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941.
J. A. Ruiz‐Arias D. Pozo‐Vázquez H. Alsamamra 《International journal of geographical information science》2013,27(8):1049-1076
Daily solar radiation estimates of four up‐to‐date solar radiation models (Solar Analyst, r.sun, SRAD and Solei‐32), based on a digital elevation model (DEM), have been evaluated and compared in a Mediterranean environment characterized by a complex topography. The models' estimates were evaluated against 40 days of radiometric data collected in 14 stations. Analyzed sky conditions ranged from completely overcast conditions to clear skies. Additionally, the role of the spatial resolution of the DEM has been evaluated through the use of two different resolutions: 20 and 100 m. Results showed that, under clear‐sky conditions, the daily solar radiation variability in the study area may be reasonably estimated with mean bias errors under 10% and root mean square error values of around 15%. On the other hand, results proved that the reliability of the estimates substantially decreases under overcast conditions for some of the solar radiation models. Regarding the role of the DEM spatial resolution, results suggested that the reliability of the estimates for complex topography areas under clear‐sky conditions improves using a higher spatial resolution. 相似文献
942.
D. Sheeren S. Mustière J.‐D. Zucker 《International journal of geographical information science》2013,27(8):961-992
When different spatial databases are combined, an important issue is the identification of inconsistencies between data. Quite often, representations of the same geographical entities in databases are different and reflect different points of view. In order to fully take advantage of these differences when object instances are associated, a key issue is to determine whether the differences are normal, i.e. explained by the database specifications, or if they are due to erroneous or outdated data in one database. In this paper, we propose a knowledge‐based approach to partially automate the consistency assessment between multiple representations of data. The inconsistency detection is viewed as a knowledge‐acquisition problem, the source of knowledge being the data. The consistency assessment is carried out by applying a proposed method called MECO. This method is itself parameterized by some domain knowledge obtained from a second method called MACO. MACO supports two approaches (direct or indirect) to perform the knowledge acquisition using data‐mining techniques. In particular, a supervised learning approach is defined to automate the knowledge acquisition so as to drastically reduce the human‐domain expert's work. Thanks to this approach, the knowledge‐acquisition process is sped up and less expert‐dependent. Training examples are obtained automatically upon completion of the spatial data matching. Knowledge extraction from data following this bottom‐up approach is particularly useful, since the database specifications are generally complex, difficult to analyse, and manually encoded. Such a data‐driven process also sheds some light on the gap between textual specifications and those actually used to produce the data. The methodology is illustrated and experimentally validated by comparing geometrical representations and attribute values of different vector spatial databases. The advantages and limits of such partially automatic approaches are discussed, and some future works are suggested. 相似文献
943.
C. Qin A.‐X. Zhu T. Pei B. Li C. Zhou L. Yang 《International journal of geographical information science》2013,27(4):443-458
Most multiple‐flow‐direction algorithms (MFDs) use a flow‐partition coefficient (exponent) to determine the fractions draining to all downslope neighbours. The commonly used MFD often employs a fixed exponent over an entire watershed. The fixed coefficient strategy cannot effectively model the impact of local terrain conditions on the dispersion of local flow. This paper addresses this problem based on the idea that dispersion of local flow varies over space due to the spatial variation of local terrain conditions. Thus, the flow‐partition exponent of an MFD should also vary over space. We present an adaptive approach for determining the flow‐partition exponent based on local topographic attribute which controls local flow partitioning. In our approach, the influence of local terrain on flow partition is modelled by a flow‐partition function which is based on local maximum downslope gradient (we refer to this approach as MFD based on maximum downslope gradient, MFD‐md for short). With this new approach, a steep terrain which induces a convergent flow condition can be modelled using a large value for the flow‐partition exponent. Similarly, a gentle terrain can be modelled using a small value for the flow‐partition exponent. MFD‐md is quantitatively evaluated using four types of mathematical surfaces and their theoretical ‘true’ value of Specific Catchment Area (SCA). The Root Mean Square Error (RMSE) shows that the error of SCA computed by MFD‐md is lower than that of SCA computed by the widely used SFD and MFD algorithms. Application of the new approach using a real DEM of a watershed in Northeast China shows that the flow accumulation computed by MFD‐md is better adapted to terrain conditions based on visual judgement. 相似文献
944.
This research is motivated by the need for 3D GIS data models that allow for 3D spatial query, analysis and visualization of the subunits and internal network structure of ‘micro‐spatial environments’ (the 3D spatial structure within buildings). It explores a new way of representing the topological relationships among 3D geographical features such as buildings and their internal partitions or subunits. The 3D topological data model is called the combinatorial data model (CDM). It is a logical data model that simplifies and abstracts the complex topological relationships among 3D features through a hierarchical network structure called the node‐relation structure (NRS). This logical network structure is abstracted by using the property of Poincaré duality. It is modelled and presented in the paper using graph‐theoretic formalisms. The model was implemented with real data for evaluating its effectiveness for performing 3D spatial queries and visualization. 相似文献
945.
946.
