GeohashTile: Vector Geographic Data Display Method Based on Geohash

© 2020 MDPI AG. All rights reserved. In the development of geographic information-based applications for mobile devices, achieving better access speed and visual effects is the main research aim. In this paper, we propose a new geographic data display method based on Geohash, namely GeohashTile, to improve the performance of traditional geographic data display methods in data indexing, data compression, and the projection of different granularities. First, we use the Geohash encoding system to represent coordinates, as well as to partition and index large-scale geographic data. The data compression and tile encoding is accomplished by Geohash. Second, to realize a direct conversion between Geohash and screen-pixel coordinates, we adopt the relative position projection method. Finally, we improve the calculation and rendering efficiency by using the intermediate result caching method. To evaluate the GeohashTile method, we have implemented the client and the server of the GeohashTile system, which is also evaluated in a real-world environment. The results show that Geohash encoding can accurately represent latitude and longitude coordinates in vector maps, while the GeohashTile framework has obvious advantages when requesting data volume and average load time compared to the state-of-the-art GeoTile system

Augmented reality over maps

Dissertação de mestrado integrado em Engenharia InformáticaMaps and Geographic Information System (GIS) play a major role in modern society, particularly on tourism, navigation and personal guidance. However, providing geographical information of interest related to individual queries remains a strenuous task. The main constraints are (1) the several information scales available, (2) the large amount of information available on each scale, and (3) difficulty in directly infer a meaningful geographical context from text, pictures, or diagrams that are used by most user-aiding systems. To that extent, and to overcome the aforementioned difficulties, we develop a solution which allows the overlap of visual information over the maps being queried — a method commonly referred to as Augmented Reality (AR). With that in mind, the object of this dissertation is the research and implementation of a method for the delivery of visual cartographic information over physical (analogue) and digital two-dimensional (2D) maps utilizing AR. We review existing state-of-art solutions and outline their limitations across different use cases. Afterwards, we provide a generic modular solution for a multitude of real-life applications, to name a few: museums, fairs, expositions, and public street maps. During the development phase, we take into consideration the trade-off between speed and accuracy in order to develop an accurate and real-time solution. Finally, we demonstrate the feasibility of our methods with an application on a real use case based on a map of the city of Oporto, in Portugal.Mapas e Sistema de Informação Geográfica (GIS) desempenham um papel importante na sociedade, particularmente no turismo, navegação e orientação pessoal. No entanto, fornecer informações geográficas de interesse a consultas dos utilizadores é uma tarefa árdua. Os principais dificuldades são (1) as várias escalas de informações disponíveis, (2) a grande quantidade de informação disponível em cada escala e (3) dificuldade em inferir diretamente um contexto geográfico significativo a partir dos textos, figuras ou diagramas usados. Assim, e para superar as dificuldades mencionadas, desenvolvemos uma solução que permite a sobreposição de informações visuais sobre os mapas que estão a ser consultados - um método geralmente conhecido como Realidade Aumentada (AR). Neste sentido, o objetivo desta dissertação é a pesquisa e implementação de um método para a visualização de informações cartográficas sobre mapas 2D físicos (analógicos) e digitais utilizando AR. Em primeiro lugar, analisamos o estado da arte juntamente com as soluções existentes e também as suas limitações nas diversas utilizações possíveis. Posteriormente, fornecemos uma solução modular genérica para uma várias aplicações reais tais como: museus, feiras, exposições e mapas públicos de ruas. Durante a fase de desenvolvimento, tivemos em consideração o compromisso entre velocidade e precisão, a fim de desenvolver uma solução precisa que funciona em tempo real. Por fim, demonstramos a viabilidade de nossos métodos com uma aplicação num caso de uso real baseado num mapa da cidade do Porto (Portugal)

Multiscale visualization approaches for Volunteered Geographic Information and Location-based Social Media

