Applying Supervised Clustering to Landsat MSS Images into GIS-Application

Applying Supervised Clustering to Landsat MSS Images into GIS-Application

Miguel Torres (Centro de Investigación en Computación, Instituto Politécnico Nacional, Mexico City, Mexico), Marco Moreno-Ibarra (Centro de Investigación en Computación, Instituto Politécnico Nacional, Mexico City, Mexico), Rolando Quintero (Centro de Investigación en Computación, Instituto Politécnico Nacional, Mexico City, Mexico) and Giovanni Guzmán (Centro de Investigación en Computación, Instituto Politécnico Nacional, Mexico City, Mexico)
Copyright: © 2013 |Pages: 9
DOI: 10.4018/ijksr.2013070110
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Abstract

In this paper, the authors describe and implement an algorithm to perform a supervised classification into Landsat MSS satellite images. The Maximum Likelihood Classification method is used to generate raster digital thematic maps by means of a supervised clustering. The clustering method has been proved in Landsat MSS images of different regions of Mexico to detect several training data related to the geographic environment. The algorithm has been integrated into Spatial Analyzer Module to improve the decision making model and the spatial analysis into GIS-applications.
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2. Architecture Of Gis-Application

The GIS-application has been developed using client-server architecture. This tool contains the following components:

  • Spatial Database (SDB): This module stores the spatial data (vector and raster) into a hierarchical structure. SDB contains a spatial dynamic index mechanism to organize physically the geographical objects according to the basic primitive of representation (Rigaux, Scholl, & Voisard, 2002);

  • ArcMap GUI: This mechanism is a common wateway, which is used to process the requests of the users. The results obtained by the spatial analysis are rendered in this component;

  • Administration Module (AM): AM is used to control all the processes of the GIS-application. This module receives all the requests that the users have generated to perform any spatial analysis;

  • Spatial Analyzer Module (SAM): This module has been designed to make spatial analysis procedures. It includes the supervised clustering method to identify the characteristics of the raster data. SAM is composed by several methods to make spatial and visual analysis with the geo-information.

The functional mechanism of the GIS-application is the following: ArcMap users need to make a request. This request is sent by DCOM technology to the AM to interpret, control, and interact with the Enterprise GIS. AM processes the request and sends the parameters to SAM. In the Enterprise GIS, it is necessary to verify the definition to obtain the spatial data from SDB. The geographical objects are stored in the spatial database, in which they will be analyzed by SAM. SAM is focused on detecting the characteristics of vector and raster data.

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