Abstract:
In one embodiment of the present invention, in a database management system, a system for handling geographic raster data comprises a first data table including a plurality of GeoRaster objects, each GeoRaster object including a spatial extent geometry and associated metadata, the spatial extent geometry identifying a footprint of a geographic raster data object and associated with at least one block of raster data, a second data table including a plurality of raster objects, each raster object associated with one block of raster data of a GeoRaster object and including information indicating a spatial extent of the block of raster data and information relating to the block of raster data, a first spatial index built on the first data table based on the spatial extent geometry of each of the plurality of GeoRaster objects, the first spatial index operable to retrieve a GeoRaster object from the first data table based on a relative spatial location of the GeoRaster object, and a primary key index built on the second data table based on the information relating to the block of raster data, the index operable to retrieve a raster object from the second data table based on the information relating to the block of raster data associated with the retrieved raster object.

Description:
CROSS REFERENCE TO RELATED APPLICATIONS 
   This application claims the benefit of U.S. Provisional Application No. 60/500,461, filed Sep. 5, 2003. 

   FIELD OF THE INVENTION 
   The present invention relates to a system and method for handling geographic raster data in a database management system. 
   BACKGROUND OF THE INVENTION 
   Information representing geographic features may be stored in databases and retrieved and manipulated using database management functions. Geographic features stored in databases are represented in either vector or raster format. For vector data, points are represented by their explicit x,y,z coordinates. Lines: are strings of points. Areas are represented as polygons whose borders are lines. This kind of vector format can be used to precisely record the location and shape of spatial objects. Instead of representing features by vector data formats, you can represent spatial objects by assigning values to the cells that cover the objects and record the cells as arrays, i.e. raster format. This kind of raster format has less precision, but is best for a lot of spatial analysis. 
   As a matter of fact, raster data (imagery and gridded data) is the dominant form of spatial information, which includes thematic maps, DEM/DTM, lattice data, remote sensing imagery, photogrammetric photos, scanned maps and graphs, geophysical images, medical images, etc. 
   Any spatial database management system must deal with the raster data type to provide a complete and efficient solution. Some general needs of broad application groups including:
         Traditional GIS and remote sensing applications—users manage their geographic raster and gridded data assets using a scaleable, secure, and robust RDBMS for defense, intelligence, agriculture, natural resource management.   Business applications—leverage raster-based data in conjunction with other basic location data (address, etc.) to inventory and evaluate site locations and to track fixed and/or continuous assets. They include Asset Management and Facilities Management particularly in energy and utilities.   Image and Gridded Raster Data Repositories/Clearinghouses—support for clearinghouse servers that need to ingest, store, and disseminate very large volumes of geoimagery.       

   SUMMARY OF THE INVENTION 
   The present invention is a feature of a database management system (DBMS) that lets you store, index, query, analyze, and deliver GeoRaster data, that is, raster image and gridded data and its associated metadata. The present invention provides a raster database management system targeting many domain subjects including remote sensing, photogrammetry, raster GIS, and other geoimaging and general imaging technologies. It also allows users of file-based image processing and raster data applications to benefit from the scalability, security and performance of DBMSs to support the mission critical applications. 
   In one embodiment of the present invention, in a database management system, a system for handling geographic raster data comprises a first data table including a plurality of GeoRaster objects, each GeoRaster object including a spatial extent geometry and associated metadata, the spatial extent geometry identifying a footprint of a geographic raster data object and associated with at least one block of raster data, a second data table including a plurality of raster objects, each raster object associated with one block of raster data of a GeoRaster object and including information indicating a spatial extent of the block of raster data and information relating to the block of raster data, a first spatial index built on the first data table based on the spatial extent geometry of each of the plurality of GeoRaster objects, the first spatial index operable to retrieve a GeoRaster object from the first data table based on a relative spatial location of the GeoRaster object, and a primary key index built on the second data table based on the information relating to the block of raster data, the index operable to retrieve a raster object from the second data table based on the information relating to the block of raster data associated with the retrieved raster object. 
   In one aspect of the present invention, each GeoRaster object further comprises raster type information indicating a number of spatial dimensions of the GeoRaster object and band or layer information of the GeoRaster object. Each GeoRaster object further comprises information identifying the second data table for each block of raster data in the GeoRaster object. Each GeoRaster object further comprises information identifying a raster object in the second data table for each block of raster data in the GeoRaster object. 
   In one aspect of the present invention, each raster object further comprises information matching information identifying a raster object in the second data table in a GeoRaster object. Each raster object further comprises information indicating a resolution of raster data associated with the raster object. Each raster object further comprises information identifying a block of raster data associated with the raster object. 
   In one aspect of the present invention, the associated metadata comprises object metadata including object description information and object version information, raster metadata including cell depth information, dimensionality information, blocking information, and interleaving information. The associated metadata further comprises spatial reference system information relating to a polynomial transformation for georeferencing. The polynomial transformation is an affine transformation. The associated metadata further comprises information relating to layers in a GeoRaster object. The associated metadata further comprises image/cell attribution information, scaling factor information, color related information, and layer-based attribute information for each layer. 
   In one aspect of the present invention, the first spatial index comprises an R-Tree index. The second index comprises a B-Tree index. 
   In one aspect of, the present invention, the system further comprises a second spatial index built on the second data table based on the information indicating a spatial extent of the block of raster data of each of the plurality of raster data objects, the second spatial index operable, to retrieve a raster object from the second data table based on a relative spatial location of a block of raster data associated with the retrieved raster object. The second spatial index comprises a R-Tree index. 
   In one aspect of the present invention, the system further comprises a trigger operable to perform an action after a data manipulation language operation affecting a GeoRaster object. The data manipulation language operation comprises at least one of inserting a row, updating the GeoRaster object, and deleting a row. 
   In one aspect of the present invention, the system further comprises a system data table operable to maintain a relationship between the first data table and the second data table. The system further comprises a trigger operable to maintain the system data table and GeoRaster object integrity after a data definition language operation is performed on the first data table. The data definition language operation comprises at least one of a drop operation and a truncate operation. 

