measure --TRIM – that quantifies the regularity of users' path choice between an origin and destination. TRIM effectively captures the extent of the diversity of the paths that are taken between a given origin and destination pair, and identifies users with distinct movement patterns, while facilitating the comparison of the movement behavior variations between users. Our experiments using synthetic and real datasets and across geographies show the effectiveness of our method.  相似文献   
16.
Journal of Seismology - By utilizing teleseismic data, the P-wave receiver functions (RFs) have been computed for 20 broadband seismic station deployed in Harrat Khaybar and Ithnayn, in the Arabian...  相似文献   
17.
Acta Geotechnica - This technical paper focuses on evaluating the shear strength of unsaturated sand at drying, wetting and alternate drying–wetting cycles, as well as the correlation between...  相似文献   
18.
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   
19.
This paper proposes a spectral–spatial method for classification of hyperspectral images. The proposed method, called SSC, consists of two steps. In the first step, to overcome the computation complexity, a wavelet-based classifier is designed. In the second step, to enhance the classification accuracy, a novel hidden Markov random field called NHMRF technique in spatial domain is suggested. In NHMRF, we convert two-dimensional energies of traditional hidden Markov random field to three-dimensional energies and then we apply edge preserving regularization terms on each two-dimensional energy of this cube. The class label of each test pixel is fixed based on minimum three-dimensional energy achieved by edge preserving regularization terms. Experimental results show that the classification accuracy of the proposed approach based on three-dimensional energies and edge preserving regularization terms is effectively improved in comparison with the state-of-the-art methods.  相似文献   
20.
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