Spatial data types

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  • MySQL 5 is slated to be the most significant release in the products history. The Definitive Guide to MySQL 5, Third Edition is the newest revision of Michael Koflers popular book. This is the first book to offer in-depth instruction about the new features of the world's most popular open source database server. Updated to reflect changes in MySQL version 5, this book will expose you to MySQL's impressive array of new features: views, stored procedures, triggers, and spatial data types.

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  • Chapter 25 - Advanced data types and new applications. This chapter covers advanced data types and new applications, including temporal datababases, spatial and geographic databases, multimedia databases, and mobility and personal databases. This chapter is suited as a means to lay the groundwork for an advanced course. Some of the material, such as temporal and spatial data types, may be suitable for self-study in a first course.

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  • This chapter covers advanced data types and new applications, including temporal datababases, spatial and geographic databases, multimedia databases, and mobility and personal databases. This chapter is suited as a means to lay the groundwork for an advanced course. Some of the material, such as temporal and spatial data types, may be suitable for self-study in a first course.

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  • Oracle allows you to define your own object data types, which you can use for creating objects, discussed in detail in Chapter 21, “Object Relational Interactions with Oracle.” Oracle also includes specialized data types for working with XML, spatial data, and media data, as well as ways to access type descriptions when the data type is not known. Since these data types are only used in specialized situations, and since you will probably want detailed information about these data types if you are going to be using them, you should consult the Oracle documentation if you feel you need the...

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  • The DBMS field has always focused on capturing, organizing, storing, analyzing, and retrieving structured data. Until recently, there was limited interest in extending a DBMS to also manage text, temporal, spatial, sound, image, or video data. However, the Web has clearly demonstrated the importance of these more sophisticated data types. The general problem is that as systems add capabilities, it is hard to make these additions “cleanly.” Rather, there is a tendency to do the minimum necessary to...

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  • The technical, scientific, policy, and institutional environment for conduct- ing Earth science research has been changing rapidly over the past few decades. Changes in the technical environment are due both to the advent of new types and sources of remote sensing data, which have higher spatial and spectral resolution, and to the development of vastly expanded capa- bilities in data access, visualization, spatial data integration, and data manage- ment.

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  • Remotely-sensed data for urban classification is very diverse in data type, acquisition time, and spatial resolution. Therefore, preprocessing is needed for input data, in which the spatial resolution must be changed by different resampling methods. However, data transformations during resampling have many effects on classification results. In this research, resampling methods were evaluated.

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  • This study has assessed soil erosion in some protection plantation models at Hong Linh town, Ha Tinh province by applying soil loss prediction equation and spatial analysis. We conducted 20 plots & 80 random points to collect data. To assess soil erosion, the study was based on IDW interpolation in ArcGIS to conduct maps. The results show that (1) There are five main forest types (Pine, mixed Pine and Acacia, Acacia, Eucalypt, mixed Eucalypt & Acacia) in which Pine (Pinus merkusii) is a native species and dominant in protection plantations with 47.65% (665.96 ha).

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  • Many environmental variables are frequently used to predict values of soil in locations where they are not measured. Digital soil mapping (DSM) has a long-standing convention to describe soils as a function of climate, organisms, topography, parent material, time and space. It is obvious that terrain, climate, parent material and organisms are used frequently in the prediction of soil properties while time and space factors are rarely used. Time is the indirect factor for the formation and development of soil.

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  • In this paper, data with significant noise and discontinuities is considered. Finding appropriate interpolation methods for these types of data poses several challenges. The main aims of this paper are to present spatial interpolation methods and to select an adequate interpolation method for the particular data. The results of different interpolation methods are implemented and tested in a case study of the Sai Gon river.

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  • Thematic maps present information relating to spatial variations in the distribution of specific geographical features at a regional scale or across the entire basin. The spatial distribution of thematic maps aids in decision-making of management of resources. Different thematic maps generated for the Kinnerasani basin include watershed boundary, drainage network, slope map, landuse/landcover map and soil map with the help of Survey of India topographical map and Cartosat DEM. LULC map was developed using IRS P6 LISS III satellite data.

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  • Technological developments in the emerging field of spatial transcriptomics have opened up an unexplored landscape where transcript information is put in a spatial context. Clustering commonly constitutes a central component in analyzing this type of data.

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  • Normalization is essential to ensure accurate analysis and proper interpretation of sequencing data, and chromosome conformation capture data such as Hi-C have particular challenges. Although several methods have been proposed, the most widely used type of normalization of Hi-C data usually casts estimation of unwanted effects as a matrix balancing problem, relying on the assumption that all genomic regions interact equally with each other.

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  • The database community has insulated itself from the information retrieval community, and has largely eschewed dealing with messy data types like time and space (not everyone has, just most of us.) We had our hands full dealing with the “simple stuff” of numbers, strings, and relational operators on them. But, real ap- plications have massive amounts of text data, have temporal prop- erties, and have spatial properties. The DBMS extensibility offered by integrating languages with the DBMS makes it relatively easy to add data types...

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  • Magnetic motion capture systems require the real actor to wear a set of sensors, which are capable of measuring their spatial relationship to a centrally located magnetic transmitter. The position and orientation of each sensor is then used to drive an animated character. One problem is the need for synchronizing receivers. The data stream from the receivers to a host computer consists of 3D positions and orientations for each receiver.

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  • The spatial information related to these factors can be derived from remote sensing data, ground based information, and several other data sources. Geographic Information System (GIS) is a very powerful tool for the integration of different types of data. Over the past few years, there have been significant developments of GIS for spatial data analysis. Efficient landslide susceptibility mapping can be carried out by combining GIS with image processing capabilities (Sarkar and Kanungo, 2004).

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  • In recent years, under impacts of human activities and climate change, flood has been increased in both the frequency and magnitude, causing lots of damages to people. This study presents a method to evaluate the direct spatial damages of flooding based on inundation depth and land use data. Damage functions for different types of land use arc selected and applied. Matlab strings and GIS are combined to calculate damage in monitery term. The method is applied for estimating loss caused by thc flood event November 1999 for Huong rivce basin.

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  • The purpose of reservoir characterisation is to fi gure out the spatial distribution of petrophysical properties such as porosity, permeability and water saturation that are key parameters for construction of the geological model. Characterisation of a carbonate reservoir is often diffi cult mainly due to the complexity of its pore system. This study presents an integrated approach to using well log and micro-geological data to characterise rock fabrics and their pore system for a carbonate reservoir in the HR structure.

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  • Agricultural sustainability is the highest priority in developed and developing countries. This study aims in discussing the impacts and applications of geospatial information technology in agriculture and allied branches. These advanced technologies offer multi-scale benefits and they can be used to create and synthesize new low-cost information and documents.

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  • Hydrological modelling is a powerful technique of hydrologic system investigation for both the research hydrologists and the practicing water resources engineers involved in the planning and development of integrated approach for management of water resources. In present study, the observed rainfall and runoff data of 2010, 2011, 2013 and 2014years were used as input data. In ANN, input data was divided in 70 per cent, 15 per cent and 15 per cent for training, testing and validation purpose, respectively.

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