   
     BRIEF DESCRIPTION OF THE DRAWINGS 
       FIG. 1  is an exemplary format of a data object, according to the present invention. 
       FIG. 2  is an exemplary format of a data object, according to the present invention. 
       FIG. 3  is an exemplary format of a system data table, according to the present invention. 
       FIG. 4  is an exemplary format of a data view, according to the present invention. 
       FIG. 5  is an exemplary format of a data view, according to the present invention. 
       FIG. 6  is an exemplary format of a conceptual data model, according to the present invention. 
       FIG. 7  is an exemplary diagram of a relationship between logical layers in the data model and the physical bands or channels of the source image data. 
       FIG. 8  is an exemplary diagram of the storage of GeoRaster objects, according to the present invention. 
       FIG. 9  is an exemplary diagram of physical storage of GeoRaster data and several related objects in a database, according to the present invention. 
       FIG. 10  is an exemplary flow diagram of a workflow of GeoRaster operations, according to the present invention. 
       FIG. 11  is a block diagram of an exemplary implementation of a database management system (DBMS), in which the present invention may be implemented. 
   

   DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT 
   GeoRaster is a database feature (for example, implemented in the ORACLE SPATIAL® database product) that lets you store, index, query, analyze, and deliver GeoRaster data, that is, raster image and gridded data and its associated metadata. GeoRaster provides spatial data types and an object-relational schema. You can use these data types and schema objects to store multidimensional grid layers and digital images that can be referenced to positions on the Earth&#39;s surface or in a local coordinate system. 
   GeoRaster data is collected and used by a variety of geographic information technologies, including remote sensing, airborne photogrammetry, cartography, and global positioning systems. The collected data is then analyzed by digital image processing systems, computer graphics applications, and computer vision technologies. These technologies use several data formats and create a variety of products. Some examples of the main data sources and uses for GeoRaster, include: 
   Remote Sensing: Remote sensing obtains information about an area or object through a device that is not physically connected to the area or object. For example, the sensor might be in a satellite, balloon, airplane, boat, or ground station. The sensor device can be any of a variety of devices, including a frame camera, pushbroom (swath) imager, synthetic aperture radar (SAR), hydrographic sonar, or paper or film scanner. Remote sensing applications include environmental assessment and monitoring, global change detection and monitoring, and natural resource surveying. 
   The data collected by remote sensing is often called geoimagery. The wavelength, number of bands, and other factors determine the radiometric characteristics of the geoimages. The geoimages can be single-band, multiband, or hyperspectral. They can cover any area of the Earth (especially for images sensed by satellite). The temporal resolution can be high, such as with meteorological satellites, making it easier to detect changes. For remote sensing applications, various types of resolution (temporal, spatial, spectral, and radiometric) are often important. 
   Photogrammetry: Photogrammetry derives metric information from measurements made on photographs. Most photogrammetry applications use airborne photos or high-resolution images collected by satellite remote sensing. In traditional photogrammetry, the main data includes images such as black and white photographs, color photographs, and stereo photograph pairs. 
   Photogrammetry rigorously establishes the geometric relationship between the image and the object as it existed at the time of the imaging event, and enables you to derive information about the object from its imagery. The relationship between image and object can be established by several means, which can be grouped in two categories: analog (using optical, mechanical, and electronic components) or analytical (where the modeling is mathematical and the processing is digital). Analog solutions are increasingly being replaced by analytical/digital solutions, which are also referred to as softcopy photogrammetry. 
   The main product from a softcopy photogrammetry systems may include DEMs and orthoimagery. All of that raster data, together with its orientation (georeferencing) information, can be managed by GeoRaster. 
   Geographic Information Systems: A geographic information system (GIS) captures, stores, and processes geographically referenced information. GIS software has traditionally been either vector-based or raster-based; however, with the GeoRaster feature, Oracle Spatial handles both raster and vector data. 
   Raster-based GIS systems typically process georectified gridded data. Gridded data can be discrete or continuous. Discrete data, such as political subdivisions, land use and cover, bus routes, and oil wells, is usually stored as integer grids. Continuous data, such as elevation, aspect, pollution concentration, ambient noise level, and wind speed, is usually stored as floating-point grids. 
   The attributes of a discrete grid layer are stored in a relational table called a value attribute table (VAT). A VAT contains columns specified by the GIS vendor, and may also contain user-defined columns. 
   Raster GIS systems let you use map algebra operators and functions. Map operators can be grouped in several categories, including arithmetic (such as +, −, *, /, MOD, and NEGATIVE), Boolean (such as NOT, &amp;, |, and !), relational (such as &lt;, &lt;=, ==, &gt;=, &gt;, and &lt;&gt;), logical (such as DIFF, IN, and OVER), bitwise (such as ^^, &gt;&gt;, &lt;&lt;, &amp;&amp;, ||, and !!), combinatorial (such as AND, OR, and XOR), and accumulative (such as +=, −+, *=, /=, {=, and }=). Map functions can operate on a cell, a block (neighborhood), a zone, or the entire grid. 
   Cartography: is the science of creating maps, which are two-dimensional representations of the three-dimensional Earth (or of a non-Earth space using a local coordinate system). Today, maps are digitized or scanned into digital forms, and map production is largely automated. Maps stored on a computer can be queried, analyzed, and updated quickly. 
   There are many types of maps, corresponding to a variety of uses or purposes. Examples of map types include base (background), thematic, relief (three-dimensional), aspect, cadastral (land use), and inset. Maps usually contain several annotation elements to help explain the map, such as scale bars, legends, symbols (such as the north arrow), and labels (names of cities, rivers, and so on). 
   Maps can be stored in raster format (and thus can be managed by GeoRaster), in vector format, or in a hybrid format. 
   Digital Image Processing: Digital image processing is used to process raster data in standard image formats, such as TIF, GIF, JFIF (JPEG), and Sun Raster, as well as in many geoimage formats, such as ERDAS, NITF, and HDF. Image processing techniques are widely used in remote sensing and photogrammetry applications. These techniques are used as needed to enhance, correct, and restore images to facilitate interpretation; to correct for any blurring, distortion, or other degradation that may have occurred; and to classify geo-objects automatically and identify targets. The source and result imagery can be loaded and managed by GeoRaster. 
   Geology, Geophysics, and Geochemistry: Geology, geophysics, and geochemistry all use digital data and produce digital raster maps that can be managed by GeoRaster.
         In geology, the data includes regional geological maps, stratum maps, and rock slide pictures. In engineering geology, 3-D modeling is popular. In geological exploration and petroleum geology, computerized geostratum simulation, synthetic mineral prediction, and 3-D oil field characterization are widely used.   In geophysics, data about gravity, the magnetic field, seismic wave transportation, and other subjects is saved, along with georeferencing information.   In geochemistry, the contents of multiple chemical elements can be analyzed and measured. The triangulated irregular network (TIN) technique is often used to produce raster maps for further analysis, and image processing is widely used.       

