This document discusses phenomenological structuring of geographic information. It summarizes that current trends indicate a shift towards integrated decision support systems that require data to have more intelligence than conventional map applications. This intelligence comes from data relationships and structure, as well as techniques for manipulating and analyzing relationships. The document focuses on geographic knowledge bases, emphasizing that the structure of geographic information from a phenomenological viewpoint is concerned with determining what things are.
- Spatial autocorrelation measures the correlation of a variable with itself through space and can be positive or negative. It quantifies the degree of spatial clustering or dispersion of values across locations.
- Global measures identify overall patterns of clustering, while local measures identify specific clusters. Spatial weights defining neighbor relationships are required.
- Contiguity-based weights define neighbors based on shared boundaries, while distance-based weights use a threshold distance. Higher order weights incorporate indirect neighbors.
- Spatially lagged variables are weighted averages of neighboring values and are important for spatial autocorrelation tests and regression models.
This document discusses data structures for geographic and cartographic data. It notes that current data structures are characterized by: 1) being designed for input rather than use in programs, 2) storing different feature types in separate uncoordinated files, and 3) lacking information on neighboring entities. The concept of a "neighborhood function" is introduced to indicate an entity's relative location, which is important for analysis. Ongoing research includes the GEOGRAF and GDS systems, which involve manipulating data between input and use to address issues of flexibility, comparability, and topology.
On the-design-of-geographic-information-system-proceduresArmando Guevara
This document discusses the design of geographic information systems (GIS) and proposes an Adaptable Spatial Processing Architecture (ASPA) to improve upon existing GIS design. It identifies six concepts for continuity in GIS design: functional, data base, data structure, knowledge, human interface, and data transfer continuity. It also discusses using a generic functional model and specific derived spatial data models. The proposed ASPA architecture is based on these concepts of continuity and levels of abstraction, and aims to allow GIS to integrate diverse data sources and support multidisciplinary applications in a flexible, adaptable manner.
This document describes research into making digital elevation models (DEMs) more interactive. It discusses how most DEM display programs only show surface contours or parallel profiles, without allowing addition of other data or direct interaction. The researchers developed a new concept where visibility is stored as a property of spatial units (points, triangles), rather than computed only for display. This allows functions like adding roads/buildings, querying point locations, and rotating the surface without recomputing visibility each time. It explains how this concept was implemented in their triangular irregular network (TIN) DEM system to compute visibility in stages and store intermediate results in the database.
This document discusses different types of models used for modeling spatial processes in GIS for decision support. It describes natural and scale analogue models which use real-world events or objects as analogues. Conceptual models represent processes visually using diagrams. Mathematical models include deterministic, stochastic, and optimization models. Deterministic models show direct relationships while stochastic models use probabilities. Optimization models maximize or minimize outputs. The document argues that combining different modeling techniques in GIS allows for complex spatial process modeling to support decisions.
This document discusses spatial analysis and modeling in a geographical information system. It defines spatial analysis as gaining an understanding of patterns and processes underlying geographic features in order to make better decisions and understand phenomena. The document outlines four types of spatial analysis: spatial data manipulation, spatial data analysis, spatial statistical analysis, and spatial modeling. It also describes different vector and raster spatial analysis techniques, such as clipping, overlaying, buffering, and slope/aspect calculations. Spatial modeling is defined as using models to predict spatial outcomes and enable "what if" analyses.
Modeling a geo spatial database for managing travelers demandijdms
The geo-spatial database is a new technology in database systems which allow storing, retrieving and
maintaining the spatial data. In this paper, we seek to design and implement a geo-spatial database for
managing the traveler’s demand with the aid of open-source tools and object-relational database package.
The building of geo-spatial database starts with the design of data model in terms of conceptual, logical
and physical data model and then the design has been implemented into an object-relational database. The
geo-spatial database is developed to facilitate the storage of geographic information (where things are)
with descriptive information (what things are like) into the vector model. The developed vector geo-spatial
data can be accessed and rendered in the form of map to create the awareness of existence of various
services and facilities for prospective travelers and visitors.