Today, “zoomable” maps are a state-of-the-art way to explore the world, available to anyone with Internet access. However, the process of creating this visualization has been rather loosely investigated and documented. Nevertheless, with an increasing amount of available data, interactive maps have become a more integral approach to visualizing and exploring big datasets and user-generated data. OpenStreetMap and online platforms such as Twitter and Flickr offer application programming interfaces (APIs) with geographic information. They are well-known examples of this visualization challenge and are often used as examples. In addition, an increasing number of public administrations collect open data and publish their data sets, which makes the task of visualization even more relevant. This dissertation deals with the visualization of user-generated geodata as a multiscale map. The basics of today’s multiscale maps—their history, technologies, and possibilities—are explored and abstracted. This work introduces two new multiscale-focused visualization approaches for point data from volunteered geographic information (VGI) and location-based social media (LBSM). One contribution of this effort is a visualization methodology for spatially referenced information in the form of point geometries, using nominally scaled data from social media such as Twitter or Flickr. Typical for this data is a high number of social media posts in different categories—a post on social media corresponds to a point in a specific category. Due to the sheer quantity and similar characteristics, the posts appear generic rather than unique. This type of dataset can be explored using the new method of micro diagrams to visualize the dataset on multiple scales and resolutions. The data is aggregated into small grid cells, and the numerical proportion is shown with small diagrams, which can visually merge into heterogenous areas through colors depicting a specific category. The diagram sizes allow the user to estimate the overall number of aggregated points in a grid cell. A different visualization approach is proposed for more unique points, considered points of interest (POI), based on the selection method. The goal is to identify more locally relevant points from the data set, considered more important compared to other points in the neighborhood, which are then compared by numerical attribute. The method, derived from topographic isolation and called discrete isolation, is the distance from one point to the next with a higher attribute value. By using this measure, the most essential points can be easily selected by choosing a minimum distance and producing a homogenous spatial of the selected points within the chosen dataset. The two newly developed approaches are applied to multiscale mapping by constructing example workflows that produce multiscale maps. The publicly available multiscale mapping workflows OpenMapTiles and OpenStreetMap Carto, using OpenStreetMap data, are systematically explored and analyzed. The result is a general workflow for multiscale map production and a short overview of the toolchain software. In particular, the generalization approaches in the example projects are discussed and these are classified into cartographic theories on the basis of literature. The workflow is demonstrated by building a raster tile service for the micro diagrams and a vector tile service for the discrete isolation, able to be used with just a web browser. In conclusion, these new approaches for point data using VGI and LBSM allow better qualitative visualization of geodata. While analyzing vast global datasets is challenging, exploring and analyzing hidden data patterns is fruitful. Creating this degree of visualization and producing maps on multiple scales is a complicated task. The workflows and tools provided in this thesis will make map production on a worldwide scale easier.:1 Introduction 1 1.1 Motivation .................................................................................................. 3 1.2 Visualization of crowdsourced geodata on multiple scales ............ 5 1.2.1 Research objective 1: Visualization of point collections ......... 6 1.2.2 Research objective 2: Visualization of points of interest ......... 7 1.2.3 Research objective 3: Production of multiscale maps ............. 7 1.3 Reader’s guide ......................................................................................... 9 1.3.1 Structure ........................................................................................... 9 1.3.2 Related Publications ....................................................................... 9 1.3.3 Formatting and layout ................................................................. 10 1.3.4 Online examples ........................................................................... 10 2 Foundations of crowdsourced mapping on multiple scales 11 2.1 Types and properties of crowdsourced data .................................. 11 2.2 Currents trends in cartography ......................................................... 11 2.3 Definitions .............................................................................................. 12 2.3.1 VGI .................................................................................................. 12 2.3.2 LBSM .............................................................................................. 