   The invention features a physical data model for Raster data storage and management, called the GeoRaster Physical Data Model. The physical GeoRaster data model includes two object data types for storing raster data and a schema for managing system data. The two object data types are: SDO_GEORASTER  100 , shown in  FIG. 1 , for a raster data and its related metadata, and SDO_RASTER  200 , shown in  FIG. 2 , for each block in the raster data. Each image or gridded raster data is stored in a column of type SDO_GEORASTER, and the blocks in that raster data are stored in a raster data table of type SDO_RASTER. 
   The SDO_GEORASTER object contains a spatial extent geometry  102  (footprint or coverage extent) and relevant metadata, which are organized in a XML document according to the provided XML Schema. A table containing one or more columns of this object type is called a GeoRaster table. The SDO_RASTER object contains information about a block (tile) of a GeoRaster object, and it uses a BLOB object to store the raster cell data for the block. An object table of this object type is called a raster data table (RDT). 
   Each SDO_GEORASTER object has a pair of attributes (rasterDataTable  104 , rasterID  106 ) that uniquely identify the RDT and the rows within the RDT that are used to store the raster cell data for the GeoRaster object. GeoRaster uses a system data table SDO_GEOR_SYSDATA_TABLE  300 , shown in  FIG. 3 , to maintain the relationship between GeoRaster tables and their related raster data tables. 
   Two views, USER_SDO_GEOR_SYSDATA  400 , shown in  FIG. 4 , and ALL_SDO_GEOR_SYSDATA  500 , shown in  FIG. 5 , of the GeoRaster sysdata table are available for every user. To ensure the consistency and integrity of internal GeoRaster tables and data structures, GeoRaster supplies a trigger that performs necessary actions after each of the following data manipulation language (DML) operations affecting a GeoRaster object: insertion of a row, update of a GeoRaster object, and deletion of a row. In addition, two DDL triggers are defined for all users, which maintain the SYSDATA table and GeoRaster object integrity after drop and truncate operations on a GeoRaster table are performed, respectively. 
   A spatial index (R-Tree) can be built on any GeoRaster table based on the spatial extent geometry attribute of the SDO_GEORASTER data type. A spatial index can also be built on the RDT tables based the blockMBR geometry attribute of the SDO_RASTER data type. A B-tree index is built on the RDT tables based on other attributes of the SDO_RASTER data type except the blockMBR and the rasterBlock columns. 
   In a preferred embodiment, GeoRaster provides a PL/SQL API that includes more than 100 functions. Mainly the functions are packaged into a PL/SQL package called SDO_GEOR. The API provides the most important functionalities and services for loading, managing, querying, updating, deleting, processing, and exporting GeoRaster objects. 
   The GeoRaster physical data model is based on a conceptual data model we proposed. It is called the GeoRaster conceptual data model, which is a component-based, logically layered, and multidimensional raster data model. The GeoRaster conceptual data model is illustrated in  FIG. 6 . 
   The core data in a raster is a multidimensional matrix of raster cells. Each cell is one element of the matrix, and its value is called the cell value. The matrix has a number of dimensions, a cell depth, and a size for each dimension. The cell depth is the data size of the value of each cell. It also defines the range of all cell values. The cell depth applies to each single cell, not an array of cells. This core raster data set can be blocked for optimal storage, retrieval and processing. 
   In this data model, two different types of coordinates need to be considered: the coordinates of each pixel (cell) in the raster matrix and the coordinates on the Earth that they represent. Consequently, two types of coordinate systems or spaces are defined: the cell coordinate system and the model coordinate system. The cell coordinate system (also called the raster space) is used to describe pixels in the raster matrix, and its dimensions are (in this order) row, column, and band. The model coordinate system (also called the ground coordinate system or the model space) is used to describe points on the Earth or any other coordinate system associated with an Oracle SRID value. The spatial dimensions of the model coordinate system are (in this order) X and Y, corresponding to the column and row dimensions, respectively, in the cell coordinate system. The logical layers correspond to the band dimension in the cell space. The dimensionality of spaces can be expended to M dimensions. 
   The data model is logically layered. The core data is called the object layer or layer  0 , and consists of one or more logical layers (or sublayers). Assuming the core data has M dimensions, the object layer is M dimensional, but its sublayers are M−1 dimensional. Each sublayer can be further divided into sublayers which are M−2 dimensional, and so on. For example, for multi-channel remote sensing imagery, the layers are used to model the channels or bands of the imagery. In this case, each layer is a two-dimensional matrix of cells that consists of the row dimension and the column dimension. 
   In GeoRaster, band and layer are different concepts. Band is a physical dimension of the multidimensional raster data set; that is, it is one ordinate in the cell space. For example, the cell space might have the ordinates row, column, and band. Bands are numbered from 0 to n−1, where n is the highest layer number. Layer is a logical concept in the GeoRaster data model. Layers are mapped to bands. Typically, one layer corresponds to one band, and it consists of a two-dimensional matrix of size rowDimensionSize and columnDimensionSize. Layers are numbered from 1 to n; that is, layerNumber=bandNumber+1. In a preferred embodiment, the relationship between logical layers in the GeoRaster data model and the physical bands or channels of the source image data is depicted in  FIG. 7 . The XML schema allows a more flexible random mapping between layerNumber and bandNumber other than layerNumber=bandNumber+1. A GeoRaster object has specific metadata associated with it. In the GeoRaster data model, metadata is everything but the core cell matrix and it is stored as an XMLType in the database. This metadata includes object metadata such as description and version information. GeoRaster also includes raster metadata for cell depth (1BIT, 32BIT_S, or 64BIT_REAL), dimensionality, blocking, interleaving and other information. Additionally, Spatial Reference System metadata, containing information for the affine transformation or higher-order polynomial transformations required for georeferencing, can also be stored. Additional metadata, such as metadata pertaining to each layer in a GeoRaster object, can be stored in the database as well. If the data is grid data, one or more Value Attribute Tables (VAT) can be used to maintain information about the values stored in each layer (e.g. elevation value, saturation level etc.). In addition, there is a comprehensive suite of optional metadata used to capture and track image/cell attribution, scaling factors, color related information (color map, grayscale), histogram and other layer-based attributes essential for image management and use by client applications. 
   In summary, the GeoRaster metadata is divided into different components that contain, but are not limited to, the following information:
         Object information   Raster information   Spatial reference system information   Date and time (temporal reference system) information   Spectral (band reference system) information   Layer information for each layer       

