A review of topographic controls on moraine distribution

Ice-marginal moraines are often used to reconstruct the dimensions of former ice masses, which are then used as proxies for palaeoclimate. This approach relies on the assumption that the distribution of moraines in the modern landscape is an accurate reflection of former ice margin positions during climatically controlled periods of ice margin stability. However, the validity of this assumption is open to question, as a number of additional, nonclimatic factors are known to influence moraine distribution. This review considers the role played by topography in this process, with specific focus on moraine formation, preservation, and ease of identification (topoclimatic controls are not considered). Published literature indicates that the importance of topography in regulating moraine distribution varies spatially, temporally, and as a function of the ice mass type responsible for moraine deposition. In particular, in the case of ice sheets and ice caps ( > 1000 km2), one potentially important topographic control on where in a landscape moraines are deposited is erosional feedback, whereby subglacial erosion causes ice masses to become less extensive over successive glacial cycles. For the marine-terminating outlets of such ice masses, fjord geometry also exerts a strong control on where moraines are deposited, promoting their deposition in proximity to valley narrowings, bends, bifurcations, where basins are shallow, and/or in the vicinity of topographic bumps. Moraines formed at the margins of ice sheets and ice caps are likely to be large and readily identifiable in the modern landscape. In the case of icefields and valley glaciers (10–1000 km2), erosional feedback may well play some role in regulating where moraines are deposited, but other factors, including variations in accumulation area topography and the propensity for moraines to form at topographic pinning points, are also likely to be important. This is particularly relevant where land-terminating glaciers extend into piedmont zones (unconfined plains, adjacent to mountain ranges) where large and readily identifiable moraines can be deposited. In the case of cirque glaciers (< 10 km2), erosional feedback is less important, but factors such as topographic controls on the accumulation of redistributed snow and ice and the availability of surface debris, regulate glacier dimensions and thereby determine where moraines are deposited. In such cases, moraines are likely to be small and particularly susceptible to post-depositional modification, sometimes making them difficult to identify in the modern landscape. Based on this review, we suggest that, despite often being difficult to identify, quantify, and mitigate, topographic controls on moraine distribution should be explicitly considered when reconstructing the dimensions of palaeoglaciers and that moraines should be judiciously chosen before being used as indirect proxies for palaeoclimate (i.e., palaeoclimatic inferences should only be drawn from moraines when topographic controls on moraine distribution are considered insignificant).

Manual mapping of drumlins in synthetic landscapes to assess operator effectiveness

Mapped topographic features are important for understanding processes that sculpt the Earth’s surface. This paper presents maps that are the primary product of an exercise that brought together 27 researchers with an interest in landform mapping wherein the efficacy and causes of variation in mapping were tested using novel synthetic DEMs containing drumlins. The variation between interpreters (e.g. mapping philosophy, experience) and across the study region (e.g. woodland prevalence) opens these factors up to assessment. A priori known answers in the synthetics increase the number and strength of conclusions that may be drawn with respect to a traditional comparative study. Initial results suggest that overall detection rates are relatively low (34–40%), but reliability of mapping is higher (72–86%). The maps form a reference dataset.

PREDICTING THE SPATIAL-DISTRIBUTION OF CLIMATE - TEMPERATURE IN GREAT-BRITAIN

1. The prediction and mapping of climate in areas between climate stations is of increasing importance in ecology.

2. Four categories of model, simple interpolation, thin plate splines, multiple linear regression and mixed spline-regression, were tested for their ability to predict the spatial distribution of temperature on the British mainland. The models were tested by external cross-verification.

3. The British distribution of mean daily temperature was predicted with the greatest accuracy by using a mixed model: a thin plate spline fitted to the surface of the country, after correction of the data by a selection from 16 independent topographical variables (such as altitude, distance from the sea, slope and topographic roughness), chosen by multiple regression from a digital terrain model (DTM) of the country.

4. The next most accurate method was a pure multiple regression model using the DTM. Both regression and thin plate spline models based on a few variables (latitude, longitude and altitude) only were comparatively unsatisfactory, but some rather simple methods of surface interpolation (such as bilinear interpolation after correction to sea level) gave moderately satisfactory results. Differences between the methods seemed to be dependent largely on their ability to model the effect of the sea on land temperatures.

