Application of Geographic Information Systems

The importance of Geographic Information Systems (GIS) can hardly be overemphasized in today’s academic and professional arena. More professionals and academics have been using GIS than ever – urban & regional planners, civil engineers, geographers, spatial economists, sociologists, environmental scientists, criminal justice professionals, political scientists, and alike. As such, it is extremely important to understand the theories and applications of GIS in our teaching, professional work, and research. “The Application of Geographic Information Systems” presents research findings that explain GIS’s applications in different subfields of social sciences. With several case studies conducted in different parts of the world, the book blends together the theories of GIS and their practical implementations in different conditions. It deals with GIS’s application in the broad spectrum of geospatial analysis and modeling, water resources analysis, land use analysis, infrastructure network analysis like transportation and water distribution network, and such. The book is expected to be a useful source of knowledge to the users of GIS who envision its applications in their teaching and research. This easy-to-understand book is surely not the end in itself but a little contribution to toward our understanding of the rich and wonderful subject of GIS

Regular Hierarchical Surface Models: A conceptual model of scale variation in a GIS and its application to hydrological geomorphometry

Environmental and geographical process models inevitably involve parameters that vary spatially. One example is hydrological modelling, where parameters derived from the shape of the ground such as flow direction and flow accumulation are used to describe the spatial complexity of drainage networks. One way of handling such parameters is by using a Digital Elevation Model (DEM), such modelling is the basis of the science of geomorphometry. A frequently ignored but inescapable challenge when modellers work with DEMs is the effect of scale and geometry on the model outputs. Many parameters vary with scale as much as they vary with position. Modelling variability with scale is necessary to simplify and generalise surfaces, and desirable to accurately reconcile model components that are measured at different scales. This thesis develops a surface model that is optimised to represent scale in environmental models. A Regular Hierarchical Surface Model (RHSM) is developed that employs a regular tessellation of space and scale that forms a self-similar regular hierarchy, and incorporates Level Of Detail (LOD) ideas from computer graphics. Following convention from systems science, the proposed model is described in its conceptual, mathematical, and computational forms. The RHSM development was informed by a categorisation of Geographical Information Science (GISc) surfaces within a cohesive framework of geometry, structure, interpolation, and data model. The positioning of the RHSM within this broader framework made it easier to adapt algorithms designed for other surface models to conform to the new model. The RHSM has an implicit data model that utilises a variation of Middleton and Sivaswamy (2001)’s intrinsically hierarchical Hexagonal Image Processing referencing system, which is here generalised for rectangular and triangular geometries. The RHSM provides a simple framework to form a pyramid of coarser values in a process characterised as a scaling function. In addition, variable density realisations of the hierarchical representation can be generated by defining an error value and decision rule to select the coarsest appropriate scale for a given region to satisfy the modeller’s intentions. The RHSM is assessed using adaptions of the geomorphometric algorithms flow direction and flow accumulation. The effects of scale and geometry on the anistropy and accuracy of model results are analysed on dispersive and concentrative cones, and Light Detection And Ranging (LiDAR) derived surfaces of the urban area of Dunedin, New Zealand. The RHSM modelling process revealed aspects of the algorithms not obvious within a single geometry, such as, the influence of node geometry on flow direction results, and a conceptual weakness of flow accumulation algorithms on dispersive surfaces that causes asymmetrical results. In addition, comparison of algorithm behaviour between geometries undermined the hypothesis that variance of cell cross section with direction is important for conversion of cell accumulations to point values. The ability to analyse algorithms for scale and geometry and adapt algorithms within a cohesive conceptual framework offers deeper insight into algorithm behaviour than previously achieved. The deconstruction of algorithms into geometry neutral forms and the application of scaling functions are important contributions to the understanding of spatial parameters within GISc

Modeling of realistic microstructures on the basis of quantitative mineralogical analyses