- Spatial autocorrelation measures the correlation of a variable with itself through space and can be positive or negative. It quantifies the degree of spatial clustering or dispersion of values across locations.
- Global measures identify overall patterns of clustering, while local measures identify specific clusters. Spatial weights defining neighbor relationships are required.
- Contiguity-based weights define neighbors based on shared boundaries, while distance-based weights use a threshold distance. Higher order weights incorporate indirect neighbors.
- Spatially lagged variables are weighted averages of neighboring values and are important for spatial autocorrelation tests and regression models.
This document discusses data structures for geographic and cartographic data. It notes that current data structures are characterized by: 1) being designed for input rather than use in programs, 2) storing different feature types in separate uncoordinated files, and 3) lacking information on neighboring entities. The concept of a "neighborhood function" is introduced to indicate an entity's relative location, which is important for analysis. Ongoing research includes the GEOGRAF and GDS systems, which involve manipulating data between input and use to address issues of flexibility, comparability, and topology.
On the-design-of-geographic-information-system-proceduresArmando Guevara
This document discusses the design of geographic information systems (GIS) and proposes an Adaptable Spatial Processing Architecture (ASPA) to improve upon existing GIS design. It identifies six concepts for continuity in GIS design: functional, data base, data structure, knowledge, human interface, and data transfer continuity. It also discusses using a generic functional model and specific derived spatial data models. The proposed ASPA architecture is based on these concepts of continuity and levels of abstraction, and aims to allow GIS to integrate diverse data sources and support multidisciplinary applications in a flexible, adaptable manner.
This document describes research into making digital elevation models (DEMs) more interactive. It discusses how most DEM display programs only show surface contours or parallel profiles, without allowing addition of other data or direct interaction. The researchers developed a new concept where visibility is stored as a property of spatial units (points, triangles), rather than computed only for display. This allows functions like adding roads/buildings, querying point locations, and rotating the surface without recomputing visibility each time. It explains how this concept was implemented in their triangular irregular network (TIN) DEM system to compute visibility in stages and store intermediate results in the database.
This document discusses different types of models used for modeling spatial processes in GIS for decision support. It describes natural and scale analogue models which use real-world events or objects as analogues. Conceptual models represent processes visually using diagrams. Mathematical models include deterministic, stochastic, and optimization models. Deterministic models show direct relationships while stochastic models use probabilities. Optimization models maximize or minimize outputs. The document argues that combining different modeling techniques in GIS allows for complex spatial process modeling to support decisions.
This document discusses spatial analysis and modeling in a geographical information system. It defines spatial analysis as gaining an understanding of patterns and processes underlying geographic features in order to make better decisions and understand phenomena. The document outlines four types of spatial analysis: spatial data manipulation, spatial data analysis, spatial statistical analysis, and spatial modeling. It also describes different vector and raster spatial analysis techniques, such as clipping, overlaying, buffering, and slope/aspect calculations. Spatial modeling is defined as using models to predict spatial outcomes and enable "what if" analyses.
Modeling a geo spatial database for managing travelers demandijdms
The geo-spatial database is a new technology in database systems which allow storing, retrieving and
maintaining the spatial data. In this paper, we seek to design and implement a geo-spatial database for
managing the traveler’s demand with the aid of open-source tools and object-relational database package.
The building of geo-spatial database starts with the design of data model in terms of conceptual, logical
and physical data model and then the design has been implemented into an object-relational database. The
geo-spatial database is developed to facilitate the storage of geographic information (where things are)
with descriptive information (what things are like) into the vector model. The developed vector geo-spatial
data can be accessed and rendered in the form of map to create the awareness of existence of various
services and facilities for prospective travelers and visitors.
The present study evaluates the possibility of spatial heterogeneity in the effects on municipal-level crime rates of both demographic and socio-economic variables. Geoggraphically weighted regression (GWR) is used for exploring spatial heterogeneity and confirms that place matters.