   We use XML schema to describe the metadata and related raster physical storage. Appendix A is the GeoRaster metadata XML Schema we defined based on the above conceptual data model and the following physical data model. It provides a detailed description of each metadata item of GeoRaster objects. 
   In general, the invention features a physical data model for Raster data storage and management, called the GeoRaster Physical Data Model. It&#39;s embodied as two spatial data types and an object-relational schema inside Oracle ORDBMS. 
   Returning now to  FIG. 1 , an example of a preferred embodiment of an object of SDO_GEORASTER data type  100  is shown. At the top level, one raster data (an image or a grid) is stored in Oracle as an object of SDO_GEORASTER data type  100 . A table containing one or more columns of this object type is called a GeoRaster table. A GeoRaster object of this type consists of a multidimensional matrix of cells and the GeoRaster metadata. Most metadata is stored as one attribute  108  of the SDO_GEORASTER type. It is an XML document using the Oracle XMLType data type. The metadata is defined according to the GeoRaster metadata XML schema, which is described in Appendix A. The spatial extent (footprint) of a GeoRaster object is part of the metadata, but it is stored separately as an attribute  102  of the GeoRaster object. This approach allows GeoRaster to take advantage of the spatial geometry type and related capabilities, such as using spatial R-tree indexing on GeoRaster objects. Another attribute of the SDO_GEORASTER type is the rasterType  110 , which contains dimensionality information and the data type that can be further defined. More descriptions about preferred embodiments of each attribute follow: 
   1. rasterType  110   
   
       
       
         
           The rasterType attribute  110  must be a 5-digit number in the format [d][b][t][gt], where:
           [d] identifies the number of spatial dimensions. Must be 2 for the current release.   [b] indicates band or layer information: 0 means one band or layer; 1 means one or more than one band or layer. Note that the total number of bands or layers is not specified in this field.   [t] is reserved for temporal dimension and should be specified as 0 (zero) currently.   [gt] identifies the 2-digit GeoRaster type, and must be the following:
               00 Reserved.   01 Any GeoRaster type. This is the only value supported for the current release. This value causes GeoRaster not to apply any restrictions associated with specific types that might be implemented in future releases.   02–50 Reserved. Each special GeoRaster type will be allocated a number from this range.   51–99 For customer use.
 
