Kandidater udgået fra Københavns Universitets Geografiske Institut 1966–71

Christensen, Leif: Faststående og omlejrede Saale-morånelersaflejringer. Et eksempel fra Szdding-området, Vestjylland. Geografisk Tidsskrift 82: 91–94. Copenhagen, Dec. 1, 1982.

In situ clayey till materials on the Skovbjerg Bakkea, western Jutland can be recognized by crop-marks revealing pseudomorphs of ice-wedge polygons in orthogonal, random orthogonal and hexagonal patterns. The tills inside these polygonal patterns have high shear-strength values as measured by vane tests. Remoulded fossil solifluction deposits of till origin reveal stripes and deformed polygonal patterns in the crops. High strength as measured by vane are encountered below fossil solifluction deposits 4 meters below ground.     

The Landscape of Diversity in U.S. Higher Education Geography

Palynological analyses were completed for the A and B horizons of a forested Mollic Hapludalf to determine type, amount, and distribution of pollen and spores within the soil solum. Hypotheses regarding the origin of pollen and the mechanisms of its movement within soil bodies are also advanced. Pollen downwash within the mineral soil seems to be very slow and confined to the uppermost porous and most homogenized part of the solum. The predominance of non-arboreal pollen at depth was believed to be a result of deposition with the loess parent material. High arboreal pollen frequencies in the upper horizons coupled with increases in non-arboreal types at depth indicate gradual ongoing mixing from the present vegetation into the soil.     

Exploring the Impact of Contextual Information on Student Performance and Interest in Open Humanitarian Mapping

The opportunity to engage university students in authentic, open humanitarian mapping raises important questions about how to guide the quality and productivity of volunteer spatial contributions while providing a valuable learning experience. It presents the unique chance to pique new mappers’ interest, satisfaction, and confidence in spatial technologies in particular, and technology in general, as well as pique their interest in the people and places that are served by the humanitarian mapping projects. This article shares the findings of a study that explores the importance of sharing authentic contextual information about the purpose of the humanitarian mapping task. Two groups of beginner mappers were given mapping tasks, with only one group being provided details on the purpose. Comparisons were made on their respective performance and changes in affective response to a series of questions about technology, education, good citizenship, and empathy. Measures of the quantity and quality of spatial data produced; their respective levels of interest, satisfaction, and confidence in technology; and affective responses before and after mapping show the relative effects of contextual information. Results provide insights about the potential effectiveness of authentic instruction on the performance of mapping as well as the potential effect on mappers themselves. Key Words: citizenship, data quality, empathy, humanitarian mapping, volunteered geographic information.     

Ornamental plants and the production of nature(s) in the Spanish real estate boom and bust: the case of Alicante

The Spanish real estate boom and bust of the 2000s caused immense economic, social, and environmental changes across the country. Massive urbanization, however, does not necessarily entail the end of nature and natural processes, instead marking a radical transformation of environments and societies. Through a political ecology approach, we analyze how ornamental species have become a fundamental part of new natures induced by urbanization in the Spanish province of Alicante. We connect the economic and ecological characteristics of ornamental plants like the palm tree to urbanization and real estate trends in Alicante. Our evidence indicates that, in Alicante, economic recession and environmental crises (manifested in the pests affecting palm trees) have mutually reinforced one other, creating a new geography of ecological desolation in many areas.     

Using auxiliary information to adjust fuzzy membership functions for improved mapping of soil qualities

Agronomic soil management and decision-making frequently requires the joint classification of soil variables. Fuzzy set theory is often used to accomplish this task. This paper addresses the issues of objectively defining fuzzy membership functions (FMF) and reducing classification uncertainty with hedge operators. As an example, soil in North-east Thailand was classified according to its inherent potential to support the recovery of a rice crop after a drought spell. The utility of auxiliary information not directly included in the classification was explored. A tree cover density index was employed for an objective definition of the FMF to classify soil organic matter content and plant-available potassium. Mapping units were allocated to classes having low, medium or high availability of these plant nutrients. It was shown that crisp, Boolean style classifications severely misclassify land in all but one class. Adjusted FMF decreased the uncertainty contained in thematic class maps. Single FMF values for soil organic matter and plant-available K were then jointly modelled and the soil classified as having low, medium and high potential for rice plants to recover from drought impacts. The very and more or less hedge operators were applied to increase or decrease the joint FMF values using farmer' knowledge about soil fertility. Overall classification uncertainty using FMF was decreased by 14% if the standard FMF was adjusted and the generated membership values were hedged. It was shown that adjusting FMF influenced the uncertainty components vagueness and ambiguity differently; the former increased slightly but the latter was drastically reduced.     

