Curdin Derungs

From text to landscape: locating, identifying and mapping the use of landscape features in a Swiss Alpine corpus

In this paper, we demonstrate how a large corpus, consisting of about 10 000 articles describing Swiss alpine landscapes and activities and dating back to 1864, can be used to explore the use of language in space. In a first step, we link landscape descriptions to geospatial footprints, which requires new methods to disambiguating toponyms referring to natural features. Secondly, we identify natural features used to describe landscapes, which are compared and discussed in the light of previous work based on controlled participant experiments in laboratory settings and more exploratory ethnographic studies. Finally, we use natural features in combination with geospatial footprints to investigate variations in landscape descriptions across space. Our contributions are threefold. Firstly, we show how a corpus composed of detailed descriptions of natural landscapes can be georeferenced and mapped using density surfaces and an adaptive grid linking footprints to articles. Secondly, 95 natural features are identified in the corpus, forming a vocabulary of terms reflecting known basic levels and their relationships to other more specific landscape features. Thirdly, we can explore the use of natural features in broader spatial and temporal contexts than is possible in typical ethnographic work, by exploring when and where particular terms are used within Switzerland with respect to our corpus. On the one hand, this enables us to characterize individual regions and, on the other hand, to measure similarity between regions, on the basis of associated natural features. Our methods could be adapted to different types of corpus, for instance, referring to fine granularity entities in urban landscapes. Our results are potential building blocks for attaching place-related descriptions to automatically generated sensor data such as photographs or satellite images.

Soil attributes and microclimate are important drivers of initial deadwood decay in sub-alpine Norway spruce forests.

Deadwood is known to significantly contribute to global terrestrial carbon stocks and carbon cycling, but its decay dynamics are still not thoroughly understood. Although the chemistry of deadwood has been studied as a function of decay stage in temperate to subalpine environments, it has generally not been related to time. We therefore studied the decay (mass of deadwood, cellulose and lignin) of equal-sized blocks of Picea abies wood in soil-mesocosms over two years in the Italian Alps. The 8 sites selected were along an altitudinal sequence, reflecting different climate zones. In addition, the effect of exposure (north- and south-facing slopes) was taken into account. The decay dynamics of the mass of deadwood, cellulose and lignin were related to soil parameters (pH, soil texture, moisture, temperature) and climatic data. The decay rate constants of Picea abies deadwood were low (on average between 0.039 and 0.040y(-1)) and of lignin close to zero (or not detectable), while cellulose reacted much faster with average decay rate constants between 0.110 and 0.117y(-1). Our field experiments showed that local scale factors, such as soil parameters and topographic properties, influenced the decay process: higher soil moisture and clay content along with a lower pH seemed to accelerate wood decay. Interestingly, air temperature negatively correlated with decay rates or positively with the amount of wood components on south-facing sites. It exerted its influence rather on moisture availability, i.e. the lower the temperature the higher the moisture availability. Topographic features were also relevant with generally slower decay processes on south-facing sites than on north-facing sites owing to the drier conditions, the higher pH and the lower weathering state of the soils (less clay minerals). This study highlights the importance of a multifactorial consideration of edaphic parameters to unravel the complex dynamics of initial wood decay.

From Space to Place: Place-Based Explorations of Text

New data sources, for example in the form of geotagged image libraries and digitised archives of historical text documents, provide us with new opportunities for exploring how place is described. Using a framework derived from work in human geography and information science, we illustrate how there is more to place than names and coordinates. Through a set of case studies we explore different aspects of the seemingly trivial query ‘mountains in the Alps’ addressing a range of issues including ambiguity, the use of vernacular names, ways in which concepts such as mountain are used in different locations and by different groups, approaches to automatically generating macro-maps in space and time and, finally, techniques allowing regions to be characterised and compared based on the terms used to describe them. The use of all these methods in combination allows us to come closer to a meaningful representation of place in the sense of human geography within the context of Geographic Information Science. Howev...

The Meanings of the Generic Parts of Toponyms: Use and Limitations of Gazetteers in Studies of Landscape Terms

Are the contents of toponyms meaningless, as it is often claimed in linguistic literature, or can the generic parts in toponyms, such as hill in Black Hill, be used to infer landscape descriptions? We investigate this question by, firstly, linking gazetteer data with topographic characteristics, and, secondly, by conducting analysis of how the use of landscape terms might have changed over time in a historic corpus. We thus aim at answering a linguistic, and ethnophysiographic, research question through digital input data and processing. Our study area is Switzerland and our main focus is on geographic eminences, and in particular on the use of the terms Spitze, Horn and Berg. We show that most prominent generic parts in toponyms show expected topographic characteristics. However, not all generic parts strictly follow this rule, as in the case of Berg. Some generic parts have lost their meaning in standard language over time (e.g. Horn). We therefore put a cautionary note on the use of generic parts in toponyms in landscape studies, but point out that the subtle details of these differences provide rich topics for future research.

Mining nearness relations from an n-grams Web corpus in geographical space

Interacting with spatial data effectively requires systems that not only process references to locations, but understand spatial natural language. Empirical research has demonstrated that near is vague, asymmetric and context dependent. We explore near in language using Microsoft Web n-grams for expressions of the form A near*, where A are placenames referring to different spatial granularities, ranging from points of interest to large U.S. cities and * are autocomplete suggestions for placenames. Analyzing the extracted expressions requires consideration of semantic and referent ambiguity. With more than 200,000 expressions we show not only what is considered to be near at different scales, but also produce intuitive maps of nearness for different locations.