2. spatialExtent  102 
   
               
         
           The spatialExtent attribute  102  identifies the spatial extent, or footprint, associated with the raster data. The spatial extent is a Spatial geometry of type SDO_GEOMETRY. The spatial extent geometry can be in any coordinate system; The spatial extent geometry can also be in cell space that has a null SRID value. Because of the potential performance benefits of spatial indexing for GeoRaster applications, the geometry is associated with the spatialExtent attribute, rather than being included in the XML metadata attribute.
 
3. rasterDataTable  104 
 
           The rasterDataTable attribute  104  identifies the name of the raster data table. The raster data table must be an object table of type SDO_RASTER. It contains a row of type SDO_RASTER for each raster block that is stored. You must create and (if necessary) drop the raster data table. You should never modify the rows in this table directly, but you can query this table to access the raster data.
 
4. rasterID  106 
 
           The rasterID attribute  106  value is stored in the rows of the raster data table to identify which rows belong to the GeoRaster object. The rasterDataTable attribute and rasterID attribute together uniquely identify the GeoRaster object in the database for a specific schema or user [i.e., for the whole database, (username, rasterDataTable, rasterID) is unique. For one user, (rasterDataTable, rasterID) is unique]. That is, each GeoRaster object has a raster data table, although a raster data table can contain data from multiple GeoRaster objects. You can specify the rasterID and rasterDataTable attributes for new GeoRaster objects, as long as each pair is unique in the database. If you do not specify these values, they are automatically generated when you call SDO_GEOR.init or SDO_GEOR.createBlank function to initialize or create a GeoRaster object.
 
5. metadata  108 
 
           The metadata attribute  108  contains the GeoRaster metadata that is defined by Oracle. The metadata is described by the GeoRaster metadata XML schema, which is documented in Appendix A. The metadata of any GeoRaster object must be validated against this XML schema, and it must also be validated using the SDO_GEOR.validateGeoraster function, which imposes additional restrictions not defined by this XML schema. 
         
       
     
  
   The multidimensional matrix of cells is blocked into small subsets for large-scale GeoRaster object storage and optimal retrieval and processing. Blocking can be regular and irregular. For regular blocking, each block is a rectangular and aligned to each other. Each block has the same size. For irregular blocking blocks might have different sizes. Only regular blocking is implemented. 
   Referring now to  FIG. 2 , an example of a preferred embodiment of an object table of type SDO_RASTER  200  is shown. All blocks are stored in an object table of type SDO_RASTER  200 , which is defined by the GeoRaster Physical Data Model, as shown in  FIG. 2 . This object table is called raster data table  200 , or simply RDT table  200 . Each block  202  is stored in the RDT table  200  as a binary large object (BLOB), and a geometry object (of type SDO_GEOMETRY) is used to define the precise extent of the block. The extent geometry is called the attribute  204 . One benefit of this attribute is to build a spatial index so that blocks can be quickly retrieved based on their relative spatial location. This also allows the physical data model to block a GeoRaster object into irregular blocks, i.e., blocks can have different sizes. Each row of the table stores only one block and the blocking information related to that block. (This blocking scheme applies to any pyramids also). More descriptions about preferred embodiments of each attribute follow: 
   1. rasterID  206   
   
       
       
         
           The rasterID attribute  206  in the SDO_RASTER object  200  must be a number that matches the rasterID value in its associated SDO_GEORASTER object. The matching of these numbers identifies the raster block as belonging to a specific GeoRaster object.
 
2. pyramidLevel  208 
 
           The pyramidLevel attribute  208  identifies the pyramid level for this block of cells. In a preferred embodiment, the pyramid level is 0 or any positive integer. A pyramid level of 0 indicates the original raster data; that is, there is no reduction in the image resolution and no change in the storage space required. Values greater than 0 (zero) indicate increasingly reduced levels of image resolution and reduced storage space requirements.
 
3. bandBlockNumber  210 
 
           The bandBlockNumber  210  attribute identifies the block number along the band dimension. Only used when the GeoRaster object is regularly blocked.
 
4. rowBlockNumber  212 
 
           The rowBlockNumber attribute  212  identifies the block number along the row dimension. Only used when the GeoRaster object is regularly blocked.
 
5. columnBlockNumber  214 
 
           The columnBlockNumber attribute  214  identifies the block number along the column dimension. Only used when the GeoRaster object is regularly blocked.
 
6. blockMBR  204 
 
           The blockMBR attribute  204  is the geometry (of type SDO_GEOMETRY) for the minimum bounding rectangle (MBR) for this block. The geometry is in cell space (that is, its SRID value is null), and all ordinates are integers. The ordinates represent the minimum row and column and the maximum row and column stored in this block.
 
7. rasterBlock  202 
 
           The rasterBlock attribute  202  contains all raster cell data for this block. The rasterBlock attribute is of type BLOB. 
           The dimension sizes (along row, column, and band dimensions) may not be evenly divided by their respective block sizes. GeoRaster adds padding to the boundary blocks that do not have enough original cells to be completely filled. The boundary blocks are the end blocks along the positive direction of each dimension. The padding cells have the same cell depth as other cells and have values equal to zero. Padding makes each block have the same BLOB size. Padding applies to all dimensions. 
         
