Updating soil information with digital soil mapping

De Bodemkaart van Nederland, schaal 1:50.000, is de belangrijkste bron van bodeminformatie in Nederland. Deze kaart raakt echter in gebieden met veengronden verouderd. Door intensief gebruik van deze gronden verdwijnt het veen. Actualisatie van de bodemkaart is daarom noodzakelijk. Bas Kempen promoveerde op zijn onderzoek hiernaar

Spatial Analysis of Air Particulate Pollution Distributions and Its Relation to Real Property Value in Beijing, China

Air particulate pollution contributes the major air pollution in Beijing, China. In this research, concentrations of air particulate pollutants were measured at a total of twenty-three field locations in the urban districts of Beijing applying a laser particle counter in June and December 2015. Geographic Information System (GIS) was utilized to study the two and three-dimensional spatial distributions of air particulate pollution (PM0.5, PM1.0, PM2.5, PM5.0, PM10). Geostatistical or spatial statistical models were applied to interpolate the spatial distributions of air particulate pollution and real property values in the study area. Geographically Weighted Regression (GWR) was applied to analyze the spatial relationships of air particulate pollution and distribution of real property values. The three-dimensional analysis was conducted to illustrate vertical spatial distributions of air particulate pollution for each of the twenty-three field survey profiles in ArcGIS. Temporal distributions of air particulate pollution within 10 hours daytime at two field survey locations were analyzed. The results show that the concentrations of different sizes of air particulate pollutants in urban areas of Beijing distribute differently with different spatial patterns. The spatial distributions of real property values indicate that the highest value occurred in the northwestern and the central parts of Beijing both in the June and December 2015. There is no significant relationship of real property values and the intensity of air particulate pollution. Therefore, we suggest that the spatial distribution factors of air particulate pollution in Beijing is not a major factor for people to purchase real properties as homes

Environmental risk assessment in the mediterranean region using artificial neural networks

Los mapas auto-organizados han demostrado ser una herramienta apropiada para la clasificación y visualización de grupos de datos complejos. Redes neuronales, como los mapas auto-organizados (SOM) o las redes difusas ARTMAP (FAM), se utilizan en este estudio para evaluar el impacto medioambiental acumulativo en diferentes medios (aguas subterráneas, aire y salud humana). Los SOMs también se utilizan para generar mapas de concentraciones de contaminantes en aguas subterráneas simulando las técnicas geostadísticas de interpolación como kriging y cokriging. Para evaluar la confiabilidad de las metodologías desarrolladas en esta tesis, se utilizan procedimientos de referencia como puntos de comparación: la metodología DRASTIC para el estudio de vulnerabilidad en aguas subterráneas y el método de interpolación espacio-temporal conocido como Bayesian Maximum Entropy (BME) para el análisis de calidad del aire. Esta tesis contribuye a demostrar las capacidades de las redes neuronales en el desarrollo de nuevas metodologías y modelos que explícitamente permiten evaluar las dimensiones temporales y espaciales de riesgos acumulativos

Off-System Public Roads Annual Average Daily Traffic (AADT) Estimation Study

This report describes a process to estimate AADT on non-Federal-Aid public roads (collectively called \u201coff-system\u201d roads) in Idaho. This will provide additional data for ITD and regional and local transportation agencies to conduct analysis, and it will meet new federal requirements for estimating AADT on all public roads. The report includes a review of AADT estimation approaches in research and in practice, documentation of ITD\u2019s current AADT estimation process, and summaries of federal guidance. It also includes an inventory of potential data sources. The project team proposed three methods (related to regression, travel demand models, and geospatial interpolation), and the technical advisory committee (TAC) selected the geospatial interpolation approach based on its flexibility, understandability, moderate technical requirements, and accuracy. Therefore, this report also details how to implement the geospatial interpolation method for estimating off-system AADT. Some methodological decisions remain to be made based on the data (such as the specific geospatial interpolation technique and variables to include), so the report describes the decisions to be made and how to approach them. Finally, the report provides an implementation and validation plan with next steps, implementation roles, schedule, and statistics for use in model validation. This process can be implemented using tools in Esri ArcGIS and Python