Creating test collections from user generated content for GIR evaluation

Evaluation of the effectiveness of Geographic Information Retrieval (GIR) systems is challenging and time consuming. We describe an approach to such evaluations, where we use user generated content in the form of text and associated metadata to build a large test colletion automatically. We can thus show that the UGC test collection is useful for evaluating and exploring some of the critical aspects of a GIR, for instance by submitting large numbers of queries.

Environmental factors drive language density more in food-producing than in hunter–gatherer populations

Linguistic diversity is a key aspect of human population diversity and shapes much of our social and cognitive lives. To a considerable extent, the distribution of this diversity is driven by environmental factors such as climate or coast access. An unresolved question is whether the relevant factors have remained constant over time. Here, we address this question at a global scale. We approximate the difference between pre- versus post-Neolithic populations by the difference between modern hunter–gatherer versus food-producing populations. Using a novel geostatistical approach of estimating language and language family densities, we show that environmental—chiefly climate factors—have driven the language density of food-producing populations considerably more strongly than the language density of hunter–gatherer populations. Current evidence suggests that the population dynamics of modern hunter–gatherers is very similar to that of what can be reconstructed from the Palaeolithic record. Based on this, we cautiously infer that the impact of environmental factors on language densities underwent a substantial change with the transition to agriculture. After this transition, the environmental impact on language diversity in food-producing populations has remained relatively stable since it can also be detected—albeit in slightly weaker form—in models that capture the reduced linguistic diversity during large-scale language spreads in the Mid-Holocene.

Are prominent mountains frequently mentioned in text? Exploring the spatial expressiveness of text frequency

ABSTRACT Data-driven GIScience shows a growing interest in making spatial information from large text data. In this paper, we quantify and thus evaluate the relation between text frequency and properties of the outer-text, geographic setting by comparing text frequencies of mountain names to the respective geomorphometric characteristics. We focus on some 2000 unique mountain names that appear some 50,000 times in a large compilation of texts on Swiss alpine history. The results on the full data set suggest only a weak relation: only 5–10% of the variation in the text frequency being explained by the respective geomorphometric characteristics. However, an analysis of multiple scales allows us to identify a Simpson’s Paradox. What appears to be ‘noise’ in the analysis of all mountains in the whole of Switzerland shows significant local signals. Small spatial extents, found all over Switzerland, can show considerably strong correlations between text frequency and spatial prominence, with up to 90% of the total variation explained. We argue that our findings have practical implications for data-driven GIScience. Retrieving meaningful spatial information from text might only be possible if the spatial scale of analysis reflects the spatial scale described in the input text documents.

Prediction of Soil Formation as a Function of Age Using the Percolation Theory Approach

Recent modeling and comparison with field results showed that soil formation by chemical weathering, from bedrock or unconsolidated material, is limited largely by solute transport. Chemical weathering rates are proportional to solute velocities. Nonreactive solute transport described by non-Gaussian transport theory appears compatible with soil formation rates. This change in understanding opens new possibilities for predicting soil production and depth across orders of magnitude of time scales. Percolation theory for modeling the evolution of soil depth and production was applied to new and published data for alpine and Mediterranean soils. The first goal was to check whether the empirical data conform to the theory. Secondly we analyzed discrepancies between theory and observation to find out if the theory is incomplete, if modifications of existing experimental procedures are needed and what parameters might be estimated improperly. Not all input parameters required for current theoretical formulations (particle size, erosion and infiltration rates) are collected routinely in the field; thus, theory must address how to find these quantities from existing climate and soil data repositories, which implicitly introduces some uncertainties. Existing results for soil texture, typically reported at relevant field sites, had to be transformed to results for a median particle size, d50, a specific theoretical input parameter. The modeling tracked reasonably well the evolution of the alpine and Mediterranean soils. For the Alpine sites we found, however, that we consistently overestimated soil depths by approximately 45%. Particularly during early soil formation, chemical weathering is more severely limited by reaction kinetics than by solute transport. The kinetic limitation of mineral weathering can affect the system until 1kyr to a maximum of 10kyr of soil evolution. Thereafter, solute transport seems dominant. The trend and scatter of soil depth evolution is well captured, particularly for Mediterranean soils. We assume that some neglected processes, such as bioturbation, tree throw, and land use change contributed to local reorganization of the soil and thus to some differences to the model. Nonetheless, the model is able to generate soil depth and confirms decreasing production rates with age. A steady state for soils is not reached before about 100 kyr.

Spatial characteristics of a large web n-gram corpus

N-gram corpora, though prominently used to structure and index large natural language corpora, are rarely in the focus of GIR. In this study we describe a step in this direction by characterizing spatial information in a large Web n-gram corpus provided by Microsoft. We explore how continent and country toponyms are represented in this corpus and if basic topological relations can be correctly retrieved. Results suggest that toponym ambiguity has major impact and that although retrieved topological relations are often correct, recall is considerably low. We conclude that further research is required if more fine grained spatial information is to be retrieved from n-grams.