       
     
  
   Pyramids are subobjects of a GeoRaster object that represent the raster image or raster data at differing sizes and degrees of resolution. Pyramid levels represent reduced or increased resolution images that require less or more storage space, respectively. A pyramid level of 0 indicates the original raster data. Values greater than 0 (zero) indicate increasingly reduced levels of image resolution and reduced storage space requirements. GeoRaster currently supports only pyramids of reduced resolution by 2 and only applies to row and column dimensions. 
   The pyramids are stored in the same raster data table as the GeoRaster object. The pyramidLevel attribute in the raster data table identifies all the blocks related to a specific pyramid level. In general, the blocking scheme for each pyramid level is the same as that for the original level (which is defined in the GeoRaster object metadata), except in the following cases:
         If the original GeoRaster object is not blocked, that is, if the original cell data is stored in one block (BLOB) of the exact size of the object, the cell data of each pyramid level is stored in one block, and its size is the same as that of the actual pyramid level raster data.   If the original GeoRaster object is blocked (even if blocked as one block), the cell data of each pyramid level is blocked in the same way as for the original level data, and each block is stored in a different BLOB object as long as the maximum dimension size of the actual pyramid level image is larger than the block sizes. However, if lower-resolution pyramids are generated (that is, if both the row and column dimension sizes of the pyramid level are less than or equal to one-half the row block size and column block size, respectively), the cell data of each such pyramid level is stored in one BLOB object and its size is the same as that of the actual pyramid level raster data.       

   Based on this data model, compression can be applied to each block. But each block will have the same compression scheme. 
   In the raster space, band dimension stores layers or bands of multispectral imagery. Physically, three types of interleaving are supported: BSQ (band sequential), BIL (band interleaved by line), and BIP (band interleaved by pixel). Interleaving applies between bands or layers only. Interleaving is limited to the interleaving of cells inside each block of a GeoRaster object. This means GeoRaster always applies blocking on a GeoRaster object first, and then it applies interleaving inside each block independently. However, each block of the same GeoRaster object has the same interleaving type. 
   In summary, all metadata of a raster object is stored in an SDO_GEORASTER object of a GeoRaster table and all cell data of the raster object is stored in a Raster Data Table of SDO_RASTER object type, which can be optionally blocked into many smaller rectangular blocks. The SDO_GEORASTER object contains a spatial extent geometry (footprint or coverage extent) and relevant metadata. The SDO_RASTER object contains information about a block (tile) of a GeoRaster object, and it uses a BLOB object to store the raster cell data for the block. Each SDO_GEORASTER object has a pair of attributes (rasterDataTable, rasterID) that uniquely identify the RDT and the rows within the RDT that are used to store the raster cell data for the GeoRaster object. 
   Turning now to  FIG. 8 , an example of a preferred embodiment of the storage of GeoRaster objects is shown, using as an example an image of Boston, Mass. in a table that contains rows with images of various cities. 
   As shown in  FIG. 8 :
         Each row in the table of city images contains information about the image for a specific city (such as Boston), including an SDO_GEORASTER object.   The SDO_GEORASTER object includes the spatial extent geometry covering the entire area of the image, the metadata, the raster ID, and the name of the raster data table associated with this image.   Each row in the raster data table contains information about a block (or tile) of the image, including the block&#39;s minimum bounding rectangle (MBR) and image data (stored as a BLOB).       

   GeoRaster uses a system data table SDO_GEOR_SYSDATA_TABLE  300  (called the GeoRaster sysdata table) to maintain the relationship between GeoRaster tables and their related raster data tables, as shown in  FIG. 3 . Two views USER_SDO_GEOR_SYSDATA  400  and ALL_SDO_GEOR_SYSDATA  500  of the GeoRaster sysdata table are available for every user, as shown in  FIGS. 4 and 5 , respectively. All new GeoRaster objects have to be initialized and a pair of attributes (rasterDataTable, rasterID) has to be assigned to each new GeoRaster object. In the mean time when the new GeoRaster object is inserted into a GeoRaster table, all related information will be automatically inserted into the sysdata table by the GeoRaster DML trigger defined on the GeoRaster table. The uniqueness of the (rasterDataTable, rasterID) pair is enforced by the constraint defined on the sysdata table. More descriptions about preferred embodiments of each column of the sysdata table  300 , shown in  FIG. 3 , and views follow: 
   1. SDO_OWNER  302   
   
       
       
         
           The SDO_OWNER column  302  contains the GeoRaster user/schema name.
 
2. GEORASTER_TABLE_NAME  304 
 
           This column and the TABLE_NAME column in views contain the name of a GeoRaster table that has at least one column of type SDO_GEORASTER.
 
3. GEORASTER_COLUMN_NAME  306 
 
           This column and the COLUMN_NAME column in views contains the name of a column of type SDO_GEORASTER in the GeoRaster table specified in the GEORASTER_TABLE_NAME column.
 
4. GEOR_METADATA_COLUMN_NAME  308 
 
           This column and the METADATA_COLUMN_NAME column in views are reserved for future use. It can be used to contain more metadata complimentary to the metadata attribute of the GeoRaster object.
 
5. RDT_TABLE_NAME  310 
 
           This column and the RDT_TABLE_NAME column in views contain the name of the raster data table associated with the table and column specified in the GEORASTER_TABLE_NAME and GEORASTER_COLUMN_NAME columns.
 
6. RASTER_ID  312 
 
           This column and the RASTER_ID column in views contain a number that, together with the RDT_TABLE_NAME column value, uniquely identifies each GeoRaster object for a specific schema/user specified in the SDO_OWNER column. In the global database, the SDO_OWNER value, RDT_TABLE_NAME value and RASTER_ID value together must be unique in this GeoRaster sysdata table.
 
