Spatial data model

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  • Earth sciences phenomena have evolved in time and space jointly, but in practical applications their records are available as temporal records, spatial measurements, or both.

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  • • Data models facilitate • Early analysis of properties, ... e.g. storage cost, querying ability, • Re-use of shared data among multiple applications • Exchange of data across organization • Conversion of data to new software/ environment • Example - Y2K crisis for year 2000 Many computer software systems were developed without welldefined data models in 1960s and 1970s. These systems used a variety of data models for representing time and date. Some of the representations used two digits to represent years.

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  • One of the most important advancements in recent social science research (including applied social sciences and public policy) has been the application of quantitative or computational methods in studying the complex human or social systems. Research centers in computational social sciences have flourished on major university campuses. Among others, the University of Chicago, University of Washington, UCLA, and George Mason University have all established such a center recently to promote the multidisciplinary research related to social issues....

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  • For simplicity, in the example we have assumed that a new map is created at the end of every step. This is certainly a possibility, but it is not necessarily the best option. Later in this book, we will discuss data modeling and how to optimize the sequence of operations. In particular, Chapters 8 and 9 cover spatial operators and functions that make it possible to cluster some of the steps in the example into single queries, making the process much simpler and more efficient.

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  • - Các quy định được đưa ra trong văn bản này nhằm mục đích đảm bảo sự thống nhất các dữ liệu BDĐH tỷ lệ 1/10k, 1/25k, 1/50k và 1/100k thực hiện bằng pp số hóa phục vụ cho các mục đích khai thác sử dụng khác nhau và lưu trữ, cập nhật để quản lý sử dụng lâu dài - Cơ sở dữ liệu BDĐH số hóa 1/10k, 1/25k.

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  • Geographic Information Systems (GIS) has emerged as one of the most important and widely used softwares for the social scientists in last two decades. Economists, sociologists, political scientists, public administrators, and geographers alike use GIS for capturing, storing, analyzing, and presenting spatially referenced socio-economic data. Election campaigns have been using GIS in a rapidly increasing manner. It has also been substantially used by urban and regional planners, natural resources scientists, and civil engineers.

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  •   Nowadays,  digital  terrain  models  (DTM)  are  an  important  source  of  spatial  data  for  various  applications  in  many  scientific  disciplines.  Therefore,  special  attention  is  given  to  their  main characteristic ‐ accuracy. At it is well known, the source data for DTM creation contributes a  large amount  of errors, including gross errors, to the final product.

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  • Working on a Ph.D. can be lonely, frustrating, discouraging. In my own case, the work was both made easier and more difficult by having been involved in researching the subject matter of my dissertation for more than fifteen years: easier because t had worked out many of the basic concepts and techniques by the time I began the most recent phase; harder because there was by then a lot of material to integrate, and my main application area (map ...

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  • The explosive growth in geographical information systems (GIS) in the last decade has resulted in considerable debate about which particular definition most accurately describes the activities of GIS research, and whether these diverse activities constitute a science of geographic information (Rhind et al., 1991). There is now widespread acceptance in the research community that the strengths of GIS lie in its diversity and the research area has correspondingly evolved to encompass an increasing range of geographical and spatially oriented analytical and modelling processes.

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  • The paper presents a new model for contextdependent interpretation of linguistic expressions about spatial proximity between objects in a natural scene. The paper discusses novel psycholinguistic experimental data that tests and verifies the model. The model has been implemented, and enables a conversational robot to identify objects in a scene through topological spatial relations (e.g. “X near Y”). The model can help motivate the choice between topological and projective prepositions.

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  • GIS has been coming of age. Millions of people use one GIS or another every day, and with the advent of Web 2.0 we are promised GIS functionality on virtually every desktop and web-enabled cellphone. GIS knowledge, once restricted to a few insiders working with minicomputers that, as a category, don’t exist any more, has proliferated and is bestowed on students at just about every university and increasingly in community colleges and secondary schools.

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  • Digital Elevation Model (DEM) is an important component of GIS applications in many socio-economic areas. Especially, DEM has a very important role in monitoring and managing natural resources, preventing natural hazards, and supporting spatial decision making. Usually, DEM is built by interpolation from a limited set of sample points. Thus, the accuracy of the DEM is depended on the used interpolation method.

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  • For this paper, we have examined the concept of an investigation to determine what is required. The result is an event-based framework that can be used to develop hypotheses and answer questions about an incident or crime. Hypotheses are developed by collecting objects that may have played a role in an event that was related to the incident. Once the objects are collected as evidence, the investigator can develop hypotheses about previous events at the crime scene.

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  • Following the consensus points described above, we identify the specific benefits and beneficiaries that flow from the typical MA ecosystem services categories. We also identify the spatial data layers needed to map the location of these beneficiaries. In order to enable the ARIES modelling paradigm, all benefits must meet five requirements.

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  • In ARIES, Ecosystem Services are the effects on human well-being of the flow of benefits from an ecosystem endpoint to a human endpoint at given extents of space and time. The methodology combines spatially explicit models of ecosystem service provision and use with dynamic flow models to describe the distribution of benefits across the landscape. The exact form of these models depends on the specific context of application and is chosen by means of machine reasoning, on the basis of data analysis and ontological connotations of the services (e.g.

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  • We specify an algorithm that builds up a hierarchy of referential discourse segments from local centering data. The spatial extension and nesting of these discourse segments constrain the reachability of potential antecedents of an anaphoric expression beyond the local level of adjacent center pairs. Thus, the centering model is scaled up to the level of the global referential structure of discourse. An empirical evaluation of the algorithm is supplied.

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  • Magnitude of the shift-invariant transmit and receive spatial correlation coefficients compared with Jakes’ model. measured data, the expectation is replaced by an average over all time samples. The transmit and receive correlation coefficients are then constructed using ρT ,q = RT ,q /RT ,0 and ρR,p = RR,p /RR,0 , respectively. Figure 1.5 shows the shift-invariant spatial transmit and receive correlation coefficient computed from the 10 × 10 data versus antenna separation p z and q z.

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  • Field data are being integrated into well-developed and tested models to better understand and characterize aerosol pollution in Mexico City. The spatial, temporal, size, and chemical characteristics of specific emissions sources are needed to allow their contributions to PM concentrations to be distinguished from each other and to provide accurate inputs to air quality models.

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  • The linkage between model results and monitoring data can be complicated if monitoring programs are not designed to address which parameters should be monitored, timing of measurements, location, spatial scale, and resolution of measurements to match with model parameters. This is particularly valuable in the early stages of a project when the opportunity exists to alter the project to ensure long-term storage and improve efficiency.

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