13 2.3.3 Space, place, and location......................................................... 13 2.4 Visualization approaches for crowdsourced geodata ................... 14 2.4.1 Review of publications and visualization approaches ........... 14 2.4.2 Conclusions from the review ...................................................... 15 2.4.3 Challenges mapping crowdsourced data ................................ 17 2.5 Technologies for serving multiscale maps ...................................... 17 2.5.1 Research about multiscale maps .............................................. 17 2.5.2 Web Mercator projection ............................................................ 18 2.5.3 Tiles and zoom levels .................................................................. 19 2.5.4 Raster tiles ..................................................................................... 21 2.5.5 Vector tiles .................................................................................... 23 2.5.6 Tiling as a principle ..................................................................... 25 3 Point collection visualization with categorized attributes 26 3.1 Target users and possible tasks ....................................................... 26 3.2 Example data ......................................................................................... 27 3.3 Visualization approaches .................................................................... 28 3.3.1 Common techniques .................................................................... 28 3.3.2 The micro diagram approach .................................................... 30 3.4 The micro diagram and its parameters ............................................ 33 3.4.1 Aggregating points into a regular structure ............................ 33 3.4.2 Visualizing the number of data points ...................................... 35 3.4.3 Grid and micro diagrams ............................................................ 36 3.4.4 Visualizing numerical proportions with diagrams .................. 37 3.4.5 Influence of color and color brightness ................................... 38 3.4.6 Interaction options with micro diagrams .................................. 39 3.5 Application and user-based evaluation ............................................ 39 3.5.1 Micro diagrams in a multiscale environment ........................... 39 3.5.2 The micro diagram user study ................................................... 41 3.5.3 Point collection visualization discussion .................................. 47 4 Selection of POIs for visualization 50 4.1 Approaches for point selection .......................................................... 50 4.2 Methods for point selection ................................................................ 51 4.2.1 Label grid approach .................................................................... 52 4.2.2 Functional importance approach .............................................. 53 4.2.3 Discrete isolation approach ....................................................... 54 4.3 Functional evaluation of selection methods .................................... 56 4.3.1 Runtime comparison .................................................................... 56 4.3.2 Use cases for discrete isolation ................................................ 57 4.4 Discussion of the selection approaches .......................................... 61 4.4.1 A critical view of the use cases ................................................. 61 4.4.2 Comparing the approaches ........................................................ 62 4.4.3 Conclusion ..................................................................................... 64 5 Creating multiscale maps 65 5.1 Examples of multiscale map production .......................................... 65 5.1.1 OpenStreetMap Infrastructure ................................................... 66 5.1.2 OpenStreetMap Carto ................................................................. 67 5.1.3 OpenMapTiles ............................................................................... 73 5.2 Methods of multiscale map production ............................................ 80 5.2.1 OpenStreetMap tools ................................................................... 80 5.2.2 Geoprocessing .............................................................................. 80 5.2.3 Database ........................................................................................ 80 5.2.4 Creating tiles ................................................................................. 82 5.2.5 Caching .......................................................................................... 82 5.2.6 Styling tiles .................................................................................... 82 5.2.7 Viewing tiles ................................................................................... 83 5.2.8 The stackless approach to tile creation ................................... 83 5.3 Example workflows for creating multiscale maps ........................... 84 5.3.1 Raster tiles: OGC services and micro diagrams .................... 84 5.3.2 Vector tiles: Slippy map and vector tiles ................................. 87 5.4 Discussion of approaches and workflows ....................................... 90 5.4.1 Map production as a rendering pipeline .................................. 