Predicción de variables dasométricas del Inventario Forestal Nacional mediante datos LIDAR con técnicas de minera de datos
| dc.contributor.advisorTFE | Álvarez-Mozos, Jesús | |
| dc.contributor.advisorTFE | Sanz Delgado, José Antonio | |
| dc.contributor.affiliation | Escuela Técnica Superior de Ingenieros Agrónomos | es_ES |
| dc.contributor.affiliation | Nekazaritza Ingeniarien Goi Mailako Eskola Teknikoa | eu |
| dc.contributor.author | Segú Tell, Jordi | |
| dc.coverage.spatial | east=-1.6453898881912976; north=42.81266896723002; name=Navarra, España | |
| dc.date.accessioned | 2018-10-26T13:06:33Z | |
| dc.date.available | 2023-10-01T23:00:12Z | |
| dc.date.issued | 2018 | |
| dc.date.updated | 2018-10-23T11:16:19Z | |
| dc.description.abstract | The management of forest resources is essential for the development of our society. This requires a forest management planning based on innovative studies, according to new technologies and seeking to lower costs. In this project, a methodology has been developed for the extraction of predictive regression models to determine the main dasometric variables of the beech forest layer with over 70% of the forest cover density in Navarre. For this purpose, data mining techniques and Python as programming language have been used. The inputs of the work are: data from the plots of the national forest inventory (dependent variables) and statistics derived from the LIDAR-PNOA flight for these same plots (independent variables) obtained with the LasTools software. The output is the model that best fits the input data, determined by the methodology used. | en |
| dc.description.degree | Máster Universitario en Sistemas de Información Geográfica y Teledetección por la Universidad Pública de Navarra | es_ES |
| dc.description.degree | Informazio Geografikoko Sistemetako eta Teledetekzioko Unibertsitate Masterra Nafarroako Unibertsitate Publikoan | eu |
| dc.embargo.lift | 2023-10-01 | |
| dc.embargo.terms | 2023-10-01 | |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.uri | https://academica-e.unavarra.es/handle/2454/31249 | |
| dc.language.iso | spa | en |
| dc.rights.accessRights | info:eu-repo/semantics/openAccess | |
| dc.subject | LIDAR | es_ES |
| dc.subject | IFN | es_ES |
| dc.subject | Python | es_ES |
| dc.subject | Data mining | es_ES |
| dc.subject | Fagus sylvatica | es_ES |
| dc.subject.geo | Ingeniería cartográfica, geodésica y fotogrametría | es_ES |
| dc.title | Predicción de variables dasométricas del Inventario Forestal Nacional mediante datos LIDAR con técnicas de minera de datos | es_ES |
| dc.type | info:eu-repo/semantics/masterThesis | |
| dspace.entity.type | Publication | |
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