Methods to Measure Map Readability

Creation of maps in real-time web services introduces challenges concerning map readability. Therefore we must introduce analytical measures controlling the readability. The aim of this study is to develop and evaluate analytical readability measures with the help of user tests

DEFINITION OF CONTOUR LINES INTERPOLATION OPTIMAL METHODS FOR E-GOVERNMENT SOLUTIONS

Citizens expect high quality and rich e-Government solutions. Map based applications could be significantly improved by utilization of digital elevation models (DEMs). DEMs can be produced using expensive modern remote sensing solutions (e.g., LIDAR). Such data are not available for the wide public. Thus, it is very effective to use contour line maps to derive high-quality DEMs. For many cities around the world, contour line maps available under liberal licenses. Defining an optimal algorithm of contour line interpolation and evaluation of the quality of DEM is an important challenge. In this article, we propose a simple method allowing users to evaluate the quality of DEM produced from a contour line map and define an optimal interpolation algorithm. This method was tested on Turin (Italy) data sets. The results were proved by a visual analysis. The approach is utilized in existing e-Government WebGIS services. This work introduces an information theory-based approach to DEM quality assessment. The results can be utilized in various domains related to DEM quality assurance

Local and global spatio-temporal entropy indices based on distance- ratios and co-occurrences distributions

When it comes to characterize the distribution of ‘things’ observed spatially and identified by their geometries and attributes, the Shannon entropy has been widely used in different domains such as ecology, regional sciences, epidemiology and image analysis. In particular, recent research has taken into account the spatial patterns derived from topological and metric properties in order to propose extensions to the measure of entropy. Based on two different approaches using either distance-ratios or co-occurrences of observed classes, the research developed in this paper introduces several new indices and explores their extensions to the spatio-temporal domains which are derived whilst investigating further their application as global and local indices. Using a multiplicative space-time integration approach either at a macro or micro-level, the approach leads to a series of spatio-temporal entropy indices including from combining co-occurrence and distances-ratios approaches. The framework developed is complementary to the spatio-temporal clustering problem, introducing a more spatial and spatio-temporal structuring perspective using several indices characterizing the distribution of several class instances in space and time. The whole approach is first illustrated on simulated data evolutions of three classes over seven time stamps. Preliminary results are discussed for a study of conflicting maritime activities in the Bay of Brest where the objective is to explore the spatio-temporal patterns exhibited by a categorical variable with six classes, each representing a conflict between two maritime activities

GeoAI-enhanced Techniques to Support Geographical Knowledge Discovery from Big Geospatial Data

abstract: Big data that contain geo-referenced attributes have significantly reformed the way that I process and analyze geospatial data. Compared with the expected benefits received in the data-rich environment, more data have not always contributed to more accurate analysis. “Big but valueless” has becoming a critical concern to the community of GIScience and data-driven geography. As a highly-utilized function of GeoAI technique, deep learning models designed for processing geospatial data integrate powerful computing hardware and deep neural networks into various dimensions of geography to effectively discover the representation of data. However, limitations of these deep learning models have also been reported when People may have to spend much time on preparing training data for implementing a deep learning model. The objective of this dissertation research is to promote state-of-the-art deep learning models in discovering the representation, value and hidden knowledge of GIS and remote sensing data, through three research approaches. The first methodological framework aims to unify varied shadow into limited number of patterns, with the convolutional neural network (CNNs)-powered shape classification, multifarious shadow shapes with a limited number of representative shadow patterns for efficient shadow-based building height estimation. The second research focus integrates semantic analysis into a framework of various state-of-the-art CNNs to support human-level understanding of map content. The final research approach of this dissertation focuses on normalizing geospatial domain knowledge to promote the transferability of a CNN’s model to land-use/land-cover classification. This research reports a method designed to discover detailed land-use/land-cover types that might be challenging for a state-of-the-art CNN’s model that previously performed well on land-cover classification only.Dissertation/ThesisDoctoral Dissertation Geography 201