90 5.4.2 Comparison of OpenStreetMap Carto and OpenMapTiles .. 92 5.4.3 Discussion of the implementations ........................................... 93 5.4.4 Generalization in map production workflows .......................... 95 5.4.5 Conclusions ................................................................................. 101 6 Discussion 103 6.1 Development for web mapping ........................................................ 103 6.1.1 The role of standards in map production .............................. 103 6.1.2 Technological development ..................................................... 103 6.2 New data, new mapping techniques? ............................................. 104 7 Conclusion 106 7.1 Visualization of point collections ..................................................... 106 7.2 Visualization of points of interest ................................................... 107 7.3 Production of multiscale maps ........................................................ 107 7.4 Synthesis of the research questions .............................................. 108 7.5 Contributions ....................................................................................... 109 7.6 Limitations ............................................................................................ 110 7.7 Outlook ................................................................................................. 111 8 References 113 9 Appendix 130 9.1 Zoom levels and Scale ...................................................................... 130 9.3 Full information about selected UGC papers ................................ 131 9.4 Timeline of mapping technologies .................................................. 133 9.5 Timeline of map providers ................................................................ 133 9.6 Code snippets from own map production workflows .................. 134 9.6.1 Vector tiles workflow ................................................................. 134 9.6.2 Raster tiles workflow.................................................................. 137Heute sind zoombare Karten Alltag für jeden Internetznutzer. Die Erstellung interaktiv zoombarer Karten ist allerdings wenig erforscht, was einen deutlichen Gegensatz zu ihrer aktuellen Bedeutung und Nutzungshäufigkeit darstellt. Die Forschung in diesem Bereich ist also umso notwendiger. Steigende Datenmengen und größere Regionen, die von Karten abgedeckt werden sollen, unterstreichen den Forschungsbedarf umso mehr. Beispiele für stetig wachsende Datenmengen sind Geodatenquellen wie OpenStreetMap aber auch freie amtliche Geodatensätze (OpenData), aber auch die zunehmende Zahl georeferenzierter Inhalte auf Internetplatformen wie Twitter oder Flickr zu nennen. Das Thema dieser Arbeit ist die Visualisierung eben dieser nutzergenerierten Geodaten mittels zoombarer Karten. Dafür wird die Entwicklung der zugrundeliegenden Technologien über die letzten zwei Jahr-zehnte und die damit verbundene Möglichkeiten vorgestellt. Weitere Beiträge sind zwei neue Visualisierungsmethoden, die sich besonders für die Darstellung von Punktdaten aus raumbezogenen nutzergenerierten Daten und georeferenzierte Daten aus Sozialen Netzwerken eignen. Ein Beitrag dieser Arbeit ist eine neue Visualisierungsmethode für raumbezogene Informationen in Form von Punktgeometrien mit nominal skalierten Daten aus Sozialen Medien, wie beispielsweise Twitter oder Flickr. Typisch für diese Daten ist eine hohe Anzahl von Beiträgen mit unterschiedlichen Kategorien. Wobei die Beiträge, bedingt durch ihre schiere Menge und ähnlicher Ei-genschaften, eher generisch als einzigartig sind. Ein Beitrag in den So-zia len Medien entspricht dabei einem Punkt mit einer bestimmten Katego-rie. Ein solcher Datensatz kann mit der neuen Methode der „micro diagrams“ in verschiedenen Maßstäben und Auflösungen visualisiert und analysiert werden. Dazu werden die Daten in kleine Gitterzellen aggregiert. Die Menge und Verteilung der über die Kategorien aggregierten Punkte wird durch kleine Diagramme dargestellt, wobei die Farben die verschiedenen Kategorien visualisieren. Durch die geringere Größe der einzelnen Diagramme verschmelzen die kleinen Diagramme visuell, je nach der Verteilung der Farben für die Kategorien. Bei genauerem Hinsehen ist die Schätzung der Menge der aggregierten Punkte über die Größe der Diagramme die Menge und die Verteilung über die Kategorien möglich. Für einzigartigere Punkte, die als Points of Interest (POI) angesehen werden, wird ein anderer Visualisierungsansatz vorgeschlagen, der auf einer Auswahlmethode basiert. Ziel ist es dabei lokal relevantere Punkte aus dem Datensatz zu identifizieren, die im Vergleich zu anderen Punkten in der Nachbarschaft des Punktes verglichen nach einem numerischen Attribut wichtiger sind. Die Methode ist von dem geographischen Prinzip der Dominanz von Bergen abgeleitet und wird „discrete isolation“ genannt. Es handelt sich dabei um die Distanz von einem Punkt zum nächsten mit einem höheren Attributwert. Durch die Verwendung dieses Maßes können lokal bedeutende Punkte leicht ausgewählt werden, indem ein minimaler Abstand gewählt und so räumlich gleichmäßig verteilte Punkte aus dem Datensatz ausgewählt werden. Die beiden neu vorgestellten Methoden werden in den Kontext der zoombaren Karten gestellt, indem exemplarische Arbeitsabläufe erstellt werden, die als Er-gebnis eine