Diese Forschung zielt darauf ab, den Einsatz realistischer Mineralmikrostrukturen in Mineralverarbeitungssimulationen Simulationen von Aufbereitungsprozessen zu ermöglichen. Insbesondere Zerkleinerungsprozesse, wie z.B. das Brechen und Mahlen von mineralischen Rohmaterialien, werden stark von der mineralischen Mikrostruktur beeinflusst, da die Textur und die Struktur der vielen Körner und ihre mikromechanischen Eigenschaften das makroskopische Bruchverhalten bestimmen. Ein Beispiel: Stellen wir uns vor, wir haben ein mineralisches Material, das im Wesentlichen aus Körnern zweier verschiedener Mineralphasen, wie Quarz und Feldspat, besteht. Wenn die mikromechanischen Eigenschaften dieser beiden Phasen unterschiedlich sind, wird sich dies wahrscheinlich auf das makroskopische Bruchverhalten auswirken. Unter der Annahme, dass die Körner eines der Minerale bei geringeren Belastungen brechen, ist es wahrscheinlich, dass sich ein Riss durch einen Stein dieses Materials durch die schwächeren Körner ausbreitet. Tatsächlich ist dies eine wichtige Eigenschaft für die Erzaufbereitung. Um wertvolle Mineralien aus einem Erz zu gewinnen, ist es wichtig, sie aus dem kommerziell wertlosen Material, in dem sie vorkommen, zu befreien. Dazu ist es wichtig zu wissen und zu verstehen, wie das Material auf Korngrößenebene bricht. Um diesen Bruch simulieren zu können, ist es wichtig, realistische Modelle der mineralischen Mikrostrukturen zu verwenden. Diese Studie zeigt, wie solche realistischen zweidimensionalen Mikrostrukturen auf der Grundlage der quantitativen Mikrostrukturanalyse am Computer erzeugt werden können. Darüber hinaus zeigt die Studie, wie diese synthetischen Mikrostrukturen dann in die gut etablierte Diskrete-Elemente-Methode integriert werden können, bei der der Bruch von mineralischem Material auf Korngrößenebene simuliert werden kann.:List of Acronyms VII List of Latin Symbols IX List of Greek Symbols XV 1 Introduction 1 1.1 Motivation for using realistic microstructures in Discrete Element Method (DEM) 1 1.2 Possibilities for using realistic mineral microstructures in DEM simulations . 4 1.3 Objective and disposition of the thesis . . . . . . . . . . . . . . . . . . . . 7 2 Background 9 2.1 Discrete Element Method (DEM) . . . . . . . . . . . . . . . . . . . . . . . . 9 2.1.1 Fundamentals of the Discrete Element Method (DEM) . . . . . . . . 9 2.1.2 Applications of DEM in comminution science . . . . . . . . . . . . . 21 2.1.3 Limitations of DEM in comminution science . . . . . . . . . . . . . . 26 2.2 Quantitative Microstructural Analysis . . . . . . . . . . . . . . . . . . . . . 29 2.2.1 Fundamentals of the Quantitative Microstructural Analysis . . . . . . 29 2.2.2 Applied QMA in mineral processing . . . . . . . . . . . . . . . . . . 49 2.2.3 Applicability of the QMA for the synthesis of realistic microstructures 49 3 Synthesis of realistic mineral microstructures for DEM simulations 51 3.1 Development of a computer-assisted QMA for the analysis of real and synthetic mineral microstructures . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 3.1.1 Fundamentals of the computer-assisted QMA . . . . . . . . . . . . 53 3.1.2 The requirements for the false-color image. . . . . . . . . . . . . . 54 3.1.3 The conversion of a given real mineral microstructure into a false-color image . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 3.1.4 Implementation of the point, line, and area analysis . . . . . . . . . 59 3.1.5 Selection of appropriate QMA parameters for analyzing two-dimensional microstructures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 3.1.6 Summary of the principles of the adapted Quantitative Microstructural Analysis (QMA) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 3.2 Analysis of possible strategies for the microstructure synthesis . . . . . . . . 71 3.3 Implementation of the drawing method . . . . . . . . . . . . . . . . . . . . 76 3.3.1 Drawing of a single grain . . . . . . . . . . . . . . . . . . . . . . . 77 XVIII List of Greek Symbols 3.3.2 Drawing of multiple grains, which form a synthetic microstructure . . 81 3.3.3 Synthesizing mineral microstructures consisting of multiple phases . 85 3.4 The final program for microstructure analysis and synthesis . . . . . . . . . 89 3.4.1 Synthesis and analysis of an example microstructure . . . . . . . . . 90 3.4.2 Procedure for generating a realistic synthetic microstructure of a given real microstructure . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 4 Validation of the synthesis approach 103 4.1 Methodical considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 4.1.1 The basic idea of the validation procedure . . . . . . . . . . . . . . 103 4.1.2 The experimental realizations . . . . . . . . . . . . . . . . . . . . . 108 4.2 Basic indenter test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 4.2.1 Considerations for the basic indenter test . . . . . . . . . . . . . . . 109 4.2.2 Realization and evaluation of the real basic indenter test . . . . . . . 114 4.2.3 Realization and evaluation of the simulated basic indenter test . . . 127 4.2.4 Conclusions on the basic indenter test . . . . . . . . . . . . . . . . . 138 4.3 Extended indenter test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139 4.3.1 Basic considerations for the extended indenter test . . . . . . . . . . 139 4.3.2 Realization and evaluation of the real extended indenter test . . . . 142 4.3.3 Realization and evaluation of the simulated extended indenter test . 154 4.3.4 Conclusions on the extended indenter test . . . . . . . . . . . . . . 171 4.4 Particle bed test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172 4.4.1 Basic considerations for the particle bed test . . . . . . . . . . . . . 173 4.4.2 Realization and evaluation of the real particle bed test . . . . . . . . 176 4.4.3 Realization and evaluation of the simulated particle bed test . . . . . 188 4.4.4 Conclusions on the particle bed test . . . . . . . . . . . . . . . . . . 