Geo-referenced data

Description

A geo-referenced database represents the data gathered by a set of fixed sensors observing a particular phenomenon over a time period. It is a combination of spatial database and transactional/temporal/utility database .

Types of Geo-referenced databases

Geo-referenced transactional databases
Geo-referenced temporal databases
Geo-referenced utility database

Basic topics

Location/spatial database
Neighborhood database

1. Geo-referenced transactional database

A transactional database is said to be a geo-referenced transactional database if it contains spatial items. The format of this database is similar to that of transactional database . An example of a geo-referenced transactional database is as follows:

TID	Items
1	Point(0 0) Point(0 1) Point(1 0)
2	Point(0 0) Point(0 2) Point(5 0)
3	Point(5 0)
4	Point(4 0) Point(5 0)

Note: The rules to create a geo-referenced transactional database are same as the rules to create a transactional database. In other words, the format of creating a transaction in a geo-referential database is:

spatialItem1<sep>spatialItem2<sep>...<sep>spatialItemN

An example:

                    Point(0 0)    Point(0 1)  Point(1 0)
Point(0 0)    Point(0 2)  Point(5 0)
Point(5 0)
Point(4 0)    Point(5 0)
                    
                        

2. Geo-referential temporal database

A temporal database is said to be a geo-referential temporal database if it contains spatial items. The format of this database is similar to that of temporal database . An example of a geo-referential temporal database is as follows:

TID	Timestamp	Items
1	1	Point(0 0) Point(0 1) Point(1 0)
2	2	Point(0 0) Point(0 2) Point(5 0)
3	4	Point(5 0)
4	5	Point(4 0) Point(5 0)

Note: The rules to create geo-referential temporal database are same as the rules to create a temporal database. In other words, the format to create geo-referential temporal database is as follows:

timestamp<sep>spatialItem1<sep>spatialItem2<sep>...<sep>spatialItemN

An example:

                    1   Point(0 0)    Point(0 1)  Point(1 0)
 Point(0 0)    Point(0 2)  Point(5 0)
 Point(5 0)
 Point(4 0)    Point(5 0)
                        

3. Geo-referential utility database

A utility database is said to be a geo-referential utility database if it contains spatial items. The format of this database is similar to that of utility database . An example of a geo-referential utility database is as follows:

TID	Transactions (items and their prices)
1	(Point(0 0),100) (Point(0 1),42) (Point(1 0), 20)
2	(Point(0 0), 100) (Point(0 2), 10) (Point(5 0), 30)
3	(Point(5 0), 30)
4	(Point(4 0),30), (Point(5 0),40)

Note: The rules to create geo-referential utility database are same as the rules to create a utility database. In other words, the format to create geo-referential utility database is as follows:

                            timestamp<sep>spatialItem1<sep>spatialItem2<sep>...<sep>spatialItemN : total utility : utilityA<sep>utilityB<sep>...<sep>utilityN
                        

An example:

 Point(0 0)    Point(0 1)  Point(1 0):162:100    42  20
 Point(0 0)    Point(0 2)  Point(5 0):140:100    10  30
 Point(5 0):30:30
 Point(4 0)    Point(5 0):70:30  40
                        

Location/Spatial database

Description

A spatial database is a collection of spatial objects (or items), such as pixels, points, lines, and polygons. A sample spatial database generated from the set of items, I={a,b,c,d,e,f}, is shown in below table:

Item	Spatial information
a	Point(0 0)
b	Point(0 1)
c	Point(1 0)
d	Point(0 2)
e	Point(4 0)
f	Point(5 1)

Rules to create a location database

Every row must contain only two columns, namely item and its spatial information .
An item and its spatial information have to be seperated using a seperator, such as tab space.

Format of a location database

item<sep>spatialInformation

An example

                            a   Point(0 0)
b   Point(0 1)
c   Point(1 0)
d   Point(0 2)
e   Point(4 0)
f   Point(5 1)
                        

Neighborhood database

Description

A neighborhood database is a collection of geo-referenced items and their neighbors.
A geo-referenced item j is said to be a neighbor of another geo-referenced item i if the distance between them is no more than the user-specified maximum distance threshold value. That is, if distance(i,j) <=maximumDistance , we say j is a neighbor of i .
A sample neighborhood database generated from the set of geo-referenced items, I={a,b,c,d,e,f}, is shown in below table:

Item	Neighbors
Point(0 0)	Point(1 0) Point(0 1)
Point(1 0)	Point(0 0) Point(0 1) Point(2 0)
…	…

Rules to create a neighborhood database

Every row in the neighborhood file must contain only geo-referenced items.
First item in a row is the main geo-referenced item. Remaining items in a row represent the neighbors of main item.
All items in a row are seperated with a seperator, say tab space.
Note: Every item must repeat only once in a row.

Format to create a neighborhood database

item<seperator>NeighboringItem1<seperator>NeighboringItem2<seperator>...

An example

                            item1   item3   item4   item10
item2   item3   item5   item11  ...
...
                        

Procedure to generate neighborhood file

Step 1: Import the program

from PAMI.extras.neighbours import  createNeighborhoodFileUsingEuclideanDistance as alg

Step2: Specify the parameters

inputLocationFile='geoReferencedInputFile.csv'  #name of the input file
outputNeighborhoodFile='neighborhoodFile.csv'       #name of the output file
maximumDistance=10      #specify your own value
seperator='\t'      #default seperator.

Step 3: Call the program

alg.createNeighborhoodFileUsingEuclideanDistance(inputLocationFile,outputNeighborhoodFile,maximumDistance,seperator)