Ida Damgaard Poul L. Bjerg Carsten S Jacobsen Aikaterini Tsitonaki Henriette Kerrn‐Jespersen Mette M. Broholm 《Ground Water Monitoring & Remediation》2013,33(1):48-61
At a low permeability clay till site contaminated with chlorinated ethenes (Gl. Kongevej, Denmark), enhanced reductive dechlorination (ERD) was applied by direct push injection of molasses and dechlorinating bacteria. The performance was investigated by long‐term groundwater monitoring, and after 4 years of remediation, the development of degradation in the clay till matrix was investigated by high‐resolution subsampling of intact cores. The formation of degradation products, the presence of specific degraders Dehalococcoides spp. with the vinyl chloride (VC) reductase gene vcrA, and the isotope fractionation of trichloroethene, cis‐dichloroethene (cis‐DCE), and VC showed that degradation of chlorinated ethenes occurred in the clay till matrix as well as in sand lenses, sand stringers, and fractures. Bioactive sections of up to 1.8 m had developed in the clay till matrix, but sections, where degradation was restricted to narrow zones around sand lenses and stringers, were also observed. After 4 years of remediation, an average mass reduction of 24% was estimated. Comparison of the results with model simulation scenarios indicate that a mass reduction of 85% can be obtained within approximately 50 years without further increase in the narrow reaction zones if no donor limitations occur at the site. Long‐term monitoring of the concentration of chlorinated ethenes in the underlying chalk aquifer revealed that the aquifer was affected by the more mobile degradation products cis‐DCE and VC generated during the remediation by ERD. 相似文献
947.
Guohui Wang Richelle M. Allen‐King Sungwook Choung Stanley Feenstra Robert Watson Michael Kominek 《Ground Water Monitoring & Remediation》2013,33(1):87-96
In this study, we tested a practical strategy useful for accurate chlorinated volatile organic compound (cVOC) sorption prediction. Corresponding to the feature of the superposition of adsorption due to thermally altered carbonaceous matter (TACM) with organic carbon‐water partitioning, a nonlinear Freundlich sorption isotherm covering a wide range of aqueous concentrations was defined by equilibrium sorption measurement at one or a few low concentration points with extrapolation to the empirical organic carbon‐water partition coefficient (Koc,e) near compound solubility. We applied this approach to obtain perchloroethene equilibrium sorption isotherm parameters for TACM‐containing glacial sand and gravel subsoil samples from a field site in New York. Sorption and associated Koc,c applicable to low (5–500 µg/L) and high (>100,000 µg/L) aqueous concentrations were determined in batch experiments. (The Koc,c is the organic carbon‐normalized sorption partition coefficient corresponding to aqueous concentration Cw.) The Koc,c measurements at low concentration (~5 µg/L) were 6 to 34 times greater than the Koc,e. The importance of this type of data is illustrated through presentation of its substantial impact on the site remedy. In so doing, we provide an approach that is broadly applicable to cVOC field sites with similar circumstances (low carbon content glacial sand and gravel with TACM). 相似文献
948.
The objective of this paper is to develop an online system parameter estimation technique from the response measurements through using the recursive covariance‐driven stochastic subspace identification (SSI‐COV) approach. In developing the recursive SSI‐COV, to avoid time‐consumption of singular value decomposition in recursive SSI, the extended instrumental variable version of the projection approximation subspace tracking method is used in SSI‐COV. Besides, to reduce the effect of noise on the results of identification, the preprocessing of data using recursive singular spectrum analysis technique is also presented to remove the noise contaminant measurements to enhance the stability of data analysis. On the basis of the proposed method, both the ambient vibration and seismic response data of a tower (Canton Tower) are used to observe the time‐varying system natural frequencies of a tower from its operating condition. Results from using off‐line SSI‐COV method under normal operating condition are also presented. Comparison on the identified time‐varying dynamic characteristics of the tower under normal operating condition and earthquake response of distanced earthquake event is discussed. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
949.
A frequency response function change (FRFC) method to detect damage location and extent based on the change in the frequency response functions of a shear building under the effects of ground excitation was proposed in this paper. The damage identification equation was derived from the motion equations of the system before and after the occurrence of the damage. Efforts to make the FRFC method less model‐dependent were made. Intact system matrices, which could be estimated using the measured data without the need for an analytical model, and the frequency response functions were required for the FRFC method. The effects of measurement noise and model parameter error in the FRFC method were studied numerically. The proposed FRFC method was validated by experimental studies of a six‐story steel building structure with single and multiple damage cases. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
950.
Reinforced concrete structure may exhibit significant inelastic hysteretic behavior when subject to strong earthquake excitation. To investigate such an inelastic behavior, in this study, a new system identification technique is applied by using the deteriorating distributed element (DDE) model to simulate the hysteretic behavior of a degrading structure. Through the advanced signal processing technique, the multiple singular spectrum analysis (SSA) and the nonlinear SSA, the recorded inelastic restoring force of a deteriorating structure can be decomposed into several independent additive components in its sequentially degrading order and with decreasing weight. With each decomposed hysteresis loop, the model parameters of the DDE model are identified. The evolutionary properties of the progressive stiffness degradation behavior of reinforced concrete structure can be observed from the identified model parameters. Finally, comparison on the physical properties of the identified DDE model with respect to the seismic response data of the deteriorating structure is also discussed. The result shows that the proposed identification technique can have a good estimation on the seismic behavior of the degrading structure. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献