203 5 Conclusions and directions for future development 205 6 References 211 List of Figures 229 List of Tables 235 Appendix 237This research aims to make it possible to use realistic mineral microstructures in simulations of mineral processing. In particular, comminution processes, such as the crushing and grinding of raw mineral materials, are highly aff ected by the mineral microstructure, since the texture and structure of the many grains and their micromechanical properties determine the macroscopic fracture behavior. To illustrate this, consider a mineral material that essentially consists of grains of two diff erent mineral phases, such as quartz and feldspar. If the micromechanical properties of these two phases are diff erent, this will likely have an impact on the macroscopic fracture behavior. Assuming that the grains of one of the minerals break at lower loads, it is likely that a crack through a stone of that material will spread through the weaker grains. In fact, this is an important property for ore processing. In order to extract valuable minerals from an ore, it is important to liberate them from the commercially worthless material in which they are found. For this, it is essential to know and understand how the material breaks at grain-size level. To be able to simulate this breakage, it is important to use realistic models of the mineral microstructures. This study demonstrates how such realistic two-dimensional microstructures can be generated on the computer based on quantitative microstructural analysis. Furthermore, the study shows how these synthetic microstructures can then be incorporated into the well-established discrete element method, where the breakage of mineral material can be simulated at grain-size level.:List of Acronyms VII List of Latin Symbols IX List of Greek Symbols XV 1 Introduction 1 1.1 Motivation for using realistic microstructures in Discrete Element Method (DEM) 1 1.2 Possibilities for using realistic mineral microstructures in DEM simulations . 4 1.3 Objective and disposition of the thesis . . . . . . . . . . . . . . . . . . . . 7 2 Background 9 2.1 Discrete Element Method (DEM) . . . . . . . . . . . . . . . . . . . . . . . . 9 2.1.1 Fundamentals of the Discrete Element Method (DEM) . . . . . . . . 9 2.1.2 Applications of DEM in comminution science . . . . . . . . . . . . . 21 2.1.3 Limitations of DEM in comminution science . . . . . . . . . . . . . . 26 2.2 Quantitative Microstructural Analysis . . . . . . . . . . . . . . . . . . . . . 29 2.2.1 Fundamentals of the Quantitative Microstructural Analysis . . . . . . 29 2.2.2 Applied QMA in mineral processing . . . . . . . . . . . . . . . . . . 49 2.2.3 Applicability of the QMA for the synthesis of realistic microstructures 49 3 Synthesis of realistic mineral microstructures for DEM simulations 51 3.1 Development of a computer-assisted QMA for the analysis of real and synthetic mineral microstructures . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 3.1.1 Fundamentals of the computer-assisted QMA . . . . . . . . . . . . 53 3.1.2 The requirements for the false-color image. . . . . . . . . . . . . . 54 3.1.3 The conversion of a given real mineral microstructure into a false-color image . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 3.1.4 Implementation of the point, line, and area analysis . . . . . . . . . 59 3.1.5 Selection of appropriate QMA parameters for analyzing two-dimensional microstructures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 3.1.6 Summary of the principles of the adapted Quantitative Microstructural Analysis (QMA) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 3.2 Analysis of possible strategies for the microstructure synthesis . . . . . . . . 71 3.3 Implementation of the drawing method . . . . . . . . . . . . . . . . . . . . 76 3.3.1 Drawing of a single grain . . . . . . . . . . . . . . . . . . . . . . . 77 XVIII List of Greek Symbols 3.3.2 Drawing of multiple grains, which form a synthetic microstructure . . 81 3.3.3 Synthesizing mineral microstructures consisting of multiple phases . 85 3.4 The final program for microstructure analysis and synthesis . . . . . . . . . 89 3.4.1 Synthesis and analysis of an example microstructure . . . . . . . . . 90 3.4.2 Procedure for generating a realistic synthetic microstructure of a given real microstructure . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 4 Validation of the synthesis approach 103 4.1 Methodical considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 4.1.1 The basic idea of the validation procedure . . . . . . . . . . . . . . 103 4.1.2 The experimental realizations . . . . . . . . . . . . . . . . . . . . . 108 4.2 Basic indenter test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 4.2.1 Considerations for the basic indenter test . . . . . . . . . . . . . . . 109 4.2.2 Realization and evaluation of the real basic indenter test . . . . . . . 114 4.2.3 Realization and evaluation of the simulated basic indenter test . . . 127 4.2.4 Conclusions on the basic indenter test . . . . . . . . . . . . . . . . . 138 4.3 Extended indenter test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139 4.3.1 Basic considerations for the extended indenter test . . . . . . . . . . 139 4.3.2 Realization and evaluation of the real extended indenter test . . . . 142 4.3.3 Realization and evaluation of the simulated extended indenter test . 154 4.3.4 Conclusions on the extended indenter test . . . . . . . . . . . . . . 171 4.4 Particle bed test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172 4.4.1 Basic considerations for the particle bed test . . . . . . . . . . . . . 173 4.4.2 Realization and evaluation of the real particle bed test . . . . . . . . 176 4.4.3 Realization and evaluation of the simulated particle bed test . . . . . 188 4.4.4 Conclusions on the particle bed test . . . . . . . . . . . . . . . . . . 203 5 Conclusions and directions for future development 205 6 References 211 List of Figures 229 List of Tables 235 Appendix 23

