Diseño De Un Algoritmo Para Reconocimiento De Área De Crecimiento Urbano Utilizando Imágenes Quickbird
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This paper aims to design an algorithm for recognition of urban growth area. Currently the land for construction of houses in the city of Bogota is running low due to moderate population growth, ending wetlands and green areas of the city. The Engativa located in northwest of the city, in the last ten years has had a considerable urban growth. To comply to design a specific objective which is to perform an algorithm to identify the characteristics of areas according to their specific spectral signatures and evaluate the results obtained in field on the result of the algorithm is planting. To develop the algorithm they used logic programming by means of Matlab software, where a methodology based on four phases which are employed are: Analysis, Design, Development and Implementation; these stages provide the pillars to achieve the objective. The project contains a grid of 25 checkpoints on Google Earth with a KML extension, the images that this algorithm can post processing will be taken from the screen using the Google Earth software which come from the satellite Quickbird keeping them mainly with the TIF extension and JPEG, also will be able to perform the procedure with images beyond this with the above extensions. The post process is performed by means of comparison of digital levels between the images of the current zone and the area in previous years, this algorithm processed after two satellite images to know that these changes have had a level of housing construction waiting like a semi automatic product application where the user only have to interpret the images thrown by the algorithm.