7. OTHER_TABLE_NAMES  314 
 
           This column is reserved for future use. It can be used to register other components of a GeoRaster object, such as a VAT table. 
         
       
     
  
   To ensure the consistency and integrity of internal GeoRaster tables and data structures, GeoRaster supplies a trigger that performs necessary actions after each of the following data manipulation language (DML) operations affecting a GeoRaster object: insertion of a row, update of a GeoRaster object, and deletion of a row:
         After an insert operation, the trigger inserts a row with the GeoRaster table name, GeoRaster column name, raster data table name, and rasterID value into the USER_SDO_GEOR_SYSDATA view. If an identical entry already exists, an exception is raised.   After an update operation, if the new GeoRaster object is null or empty, the trigger deletes the old GeoRaster object. If there is no entry in the USER_SDO_GEOR_SYSDATA view for the old GeoRaster object (that is, if the old GeoRaster object is null), the trigger inserts a row into that view for the new GeoRaster object. If there is an entry in the USER_SDO_GEOR_SYSDATA view for the old GeoRaster object, the trigger updates the information to reflect the new GeoRaster object.   After a delete operation, the trigger deletes raster data blocks for the GeoRaster object in its raster data table, and it deletes the row in the USER_SDO_GEOR_SYSDATA view for the GeoRaster object.       

   A function called createDMLTrigger in the SDO_GEOR_UTL package is provided. One necessary DML trigger must be created on each unique GeoRaster table and GeoRaster column pair. The necessary DML trigger or triggers must be created immediately after a GeoRaster table is created, and the trigger or triggers must be created before any operations on the table are performed. The following example creates the standard GeoRaster DML trigger for a table named XYZ_GEOR_TAB containing a GeoRaster column named GEOR_COL:
 
EXECUTEsdo_geor_utl.createDMLTrigger(‘XYZ_GEOR_TAB’,‘GEOR_COL’);
 
   In addition, two DDL triggers are defined for all users, which maintain the sysdata table and GeoRaster object integrity after drop and truncate operations on a GeoRaster table are performed respectively. These triggers make sure the GeoRaster DML trigger on a GeoRaster table is invoked for each row when user drop or truncate the GeoRaster table so that all GeoRaster objects together with their raster blocks are cleanly removed and all entries of the GeoRaster objects in the sysdata table are deleted. 
   An example of a preferred embodiment of physical storage of GeoRaster data and several related objects in a database  900  is shown in  FIG. 9 . Preferably, database  900  is implemented in a database management system As shown in  FIG. 9 :
         Each GeoRaster object, such as object  902 , in the GeoRaster table  904  has an associated raster data table, such as table  906 , which has an entry for each block of the raster image, such as entry  908 .   Each GeoRaster object has a raster data table associated with it. However, a raster data table can store blocks of multiple GeoRaster objects, and GeoRaster objects in a GeoRaster table can be associated with one or multiple raster data tables.   The BLOB  910  with image data for each raster image block is stored separately from the raster data table (which stores the BLOB locator only). You can specify separately storage parameters for the BLOBs.   GeoRaster sysdata table maintains the relationship between the GeoRaster tables and the raster data tables.       

