boundless spatial

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Oracle Spatial Field Creation index

For example, we want to create an index for the geometry field of base_passenger_station. The specific statements are as follows. INSERT into User_sdo_geom_metadata (table_name,column_name,diminfo,srid) VALUES (' base_passenger_station ', ' GEOMETRY ', Mdsys. Sdo_dim_array (Mdsys. Sdo_dim_element (' X ', -180,180,0.005), Mdsys. Sdo_dim_element (' Y ', -90,90,0.005)), 4326); CREATE INDEX Base_pgr_station_geometry_spix on Base_passenger_station (GEOMETRY) Indextype is Mdsys. Spatial_index; In the

The Java language in the backend JSP file if the Jgeometry object provided by Oracle spatial is manipulated

page times wrong jgeometry is undefined type. Later did not report this mistake, but still have the problem, always thought still this question, thought jgeometry not use. (Because before the jgeometry wrong time, there are times wrong sometimes do not report errors.) )The program then removes the Sdo_geometry object from the Select Geom, then GetObject and load. Where the index in GetObject () refers to the total item index, not the index of the object. For example, the first property is a str

MongoDB spatial positioning (point) and distance retrieval

Based on MongoDB 2.6GeoJSON format{"type": "Point", "coordinates": [Lon (longitude), lat (latitude)]}Test dataDb.point.test.insert ({"Address": "Nanjing Lukou International Airport", "Loc": {"type": "Point", "coordinates": [118.783799,31.979234]}}) Db.point.test.insert ({"Address": "Nanjing Pukou Park", "Loc": {"type": "Point", "coordinates": [118.639523,32.070078]}}) Db.point.test.insert ({"Address": "Nanjing railway Station", "Loc": {"type": "Point", "coordinates": [118.803032,32.09248]}}) Db.

GP Database Notes-table structure query, table-occupied spatial query

The method of table structure query in GP database:Select D.nspname, Obj_description (d.oid), C.relname, Obj_description (c.oid), A.attnum, A.attname, E.data_type, Col_description (C.oid,a.attum), e.is_nullable, case where E.data_type ~ ' character 'Then e.character_maximum_length| | ‘‘where E.data_type ~ ' numeric 'Then ((' (' (' | | | E.numeric_precision) | | E.numeric_scale) | | ') 'Else 'EndFrom Pg_classLeft JOIN Pg_acctribute AOn a.atttypid = T.oidJoin Pg_namespace DOn d.oid = C.relnamespac

Spatial pyramid Pooling (SPP)-net (space pyramid Pool) notes

Original from: http://blog.csdn.net/xzzppp/article/details/51377731 Reference paper: Spatial pyramid Pooling in Deep convolutional Networks for Visual recognition A brief introduction to the reference paper 1. Introduction The spatial pyramid pooling makes it possible for any size feature map to be converted to a fixed size eigenvector, which is the significance of the

Oracle spatial constructs points, lines, polygons

Label:There are several ways to store data in ArcGIS from ARCSDE storage to Oracle, including binary long Raw, Esri St_geometry, and sdo_geometry based on Oracle spatial. Recently I have mostly studied the storage method based on Oracle spatial, where the type of Geometry column shape is mdsys.sdo_geometry type. With regard to the Sdo_geometry types defined by Oracle sp

GIS spatial analysis Topic 1: Searching bird habitat

1. Background A new road is planned to be built in a certain area, but the road will affect the habitat environment of a protected bird. Therefore, this issue must be considered in road planning. The purpose of this case is to find a suitable place for the bird habitat in the region for reference by the highway planning department. These ecological protected areas can be avoided during road construction.2. Living conditions of birds According to expert research, the areas adapted to the lives of

Spatial Interpolation Method Summary

In the field of scientific computing, spatial interpolation is a common important algorithm. Many related software have built-in algorithms.The Surfer software of godensoftware is very representative and has built-in comprehensive spatial interpolation algorithms, including:Inverse Distance to a power (Inverse Distance Weighted Interpolation)Kerkin Interpolation Method)Minimum curvature (minimum curvature)M

Spatial Clustering of Introduction to postgis (Introduction to st_snaptogrid)

Clustering: Indicates clustering and classification. This word is involved in postgis. Although the two terms use the same term, they indicate different meanings. One is index clustering, and the other is spatial clustering. Spatial Clustering: This is usually used in the point type. It can aggregate some points through the closeness or other features. The st_snaptogrid method is used to achieve this. The f

ArcGIS for Android spatial data WKT and JSON description

to JSON: String WKT. Read (string wktsr) JSON to WKT method: String WKT. Write (string jsonstr) 2)Based on the first point, you can set WKTGenerate ArcGIS for AndroidRy. Read the WKT string of the Ry from the spatialite database: Select astext (geometry) from test Convert the WKT string to JSON and convert the JSON string to a ry object through the jsontogeometry method of geometryengine. String STR = "{\" rings \ ": [[1007664.4779535953, 3710553.4649297176], [957962.4793888753, 3190110.9788053