Possibilities and limits of prospective GIS land cover modelling—a compared case study: Garrotxes (France) and Alta Alpujarra Granadina (Spain)

This study focuses on the possibilities and the limits of a prospective GIS land cover modelling applied to two case studies (France and Spain). The methodology, based on available GIS tools, consists of using earlier land cover maps and relevant environmental factors (calibration data) to model actual, known land cover to validate the model. The model aggregates Markov chain analysis for time prediction and multi‐critera evaluation, multi‐objective evaluation and cellular automata to perform spatial contiguity of modelled land cover scores. The first results give an accurate, pixel by pixel prediction rate of approximately 75%. An important issue of this study consists of analysing prediction residues to improve the model.     

An OLS regression model for context-aware tile prefetching in a web map cache

The increasing popularity of web map services has motivated the development of more scalable services in the spatial data infrastructures. Tiled map services have emerged as a scalable alternative to traditional map services. Instead of rendering map images on the fly, a collection of pre-generated image tiles can be served very fast from a server-side cache. However, during the start-up of the service, the cache is initially empty and users experience a poor quality of service. Tile prefetching attempts to improve hit rates by proactively fetching map images without waiting for client requests.

While most popular prefetching policies in traditional web caching consider only the previous access history to make predictions, significant improvements could be achieved in web mapping by taking into account the background geographic information.

This work proposes a regressive model to predict which areas are likely to be requested in the future based on spatial cross-correlation between an unconstrained catalog of geographic features and a record of past cache requests. Tiles that are anticipated to be most frequently requested can be pre-generated and cached for faster retrieval. Trace-driven simulations with several million cache requests from two different nation-wide public web map services in Spain demonstrate that accurate predictions and performance gains can be obtained with the proposed model.     

The role of visualisation in the choice of stationary non-separable space–time covariance functions: an application to air pollution data

Modelling spatio-temporal dependencies resulting from dynamic processes that evolve in both space and time is essential in many scientific fields. Spatio-temporal Kriging is one of the space–time procedures, which has progressed the most over the last few years. Kriging predictions strongly depend on the covariance function associated with the stochastic process under study. Therefore, the choice of such a covariance function, which is usually based on empirical covariance, is a core aspect in the prediction procedure. As the empirical covariance is not necessarily a permissible covariance function, it is necessary to fit a valid covariance model. Due to the complexity of these valid models in the spatio-temporal case, visualising them is of great help, at least when selecting the set of candidate models to represent the spatio-temporal dependencies suggested by the empirical covariogram. We focus on the visualisation of the most interesting stationary non-separable covariance functions and how they change as their main parameters take different values. We wrote a specialised code for visualisation purposes. In order to illustrate the usefulness of visualisation when choosing the appropriate non-separable spatio-temporal covariance model, we focus on an important pollution problem, namely the levels of carbon monoxide, in the city of Madrid, Spain.     

Estimation and prediction of the spatial occurrence of fish species using Bayesian latent Gaussian models

A methodological approach for modelling the occurrence patterns of species for the purpose of fisheries management is proposed here. The presence/absence of the species is modelled with a hierarchical Bayesian spatial model using the geographical and environmental characteristics of each fishing location. Maps of predicted probabilities of presence are generated using Bayesian kriging. Bayesian inference on the parameters and prediction of presence/absence in new locations (Bayesian kriging) are made by considering the model as a latent Gaussian model, which allows the use of the integrated nested Laplace approximation ( INLA ) software (which has been seen to be quite a bit faster than the well-known MCMC methods). In particular, the spatial effect has been implemented with the stochastic partial differential equation (SPDE) approach. The methodology is evaluated on Mediterranean horse mackerel (Trachurus mediterraneus) in the Western Mediterranean. The analysis shows that environmental and geographical factors can play an important role in directing local distribution and variability in the occurrence of species. Although this approach is used to recognize the habitat of mackerel, it could also be for other different species and life stages in order to improve knowledge of fish populations and communities.     

Similarity measures of conditional intensity functions to test separability in multidimensional point processes

Separability in the context of multidimensional point processes assumes a multiplicative form for the conditional intensity function. This hypothesis is especially convenient since each component of a separable process may be modeled and estimated individually, and this greatly facilitates model building, fitting, and assessment. This is also related to the problem of reduction in the number of dimensions. Following previous approximations to this problem, we focus on the conditional intensity function, by considering nonparametric kernel-based estimators. Our approach calculates thinning probabilities under the conditions of separability and nonseparability and compares them through divergence measures. Based on Monte Carlo experiments, we approximate the statistical properties of our tests under a variety of practical scenarios. An application on modeling the spatio-temporal first-order intensity of forest fires is also developed.