   Other defined schema objects include SDO_GEOR_SRS for spatial reference system, SDO_GEOR_COLORMAP for colormap of a pseudocolor GeoRaster object, SDO_GEOR_GRAYSCALE for grayscale of a grayscaled GeoRaster object, SDO_GEOR_HISTOGRAM for histogram of a GeoRaster object or layer. But they are not used as persistent data types. They are defined to support query, modify and update of GeoRaster metadata. 
   A spatial index  912  (R-Tree) can be built on any GeoRaster table based on the spatial extent geometry attribute of the SDO_GEORASTER data type. A spatial index  914  may also be built on the RDT tables based the blockMBR geometry attribute of the SDO_RASTER data type. A B-tree index is built on the RDT tables based on other attributes of the SDO_RASTER data type except the blockMBR and the rasterBlock columns. 
   In a preferred embodiment, GeoRaster provides a PL/SQL API that includes more than 100 functions. Mainly the functions are packaged into a pl/sql package called SDO_GEOR. The API provides the most important functionalities and services for loading, managing, querying, updating, deleting, processing, and exporting GeoRaster objects. Appendix B provides a general overview of the basic functional infrastructure available in support of GeoRaster. 
   Some operations can be called directly in an SQL command. Others must be called in PL/SQL blocks in a standard way. An example of a workflow  1000  of the GeoRaster operations is shown in  FIG. 10 . The workflow begins with step  1001 , in which the GeoRaster table, the trigger, and the RDT are created. In step  1002 , GeoRaster objects are created and/or initialized in the GeoRaster table. In step  1003 , raster imagery and/or grids are loaded into the GeoRaster data structures. In step  1004 , the GeoRaster objects are validated. In step  1005 , GeoRaster objects are Georeferenced. In step  1006 , spatial or other indexes are created. In step  1007 , the format of GeoRaster storage is changed. In step  1008 , the GeoRaster metadata is queried and/or updated. In step  1009 , the GeoRaster cell data is queried and/or updated. In step  1010 , the GeoRaster objects are processed. In step  1011 , the GeoRaster objects are exported to other applications, databases, or systems. In step  1012 , the GeoRaster objects are viewed. The steps  1005 – 1012  may be performed in any order, depending on the application. In some applications, some steps may be skipped. For example, if you use the GeoRaster loader tool to load an image, the new GeoRaster object should have been validated and you can skip step  4 . If a World file is loaded together with an image, you can skip step  5  and only set an SRID for the GeoRaster object model coordinate system. 
   A block diagram of an exemplary implementation of a database management system (DBMS)  1100 , in which the present invention may be implemented, is shown in  FIG. 11 . DBMS  1100  is typically a programmed general-purpose computer system, such as a personal computer, workstation, server system, and minicomputer or mainframe computer. DBMS  1100  includes one or more processors (CPUs)  1102 A– 1102 N, input/output circuitry  1104 , network adapter  1106 , and memory  1108 . CPUs  1102 A– 1102 N execute program instructions in order to carry out the functions of the present invention. Typically, CPUs  1102 A– 1102 N are one or more microprocessors, such as an INTEL PENTIUM® processor.  FIG. 11  illustrates an embodiment in which DBMS  1100  is implemented as a single multi-processor computer system, in which multiple processors  1102 A– 1102 N share system resources, such as memory  1108 , input/output circuitry  1104 , and network adapter  1106 . However, the present invention also contemplates embodiments in which DBMS  1100  is implemented as a plurality of networked computer systems, which may be single-processor computer systems, multi-processor computer systems, or a mix thereof. 
   Input/output circuitry  1104  provides the capability to input data to, or output data from, DBMS  1100 . For example, input/output circuitry may include input devices, such as keyboards, mice, touchpads, trackballs, scanners, etc., output devices, such as video adapters, monitors, printers, etc., and input/output devices, such as, modems, etc. Network adapter  1106  interfaces DBMS  1100  with network  1110 . Network  1110  may include one or more standard local area networks (LAN) or wide area networks (WAN), such as Ethernet, Token Ring, the Internet, or a private or proprietary LAN/WAN. 
   Memory  1108  stores program instructions that are executed by, and data that are used and processed by, CPU  1102  to perform the functions of DBMS  1100 . Memory  1108  may include electronic memory devices, such as random-access memory (RAM), read-only memory (ROM), programmable read-only memory (PROM), electrically erasable programmable read-only memory (EEPROM), flash memory, etc., and electro-mechanical memory, such as magnetic disk drives, tape drives, optical disk drives, etc., which may use an integrated drive electronics (IDE) interface, or a variation or enhancement thereof, such as enhanced IDE (EIDE) or ultra direct memory access (UDMA), or a small computer system interface (SCSI) based interface, or a variation or enhancement thereof, such as fast-SCSI, wide-SCSI, fast and wide-SCSI, etc, or a fiber channel-arbitrated loop (FC-AL) interface. 
   In the example shown in  FIG. 11 , memory  1108  includes database management routines  1112 , database  1114 , and operating system  1116 . Database management routines  1112  include software routines that provide the database management functionality of DBMS  1100 . Database management routines  1112  may include an SQL interface that accepts database queries using the SQL database query language, converts the queries to a series of database access commands, calls database processing routines to perform the series of database access commands, and returns the results of the query to the source of the query. For example, in an embodiment in which DBMS  1100  is a proprietary DBMS, such as the ORACLE® DBMS, SQL interface  108  may support one or more particular versions of SQL or extensions to SQL, such as the ORACLE® PL/SQL extension to SQL. 
   Database  1114  includes a collection of information organized in such a way that computer software can select, store, and retrieve desired pieces of data. Typically, database  1114  includes a plurality of data tables, such as georaster table  904  and raster data table  906 , a plurality of indexes, such as indexes  912  and  914 , and other data, such as BLOBs  910  and georaster system data  916 . 
   In addition, as shown in  FIG. 11 , the present invention contemplates implementation on a system or systems that provide multi-processor, multi-tasking, multi-process, and/or multi-thread computing, as well as implementation on systems that provide only single processor, single thread computing. Multi-processor computing involves performing computing using more than one processor. Multi-tasking computing involves performing computing using more than one operating system task. A task is an operating system concept that refers to the combination of a program being executed and bookkeeping information used by the operating system. Whenever a program is executed, the operating system creates a new task for it. The task is like an envelope for the program in that it identifies the program with a task number and attaches other bookkeeping information to it. Many operating systems, including UNIX®, OS/2®, and WINDOWS®, are capable of running many tasks at the same time and are called multitasking operating systems. Multi-tasking is the ability of an operating system to execute more than one executable at the same time. Each executable is running in its own address space, meaning that the executables have no way to share any of their memory. This has advantages, because it is impossible for any program to damage the execution of any of the other programs running on the system. However, the programs have no way to exchange any information except through the operating system (or by reading files stored on the file system). Multi-process computing is similar to multi-tasking computing, as the terms task and process are often used interchangeably, although some operating systems make a distinction between the two. 
   It is important to note that while the present invention has been described in the context of a fully functioning data processing system, those of ordinary skill in the art will appreciate that the processes of the present invention are capable of being distributed in the form of a computer readable medium of instructions and a variety of forms and that the present invention applies equally regardless of the particular type of signal bearing media actually used to carry out the distribution. Examples of computer readable media include recordable-type media such as floppy disc, a hard disk drive, RAM, and CD-ROM&#39;s, as well as transmission-type media, such as digital and analog communications links. 
   Although specific embodiments of the present invention have been described, it will be understood by those of skill in the art that there are other embodiments that are equivalent to the described embodiments. Accordingly, it is to be understood that the invention is not to be limited by the specific illustrated embodiments, but only by the scope of the appended claims.