Collaboration on an Ontology for Generalisation

workshopInternational audienceTo move beyond the current plateau in automated cartography we need greater sophistication in the process of selecting generalisation algorithms. This is particularly so in the context of machine comprehension. We also need to build on existing algorithm development instead of duplication. More broadly we need to model the geographical context that drives the selection, sequencing and degree of application of generalisation algorithms. We argue that a collaborative effort is required to create and share an ontology for cartographic generalisation focused on supporting the algorithm selection process. The benefits of developing a collective ontology will be the increased sharing of algorithms and support for on-demand mapping and generalisation web services

Representing the function and sensitivity of coastal interfaces in Earth system models

Between the land and ocean, diverse coastal ecosystems transform, store, and transport material. Across these interfaces, the dynamic exchange of energy and matter is driven by hydrological and hydrodynamic processes such as river and groundwater discharge, tides, waves, and storms. These dynamics regulate ecosystem functions and Earth\u27s climate, yet global models lack representation of coastal processes and related feedbacks, impeding their predictions of coastal and global responses to change. Here, we assess existing coastal monitoring networks and regional models, existing challenges in these efforts, and recommend a path towards development of global models that more robustly reflect the coastal interface. Coastal systems are hotspots of ecological, geochemical and economic activity, yet their dynamics are not accurately represented in global models. In this Review, Ward and colleagues assess the current state of coastal science and recommend approaches for including the coastal interface in predictive models

Representing the function and sensitivity of coastal interfaces in earth system models

