Modelos cartográficos en agricultura y medio ambiente: métodos de cálculo de cobertura arbórea, modelo de distribución de especies y modelo de pronostico de calidad de aire
[EN] The aim of this Thesis is to establish methodologies to improve agricultural produc-tion techniques, biodiversity conservation, and forecast of air quality, through the analytical capacity of Geographic Information Systems. Several methodologies are proposed to integrate both the geographic com...
| Autor: | |
|---|---|
| Formato: | tesis doctoral |
| Fecha de publicación: | 2016 |
| País: | España |
| Recursos: | Universitat Politècnica de València (UPV) |
| Repositorio: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia |
| Idioma: | español |
| OAI Identifier: | oai:riunet.upv.es:10251/62189 |
| Acesso em linha: | https://riunet.upv.es/handle/10251/62189 |
| Access Level: | acceso abierto |
| Palavra-chave: | SIG, agricultura de precisión, cobertura arbórea, riego, predicción de especies, contaminación, imágenes aéreas. BOTANICA BIOLOGIA VEGETAL INGENIERIA AGROFORESTAL |
| Resumo: | [EN] The aim of this Thesis is to establish methodologies to improve agricultural produc-tion techniques, biodiversity conservation, and forecast of air quality, through the analytical capacity of Geographic Information Systems. Several methodologies are proposed to integrate both the geographic component of data and methods, in order to provide a practical, transferable, and integrated solution to the increasing need for environmental studies at larger scales. Initially, a plot-based approach to detect fraction of tree cover from high spatial resolution images in an Irrigation Community is proposed. The calculation of quality rates for the management of Irrigation Communities is important, and requires accurate and up-to-date knowledge of water requirements of each specific crop. The computation of the shadow fraction of vegetation cover on large areas needs of systems to able to integrate the spatial component and enable accurate results. This study presents a shadow fraction approach based on classification of high spatial resolution orthoimages acquired within the Spanish National Plan of Survey of the Territory (PNOT). The results of the classification are subsequently used in a Geographic Information System for irrigation management. Secondly, methodology for the integration of geospatial data from different sources is presented. This method aims to predict actual vegetation models, on a forested Natural Park. The quantitative spatial information is used to characterize a 25 x 25 m grid, includes: (1) topographic descriptors and the solar irradiation metrics, (2) texture features computed from aerial photography, and (3) vegetation indices informing about the vegetation status. A multivariate method is proposed by overlapping layers in a GIS. The results, are tested using independent samples, and point out to the potential of these techniques to provide and to estimate actual vegetation maps as guide in the restoration of forest ecosystems. The last study, is a forecast and evaluation of air pollution related to transport systems in urban areas. The method relies on three different geospatial data sourcess: meteorology conditions, traffic emissions, and street geometry. An inverse model calculation of dispersion of pollutants to determinate emissions of the actual car feet to provide factor emission the methodology uses. A cartographical model is defined in to integrate the geospatial data sets (i.e. measured CO concentrations, Cadastral data, and LIDAR data) with mathematical applied. The results of factor emissions have been tested in other cities. The defined model is used to estimate spatial distribution air pollutant in streets of Valencia city center and the results are represented via maps. The integration of spatial components to traditional methods allows to predict and to describe as working the phenomena in the nature. Additionally, the production of maps of phenomena improves the potential of the analysis, enable to reach more meaningful results. In order to understand and research interactions on them, these systems enable to combine different analysis disciplines and methods. For example, the atmosphere and the environment can be integrated throughout scale in space and time. This Thesis opens up various lines of research to improve our knowledge on agriculture, natural environment, and air quality. Future research may combination and fusion of methodologies to better understand the influence of vegetation cover on air quality, in order to improving the forecast of urban pollution caused by car traffic emissions. |
|---|