5. Prediction of temperature by the best methods was greater than 95% accurate in all months of the year, as shown by the correlation between the predicted and actual values. The predicted temperatures were calculated at real altitudes, not subject to sea-level correction.

6. A minimum of just over 30 temperature recording stations would generate a satisfactory surface, provided the stations were well spaced.

7. Maps of mean daily temperature, using the best overall methods are provided; further important variables, such as continentality and length of growing season, were also mapped. Many of these are believed to be the first detailed representations at real altitude.

8. The interpolated monthly temperature surfaces are available on disk.

Compositional data-driven alternatives to single geochemical component maps

Conventional practice in Regional Geochemistry includes as a final step of any geochemical campaign the generation of a series of maps, to show the spatial distribution of each of the components considered. Such maps, though necessary, do not comply with the compositional, relative nature of the data, which unfortunately make any conclusion based on them sensitive
to spurious correlation problems. This is one of the reasons why these maps are never interpreted isolated. This contribution aims at gathering a series of statistical methods to produce individual maps of multiplicative combinations of components (logcontrasts), much in the flavor of equilibrium constants, which are designed on purpose to capture certain aspects of the data.
We distinguish between supervised and unsupervised methods, where the first require an external, non-compositional variable (besides the compositional geochemical information) available in an analogous training set. This external variable can be a quantity (soil density, collocated magnetics, collocated ratio of Th/U spectral gamma counts, proportion of clay particle fraction, etc) or a category (rock type, land use type, etc). In the supervised methods, a regression-like model between the external variable and the geochemical composition is derived in the training set, and then this model is mapped on the whole region. This case is illustrated with the Tellus dataset, covering Northern Ireland at a density of 1 soil sample per 2 square km, where we map the presence of blanket peat and the underlying geology. The unsupervised methods considered include principal components and principal balances
(Pawlowsky-Glahn et al., CoDaWork2013), i.e. logcontrasts of the data that are devised to capture very large variability or else be quasi-constant. Using the Tellus dataset again, it is found that geological features are highlighted by the quasi-constant ratios Hf/Nb and their ratio against SiO2; Rb/K2O and Zr/Na2O and the balance between these two groups of two variables; the balance of Al2O3 and TiO2 vs. MgO; or the balance of Cr, Ni and Co vs. V and Fe2O3. The largest variability appears to be related to the presence/absence of peat.

Regional Knowledge Maps - Potential and Challenges

Regional knowledge map is a tool recently demanded by some actors in an institutional level to help regional policy and innovation in a territory. Besides, knowledge maps facilitate the interaction between the actors of a territory and the collective learning. This paper reports the work in progress of a research project which objective is to define a methodology to efficiently design territorial knowledge maps, by extracting information of big volumes of data contained in diverse sources of information related to a region. Knowledge maps facilitate management of the intellectual capital in organisations. This paper investigates the value to apply this tool to a territorial region to manage the structures, infrastructures and the resources to enable regional innovation and regional development. Their design involves the identification of information sources that are required to find which knowledge is located in a territory, which actors are involved in innovation, and which is the context to develop this innovation (structures, infrastructures, resources and social capital). This paper summarizes the theoretical background and framework for the design of a methodology for the construction of knowledge maps, and gives an overview of the main challenges for the design of regional knowledge maps.

Challenges and Potentials for Keyword Extraction from Company Websites for the Development of Regional Knowledge Maps

Regional Innovation Systems describe the relations between actors, structures and infrastructures in a region in order to stimulate innovation and regional development. For these systems the collection and organization of information is crucial. In the present paper we investigate the possibilities to extract information from websites of companies. First we describe regional innovation systems and the information types that are necessary to create them. Then we discuss the possibilities of text mining and keyword extraction techniques to extract this information from company websites. Finally, we describe a small scale experiment in which keywords related to economic sectors and commodities are extracted from the websites of over 200 companies. This experiment shows what the main challenges are for information extraction from websites for regional innovation systems.

Stevens County GIS Data 2009

UW access only. Questions about spatial data can be directed to uwlib-gis [at] uw [dot] edu, include the URI address below and any information you have.

Thurston County GIS Data 2012

UW access only. Questions about spatial data can be directed to uwlib-gis [at] uw [dot] edu, include the URI address below and any information you have.