zoombare Karte liefern. Dazu werden die frei verfügbaren Beispiele zur Herstellung von weltweiten zoombaren Karten mit nutzergenerierten Geo-daten von OpenStreetMap, anhand der Kartenprojekte OpenMapTiles und O-penStreetMap Carto analysiert und in Arbeitsschritte gegliedert. Das Ergebnis ist ein wiederverwendbarer Arbeitsablauf zur Herstellung zoombarer Karten, ergänzt durch eine Auswahl von passender Software für die einzelnen Arbeits-schritte. Dabei wird insbesondere auf die Generalisierungsansätze in den Beispielprojekten eingegangen und diese anhand von Literatur in die kartographische Theorie eingeordnet. Zur Demonstration des Workflows wird je ein Raster Tiles Dienst für die „micro diagrams“ und ein Vektor Tiles Dienst für die „discrete isolation“ erstellt. Beide Dienste lassen sich mit einem aktuellen Webbrowser nutzen. Zusammenfassend ermöglichen diese neuen Visualisierungsansätze für Punkt-daten aus VGI und LBSM eine bessere qualitative Visualisierung der neuen Geodaten. Die Analyse riesiger globaler Datensätze ist immer noch eine Herausforderung, aber die Erforschung und Analyse verborgener Muster in den Daten ist lohnend. Die Erstellung solcher Visualisierungen und die Produktion von Karten in verschiedenen Maßstäben ist eine komplexe Aufgabe. Die in dieser Arbeit vorgestellten Arbeitsabläufe und Werkzeuge erleichtern die Erstellung von Karten in globalem Maßstab.:1 Introduction 1 1.1 Motivation .................................................................................................. 3 1.2 Visualization of crowdsourced geodata on multiple scales ............ 5 1.2.1 Research objective 1: Visualization of point collections ......... 6 1.2.2 Research objective 2: Visualization of points of interest ......... 7 1.2.3 Research objective 3: Production of multiscale maps ............. 7 1.3 Reader’s guide ......................................................................................... 9 1.3.1 Structure ........................................................................................... 9 1.3.2 Related Publications ....................................................................... 9 1.3.3 Formatting and layout ................................................................. 10 1.3.4 Online examples ........................................................................... 10 2 Foundations of crowdsourced mapping on multiple scales 11 2.1 Types and properties of crowdsourced data .................................. 11 2.2 Currents trends in cartography ......................................................... 11 2.3 Definitions .............................................................................................. 12 2.3.1 VGI .................................................................................................. 12 2.3.2 LBSM .............................................................................................. 13 2.3.3 Space, place, and location......................................................... 13 2.4 Visualization approaches for crowdsourced geodata ................... 14 2.4.1 Review of publications and visualization approaches ........... 14 2.4.2 Conclusions from the review ...................................................... 15 2.4.3 Challenges mapping crowdsourced data ................................ 17 2.5 Technologies for serving multiscale maps ...................................... 17 2.5.1 Research about multiscale maps .............................................. 17 2.5.2 Web Mercator projection ............................................................ 18 2.5.3 Tiles and zoom levels .................................................................. 19 2.5.4 Raster tiles ..................................................................................... 21 2.5.5 Vector tiles .................................................................................... 23 2.5.6 Tiling as a principle ..................................................................... 25 3 Point collection visualization with categorized attributes 26 3.1 Target users and possible tasks ....................................................... 26 3.2 Example data ......................................................................................... 27 3.3 Visualization approaches .................................................................... 28 3.3.1 Common techniques .................................................................... 28 3.3.2 The micro diagram approach .................................................... 30 3.4 The micro diagram and its parameters ............................................ 33 3.4.1 Aggregating points into a regular structure ............................ 33 3.4.2 Visualizing the number of data points ...................................... 35 3.4.3 Grid and micro diagrams ............................................................ 36 3.4.4 Visualizing numerical proportions with diagrams .................. 37 3.4.5 Influence of color and color brightness ................................... 38 3.4.6 Interaction options with micro diagrams .................................. 39 3.5 Application and user-based evaluation ............................................ 39 3.5.1 Micro diagrams in a multiscale environment ........................... 39 3.5.2 The micro diagram user study ................................................... 41 3.5.3 Point collection vis

