Geospatial characterization of road infrastructure through Machine Learning in the district of San Isidro de El General
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| Autores: | , |
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| Formato: | artículo original |
| Estado: | Versión publicada |
| Data de Publicación: | 2024 |
| Descripción: | The proposal to get to know the estimated value of the road network of Pérez Zeledón will be to divide the roads by homogeneous zones, these present different prices per square meter; in addition, from the survey of some roads, estimation of quantities of materials with projects carried out in these zones. An approximate value of the road network of the district of San Isidro de El General is provided for the cost per square meter of road surfaces, linear meter of drainage system and square meter of sidewalks. Thus, the idea of creating a model integrated to QGis and determine these variables is concretized. Steps to complete the methodology: Data mining: the largest amount of information is extracted to integrate into the model, review of physical files of the roads, obtaining relevant layers of the network through the departments of Cadastre and Road Management in the Municipality of Perez Zeledon, geographic information from SNIT as hydrological layers, homogeneous zones and orthophotos. Then, to classify the results, supervised classification is performed to the spectrum of analysis (materials). Once the data is accommodated, the unsupervised classification by means of clustering algorithms, vector and raster tools, API complements integrated to the system, also as advanced digitizing or different geoprocesses of a GIS that optimally adjust the characteristics of the road network. These parameters are adapted to the models found in the budget bases and accurate estimates are established. The network is evaluated and its parametric estimation is concluded. |
| País: | Portal de Revistas TEC |
| Institución: | Instituto Tecnológico de Costa Rica |
| Repositorio: | Portal de Revistas TEC |
| Idioma: | Español |
| OAI Identifier: | oai:ojs.pkp.sfu.ca:article/6735 |
| Acceso en liña: | https://revistas.tec.ac.cr/index.php/tec_marcha/article/view/6735 |
| Palabra crave: | Data mining geographic information systems unsupervised classification supervised classification QGis road management Minería de datos sistemas de información geográfica clasificación no supervisada clasificación supervisada gestión vial |