© The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Ward, N. D., Megonigal, J. P., Bond-Lamberty, B., Bailey, V. L., Butman, D., Canuel, E. A., Diefenderfer, H., Ganju, N. K., Goni, M. A., Graham, E. B., Hopkinson, C. S., Khangaonkar, T., Langley, J. A., McDowell, N. G., Myers-Pigg, A. N., Neumann, R. B., Osburn, C. L., Price, R. M., Rowland, J., Sengupta, A., Simard, M., Thornton, P. E., Tzortziou, M., Vargas, R., Weisenhorn, P. B., & Windham-Myers, L. Representing the function and sensitivity of coastal interfaces in earth system models. Nature Communications, 11(1), (2020): 2458, doi:10.1038/s41467-020-16236-2.Between the land and ocean, diverse coastal ecosystems transform, store, and transport material. Across these interfaces, the dynamic exchange of energy and matter is driven by hydrological and hydrodynamic processes such as river and groundwater discharge, tides, waves, and storms. These dynamics regulate ecosystem functions and Earth’s climate, yet global models lack representation of coastal processes and related feedbacks, impeding their predictions of coastal and global responses to change. Here, we assess existing coastal monitoring networks and regional models, existing challenges in these efforts, and recommend a path towards development of global models that more robustly reflect the coastal interface.Funding for this work was provided by Pacific Northwest National Laboratory (PNNL) Laboratory Directed Research & Development (LDRD) as part of the Predicting Ecosystem Resilience through Multiscale Integrative Science (PREMIS) Initiative. PNNL is operated by Battelle for the U.S. Department of Energy under Contract DE-AC05-76RL01830. Additional support to J.P.M. was provided by the NSF-LTREB program (DEB-0950080, DEB-1457100, DEB-1557009), DOE-TES Program (DE-SC0008339), and the Smithsonian Institution. This manuscript was motivated by discussions held by co-authors during a three-day workshop at PNNL in Richland, WA: The System for Terrestrial Aquatic Research (STAR) Workshop: Terrestrial-Aquatic Research in Coastal Systems. The authors thank PNNL artist Nathan Johnson for preparing the figures in this manuscript and Terry Clark, Dr. Charlette Geffen, and Dr. Nancy Hess for their aid in organizing the STAR workshop. The authors thank all workshop participants not listed as authors for their valuable insight: Lihini Aluwihare (contributed to biogeochemistry discussions and development of concept for Fig. 3), Gautam Bisht (contributed to modeling discussion), Emmett Duffy (contributed to observational network discussions), Yilin Fang (contributed to modeling discussion), Jeremy Jones (contributed to biogeochemistry discussions), Roser Matamala (contributed to biogeochemistry discussions), James Morris (contributed to biogeochemistry discussions), Robert Twilley (contributed to biogeochemistry discussions), and Jesse Vance (contributed to observational network discussions). A full report on the workshop discussions can be found at https://www.pnnl.gov/publications/star-workshop-terrestrial-aquatic-research-coastal-systems

Percepción Activa multi-robot para la cobertura rápida y eficiente de escenas.

The efficiency of path-planning in robot navigation is crucial in tasks, such as search-and-rescue and disaster surveying, but this is emphasised even more when considering multi-rotor aerial robots due to the limited battery and flight time. In this spirit, this Master Thesis proposes an efficient, hierarchical planner to achieve a comprehensive visual coverage of large-scale outdoor scenarios for small drones. Following an initial reconnaissance flight, a coarse map of the scene gets built in real-time. Then, regions of the map that were not appropriately observed are identified and grouped by a novel perception-aware clustering process that enables the generation of continuous trajectories (sweeps) to cover them efficiently. Thanks to this partitioning of the map in a set of tasks, we are able to generalize the planning to an arbitrary number of drones and perform a well-balanced workload distribution among them. We compare our approach to an alternative state-of-the-art method for exploration and show the advantages of our pipeline in terms of efficiency for obtaining coverage in large environments.<br /

Multi-robot active perception for fast andefficient scene reconstruction.

The efficiency of path-planning in robot navigation is crucial in tasks, such as search-and-rescue and disaster surveying, but this is emphasised even more when considering multi-rotor aerial robots due to the limited battery and flight time. In this spirit, this Master Thesis proposes an efficient, hierarchical planner to achieve a comprehensive visual coverage of large-scale outdoor scenarios for small drones. Following an initial reconnaissance flight, a coarse map of the scene gets built in real-time. Then, regions of the map that were not appropriately observed are identified and grouped by a novel perception-aware clustering process that enables the generation of continuous trajectories (sweeps) to cover them efficiently. Thanks to this partitioning of the map in a set of tasks, we are able to generalize the planning to an arbitrary number of drones and perform a well-balanced workload distribution among them. We compare our approach to an alternative state-of-the-art method for exploration and show the advantages of our pipeline in terms of efficiency for obtaining coverage in large environments.<br /