Quantifying terrain factor using GIS applications for real estate property valuation

This thesis studies the use of GIS applications to derive adjustment figures for the terrain factor in property valuation tasks. It aims at suggesting a quantitative approach alternative to evaluate the terrain factor as opposed to traditional methods and current industry practices where terrain is qualitatively judged based on visual observation at site and subjected to individual opinion. In this study, the terrain factor is considered by analysing the slope and surface roughness elements of terrain. To achieve this, slope and surface roughness values are generated from available open source digital elevation models (DEMs) within the Esri ArcGIS software environment. For the purposes of this study, the Shuttle Radar Topography Mission (SRTM) DEM developed by National Geospatial-Intelligence Agency (NGA) and United States National Aeronautics and Space Administration (NASA), as well as the Advance Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global DEM jointly developed by Ministry of Economy, Trade and Industry, Japan (METI) and NASA, were used to derive terrain values. The output adjustments were tested on several hypothetical valuation cases, consisting of small and large properties, to see the effects of DEM resolution upon the results. In order to test the accuracy of the proposed-adjustment outputs and applicability of the study methods, feedbacks from industry experts were collected via an online survey for analysis. Upon analysing the feedbacks, this study finds that industry experts are of the opinion that the terrain adjustments proposed by this method are reasonable for use in the industry practice, although some apprehensions were also noted, as property valuers tend to exercise caution when using automated valuation methods. The proposed method is simple to apply and does not require advanced knowledge of GIS functions to operate. Therefore, considering the positive feedback from the valuation community, it could pave way towards future incorporation of geostatistical methods/ components in value analysis.Tesis ini mengkaji kegunaan aplikasi GIS untuk mendapatkan pekali pelarasan bagi faktor rupabumi dalam kerja-kerja penilaian. Maksud kajian adalah untuk mencadangkan pendekatan kuantitatif bagi mempertimbangkan faktor rupabumi sebagai alternatif kepada kaedah tradisional dan amalan semasa industri yang bersifat kualitatif, yang mana faktor rupabumi diputuskan berdasarkan pemerhatian visual di tapak dan tertakluk kepada pendapat peribadi. Dalam kajian ini, faktor rupabumi dipertimbangkan melalui analisis ke atas elemen kecerunan dan kekasaran permukaan rupabumi. Nilai kecerunan dan kekasaran rupabumi dijana daripada model aras digital (DEM) yang diperolehi daripada sumber terbuka (open source) menggunakan pakej perisian Esri ArcGIS. Untuk tujuan kajian ini, nilai elemen cerun diperolehi dari DEM Shuttle Radar Topography Mission (SRTM) yang dibangunkan oleh National Geospatial-Intelligence Agency (NGA) dan United States National Aeronautics and Space Administration (NASA) serta DEM Advance Spaceborne Thermal Emission and Reflection Radiometer (ASTER) yang dibangunkan melalui usahasama Kementerian Ekonomi, Perdagangan dan Industri, Jepun (METI) dan NASA. Cadangan pelarasan yang dijana (output) daripada kajian ini diuji dalam beberapa kes penilaian andaian (hypothetical) yang terdiri daripada harta tanah bersaiz kecil dan besar, bagi mengkaji kesan perincian resolusi DEM ke atas penilaian. Bagi menguji ketepatan output pelarasan yang disyorkan dan kesesuaian aplikasi syor pelarasan oleh kaedah-kaedah kajian, maklum balas daripada pakar-pakar industri dikumpul melalui soal-selidik atas talian (online) untuk dianalisis. Berdasarkan maklum balas soal-selidik, pakar-pakar industri pada umumnya berpandangan kadar pelarasan faktor rupabumi yang disyorkan oleh kaedah-kaedah kajian ini adalah munasabah untuk digunakan walaupun beberapa keraguan turut dikesan, tetapi ini adalah kerana penilai berjaga-jaga dengan nilaian janaan komputer. Kaedah yang dicadangkan oleh kajian ini adalah mudah untuk diaplikasi dan tidak memerlukan pengetahuan yang mendalam tentang GIS untuk digunapakai. Oleh itu, memandangkan maklum balas yang diterima daripada komuniti penilai adalah positif, kaedah kajian mungkin dapat membuka langkah bagi memasukkan (include) komponen analisis geostatistik dalam analisis nilai di masa hadapan.The comparison method of valuation is based on the basic principal that properties that are close to one another in location and most similar to each other in feature would logically be similar in value. Using this method, the value of a subject property at a specific time and for a specific purpose is determined by gathering comparable sale evidences at the stated date of transaction, whereby the transacted amount of the comparable is adjusted to account for factors of dissimilarity between the comparable and the subject. While some factors (e.g.: size) is numerical in nature and thus may be analysed quantitatively, in current practice, many other factors are being analysed qualitatively based on observation and personal opinion. Although this qualitative way of analysing property factors is widely accepted within the valuation community, such approach allows for a wide area for interpretation as it is difficult to put a scale on personal views and opinions. Studies in spatial statistics have contributed towards the development of GIS applications that is able to deal with spatial data in a quantitative manner. In relation to that, this project attempts to use GIS application to analyse a selected adjustment factor to be incorporated into the valuation practice. This project will propose adjustment values for the surface terrain factor, by generating slope and surface roughness values from free Digital Elevation Models (DEMs). These values are then linked to the corresponding property unit to obtain the average terrain value per property. The terrain value of the comparable property unit is then compared to the terrain value of the subject property and the difference is analysed to suggest a reasonable adjustment value for the comparable. The adjustment outputs derived from the study methods are tested by gathering feedback from property experts via an online survey based on several hypothetical valuation cases. Response from the survey notes that most respondents find the derived adjustment outputs as reasonable for application in industry, although there are some inconsistencies noted in the survey results, likely due to the small sample size used in the project, as well as due to the coarse resolution of the DEMs used. It should be noted that the methods proposed in this project is simple to use and does not require advance knowledge in GIS to operate. In fact, it should be said that this method may readily be used, especially in the event of available high quality elevation data