ARCGIS SDE Spatial Processing

feature service to a spatial data server.St_raster installation as optional operation. For instructions, see Installing the St_raster type in Oracle.Note:If your Oracle database is installed on a Windows server, but you do not have an ArcSDE application server installed, you may need to install the Microsoft Visual C + + SP1 Redistributable Package (x64). If you do not have a Microsoft Visual C + + SP1 Redistributable Package (x64) on your Oracle ser

"University calculus"-chape10-vector and spatial geometry-cross product

Introduction of the concept of cross-product:In order to measure the tilt state of a straight line in the plane, we introduce the concept of inclined angle. By establishing tanα= K in a Cartesian coordinate system, we realize the connection between geometric relations and algebraic relationships, which in fact is a core of solving geometrical problems with computers, and the computer is doing numerical operations, so what you need to do is to express the relations in algebraic relation. In space

Bron Filter--a data structure with high spatial efficiency

memory are required if you store billions of email address. A generic server cannot be stored unless it is a supercomputer.Second, Bron filter2.1 PrincipleIf you want to determine whether an element is in a collection, it is common to think of saving all the elements in the collection and then determining by comparison. Lists, trees, hash tables (also known as hash tables, hash table) and other data structures are this way of thinking. But as the elements in the collection increase, we need mor

[Digital Image processing]3*3 template gray image spatial domain transform

1function [] =PicSmooth0 (A, s)2%PicSmooth0 here to show a summary of this function3%picsmooth0 (A,s) A is the image matrix S3 Transformation Matrix4%detailed instructions are shown here5[m,n,a]=size (A);6 ifA = =37b=Rgb2gray (A);8 Else9b=A;Ten End Oneb=Double(B); % prevent overflow Ap=zeros (m,n); -k=0; -sum=0; the[m,n]=size (s); - if(m~=3|| n~=3) -fprintf ('Please enter the correct 3*3 spatial domain smoothing template'); - Else + forI=1:3

SOLR similarity nouns: VSM (vector space model) vector spatial models

Recently want to learn the next Lucene, the previous run of the demo will feel very magical, what principle, especially to find the highest similarity, the best results. Simply jump directly to this question, a lot of data are mentioned in the VSM (vector space model) is a vector spatial models, according to this model can be the search results of the optimization of the screening, and currently do not know how to prove that only by virtue of imaginat

UVA806 Spatial Structures

Spatial Structures Computer graphics, image processing, and GIS (geographic information systems) all do use of a data structure called a Qu Adtree. Quadtrees represent regional or block data efficiently and support efficient algorithms for operations like the Union and Intersection of images.A quadtree for a black and white image are constructed by successively dividing the image to four equal quadrants. If all of the pixels in

The core technology of unmanned factory is three-dimensional image modeling and spatial positioning

technology is not mature, the development of the robot obstacle is image recognition and spatial positioning. There is no high-speed image recognition chip, the development of industrial robot cost is very high, Foxconn has no chip development technology, can only develop simple robotic auxiliary assembly. GPU image processing chips may contribute to the development of image recognition chips.And the CAD software can print out the model, but can not

Time complexity and spatial complexity of the algorithm

The time complexity and spatial complexity of the Time complexity for---> Algorithms(1) Time frequency an algorithm implementation of the time spent, from the theoretical can not be calculated, must be on the machine to run the test to know. But we can not and do not need to test each algorithm, just know which algorithm spends more time, which algorithm spends less time on it. And the time that an algorithm spends is proportional to the number of exe

The number of occurrences of each element in the statistical array [1-n], the time complexity O (n), the spatial complexity O (1), the array structure can be changed

* Count the occurrences of each element in the array* The array length is N, and the range of each element is [1,n].* Count the number of occurrences of each element, requiring a time complexity of O (N) and a spatial complexity of O (1). You can modify the values of the elements in the array.** Idea: Traverse to each element, the (element value-1) as the subscript value, the subscript of the element assignment (if positive, assignment-1; if negative,

convolutional Patch Networks with Spatial Prior for Road Detection and Urban Scene understanding

convolutional Patch Networks with Spatial Prior for Road Detection and Urban Scene understandingDeep learning ideas more and more fire, in this year's CVPR 2015 articles related articles have more than 20, can be seen is very fire. I am also happy to see this article in the recent context of semantic cutting and scene parsing.ausingaofandandwhileattheof Jena.The article says it can perform well on Windows, Mac and Linux systems, and can support OpenCL

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