Visualization of implicit geographic information through map-like graphics

Viele von Web 2.0-Benutzern gesammelte Daten sind ortsbezogen, wobei der Ort meist nur eine Information unter vielen ist und dem Ortsbezug häufig keine besondere Bedeutung zugesprochen wird. Jedoch werden auch mehr und mehr geographische Informationen von Laien gesammelt und im Netz veröffentlicht. Trotz der technischen Möglichkeiten, die im Web-2.0 geboten werden, ist es für Nutzer ohne entsprechendes Expertenwissen meist nicht möglich, gut lesbare und ansprechende Karten zu erzeugen. Dieses Problem besteht, da der Nutzer den darzustellenden Inhalt bestimmt, ohne dass überprüft wird, ob die daraus resultierende Karte den kartographischen Ansprüchen genügt. Des Weiteren hat der Nutzer keinerlei Möglichkeiten, die Standardkartenbilder zu bearbeiten, um beispielsweise für seine Thematik irrelevante Objekte auszublenden oder durch Verdrängung relevante Objekte freizustellen. Besonders bei der Darstellung von POIs treten Überlappungen zwischen Signaturen häufig auf. Trotz des Bedarfs existiert aus verschiedenen Gründen keine etablierte Methode zur Verdrängung von Punktdaten. Daher liegt der Schwerpunkt dieser Arbeit auf der Entwicklung von Verfahren zur Verdrängung von Punktsignaturen. Als Hilfsstrukturen werden dazu Voronoi-Diagramme benutzt und als nutzergenerierte Information werden Sentiments visualisiert. Für den Entwurf der Visualisierungen werden relevante kartographische Bedingungen berücksichtigt und durch zugehörige Qualitätsmaße bewertet. Für die Darstellung von Sentiments werden neben der Verwendung von Punktsignaturen zwei weitere Darstellungsarten erstellt: Anpassung gegebener Signaturen und die Darstellung von Sentiments als Kontinua. Es werden Verdrängungsverfahren für Punktsignaturen entworfen und implementiert. Zur Bestimmung der Verschiebungsrichtung werden zwei verschieden Heuristiken vorgeschlagen und untersucht. Des Weiteren wird eine Möglichkeit zur Steigerung der Effizienz durch Aufteilung der Punktmenge aufgezeigt. Die Bewertung der entworfenen Punktsignaturen erfolgt durch eine Umfrage. Anschließend wird das realisierte Verfahren für gleich große Kreissignaturen in drei Aspekten evaluiert: Grad der Reduzierung der Iterationsschritte durch Zerlegung der Punktmenge, erreichte Verminderung der Überlappungsfläche und Veränderung der relativen Lage der Punkte.A lot of user generated information accumulated in the web is related to a place, with the location usually being just one piece of information among many, which gets no special attention. However, more and more geographic information is collected by laymen and published on the web. Despite the technical possibilities that are offered in Web 2.0, it is usually not possible for users without expert knowledge to produce legible and appealing maps. This problem exists because the user determines the content to be displayed without checking whether the resulting map meets the cartographic requirements. Furthermore, the user has no possibilities to edit the standard map images, for example, hide for his subject irrelevant objects or reducing overlap of relevant objects by displacement. Especially when displaying POIs, overlaps between point symbols often occur. Despite the need, there is no established method for displacing point data for various reasons. Therefore, the focus of this work is the development of methods for the displacement of point signatures. Voronoi diagrams are used as auxiliary structures and sentiment is visualized as user-generated information. For the design of the visualizations relevant cartographic requirements are taken into account and evaluated by quality measures. For the depiction of sentiments, in addition to the use of point symbols, two further types of visualizations are created: adaptation of given map symbols and the representation of sentiments as continua. Displacement techniques for point symbols are designed and implemented. To determine the direction of displacement two different heuristics are proposed and examined. Furthermore, a way to increase the efficiency by dividing the point set is shown. The evaluation of the designed point symbols is done by a survey. Subsequently, the realized method for circular symbols with equal size is evaluated in three aspects: degree of reduction of the iteration steps by decomposition of the point set, achieved reduction of the overlap area and change of the relative position of the points

Adventures in archaeological science: an exploration of oxygen and strontium isotopic variability on a micro- to macro-scale

Isotopic analysis of human remains has become a key scientific technique employed to gather direct evidence of the diet and mobility of past populations. Geographic variation in the isotopic ratios for two elements in particular, oxygen (O) and strontium (Sr), provides a basis for measuring human mobility between regions with differing isotopic signatures. Human tooth enamel acts as a time capsule, locking in the signatures of childhood food and water, so is often the target of isotopic investigations. Understanding the level of variation in these two isotopic systems, O and Sr, is crucial to their use in archaeological mobility and provenancing studies. This thesis focuses on two aspects; micro-scale O isotopic variation in human tooth enamel and macro-scale Sr isotopic variation across islands, quantifying the amount of variation present, and investigating the causes of that variation. Intra-tooth O isotopic variation has been investigated using in situ analysis techniques. Archaeological human tooth samples have been used to provide a baseline value of intra-tooth O variation in a sample comparable with conventional bulk analysis, and to show the implications this variation has for the archaeological narrative. Modern human tooth samples, with known childhood histories, provide an indication of the range of intra-tooth variation seen in stationary and mobile individuals. Strontium isotope analysis of skeletal material requires a baseline of Sr isotopic variability in a region to test for mobility. In this study, robust bioavailable Sr isotope maps (isoscapes) for use in archaeological studies for the islands of Corsica and Grande-Terre, New Caledonia, have been created using soil and plant samples. A test of the Corsican isoscape using samples from the archaeological site of Campu Stefanu shows the applicability of these surfaces in tracing mobility. Underlying data on surface geology, geological age, coastal influences and a spatial assessment have been used to assess the factors driving this isotopic variation. While developing the methodology for this study, isotopic data useful for assessments of mobility at two additional archaeological sites, in France and Guadeloupe, were obtained. By combining O and Sr isotopic analyses of individuals from these sites, mobility was identified and further light shed on their life histories