Human Machine Interaction

In this book, the reader will find a set of papers divided into two sections. The first section presents different proposals focused on the human-machine interaction development process. The second section is devoted to different aspects of interaction, with a special emphasis on the physical interaction

Pathways to spatial cognition : a multi-domain approach SpatialTrain I

“Opening a window into the future is not an easy task. Attempting to open one in a generation after the initial launching step might seemed either idealistic, naïve or with hindsight plain driven” (Formosa, 2017, p35). The drive to introduce Spatial Information integration across the Maltese Islands was an ideal, one that brought in technology, methodologies and results. However, as in the classic GIS evolution through the decades pointers on what constitutes a spatial information system were the subject of extensive debate Initially this was driven by the Push – Pull factor where entities using the primitive systems were being pushed by the availability of a mapping system and provision of base maps and hence creating data to fit the system. Initiated in the 1960s through military use, porting the processes to the physical and urban domains in the 1980s and 1990s, further takeup was made in the environmental domains in the 1990s to 2000s and eventually to the social domain in the 2000 to 2010s. Jumping through the decades, the global explosion of GIS and Spatial awareness as well as software, methods and integrative constructs morphed GIS into an availability that made it all possible, particularly through online and web-enabled GIS. This Pull – Push factor caused entities and private organisations to finally break through by creating their own data and then going for the mapping systems that fit their needs, systems that have evolved beyond recognition, both in the proprietary and open-source/open-access arenas. [Excerpt from the Introduction by Prof. Saviour Formosa]peer-reviewe

Insights into Rockfall from Constant 4D Monitoring

Current understanding of the nature of rockfall and their controls stems from the capabilities of slope monitoring. These capabilities are fundamentally limited by the frequency and resolution of data that can be captured. Various assumptions have therefore arisen, including that the mechanisms that underlie rockfall are instantaneous. Clustering of rockfall across rock faces and sequencing through time have been observed, sometimes with an increase in pre-failure deformation and pre-failure rockfall activity prior to catastrophic failure. An inherent uncertainty, however, lies in whether the behaviour of rockfall monitored over much shorter time intervals (Tint) is consistent with that previously monitored at monthly intervals, including observed failure mechanisms, their response to external drivers, and pre-failure deformation. To address the limitations of previous studies on this topic, 8 987 terrestrial laser scans have been acquired over 10 months from continuous near-real time monitoring of an actively failing coastal rock slope (Tint = 0.5 h). A workflow has been devised that automatically resolves depth changes at the surface to 0.03 m. This workflow filters points with high positional uncertainty and detects change in 3D, with both approaches tailored to natural rock faces, which commonly feature sharp edges and partially occluded areas. Analysis of the resulting rockfall inventory, which includes > 180 000 detachments, shows that the proportion of rockfall < 0.1 m3 increases with more frequent surveys for Tint < ca. 100 h, but this trend does not continue for surface comparison over longer time intervals. Therefore, and advantageously, less frequent surveys will derive the same rockfall magnitude-frequency distribution if captured at ca. 100 h intervals as compared to one month or even longer intervals. The shape and size of detachments shows that they are more shallow and smaller than observable rock mass structure, but appear to be limited in size and extent by jointing. Previously explored relationships between rockfall timing and environmental and marine conditions do not appear to apply to this inventory, however, significant relationships between rockfall and rainfall, temperature gradient and tides are demonstrated over short timescales. Pre-failure deformation and rockfall activity is observed in the footprint of incipient rockfall. Rockfall activity occurs predominantly within the same ca. 100 h timescale observed in the size-distribution analysis, and accelerated deformation is common for the largest rockfall during the final 2 h before block detachment. This study provides insights into the nature and development of rockfall during the period prior to detachment, and the controls upon it. This holds considerable implications for our understanding of rockfall and the improvement of future rockfall monitoring