IJRET-V1I1P3 - Remotely Sensed Images in using Automatic Road Map CompilationISAR Publications
High Resolution satellite Imagery is an important source for road network extraction for
roads database creation, refinement and updating. Various sources of imagery are known for their
differences in spectral, spatial, radioactive and temporal characteristics and thus are suitable for
different purposes of vegetation mapping. A number of shape descriptors are computed to reduce
the misclassification between road and other spectrally similar objects. The detected road segments
are further refined using morphological operations to form final road network, which is then
evaluated for its completeness, correctness and quality. The proposed methodology has been tested
on updating on road extraction from remotely-sensed imagery.
This document discusses GIS topology, which establishes rules for how geographic features share geometry and spatial relationships. Topology ensures data quality, enhances analysis, and manages coincident geometry. It has three components: connectivity between nodes and arcs, area definition using polygon boundaries, and contiguity to determine adjacent features. Topological rules prevent errors like overlaps, gaps, dangles and ensure proper containment of points and boundaries.
GIS.INTRODUCTION TO GIS PACKAGES &GEOGRAPHIIC ANALYSISTessaRaju
A geographic information system (GIS) allows users to integrate and analyze spatial data from a variety of sources through mapping and visualization. GIS provides tools to gather, store, retrieve, analyze and output geographic data. Spatial analysis techniques in GIS, such as buffering, proximity analysis and overlay analysis, enable users to model and understand relationships within and between spatial datasets to gain insights and solve problems.
Dynamic Land-Use Map Based on Twitter DataYuyun Wabula
This document describes a study that uses Twitter check-in data to characterize dynamic urban land use in Makassar City, Indonesia. The researchers collected over 170,000 Twitter check-in records over 6 weeks. They divided the city into grid blocks and removed blocks without check-ins, leaving 398 blocks. Text mining of user posts identified 85 venues that were categorized into 6 land use types. Two methods, rank and k-means clustering, were used to group the blocks and compare approaches for land use identification.
In this study various techniques for exploratory spatial data analysis are reviewed : spatial autocorrelation, Moran's I statistic, hot spots analysis, spatial lag and spatial error models.
The document discusses spatial data and spatial analysis. It defines spatial data as data connected to locations on Earth, with three main components - geometric data describing location, thematic data providing attribute values, and identifiers linking the geometric and thematic components. Spatial analysis in GIS involves functions like measurements, queries, classifications and modeling to analyze spatial relationships in the data and address real-world problems. Common analysis functions in GIS include measurements, queries, extractions, proximity analysis, and network analysis.
This document discusses various types of spatial analysis that can be performed using GIS. It describes how GIS allows for visual representation of data, precise vector analysis, integration of spatial and non-spatial data, and updatable analysis. The document then outlines specific spatial analysis techniques including map production, geovisualization, querying and measurement, descriptive summaries, and modeling. It provides examples for each type of analysis like cartograms for geovisualization and buffering and overlay for transformation.
THE NATURE AND SOURCE OF GEOGRAPHIC DATANadia Aziz
The document discusses various topics related to geographic data, including data formats, data capture, and data management. It describes the differences between raster and vector data formats and when each is generally used. It outlines methods for primary and secondary geographic data capture, including remote sensing, surveying, scanning, and digitizing. It also covers managing data capture projects, data editing, data conversion between formats, and linking geographic data.
Remote sensing and GIS can be applied in civil engineering for spatial analysis and to answer geographic queries. Spatial analysis examines how the locations of objects impact analysis results and can reveal patterns. GIS uses methods like overlay, proximity, density, and network analysis to study spatial relationships. Common analyses include measuring distances, areas and shapes, transforming datasets, descriptive summaries of data, and optimizing locations.
TYBSC IT PGIS Unit I Chapter II Geographic Information and Spacial DatabaseArti Parab Academics
This document discusses geographic information systems and spatial databases. It covers several key topics:
1) Models and representations of the real world in digital form, including raster and vector data models. Raster models use a grid approach while vector models represent points, lines and polygons.
2) Types of geographic phenomena like fields and objects that can be represented. Fields have values across a continuous space like elevation, while objects are discrete like roads.
3) Computer representations including raster and vector formats. Raster uses a grid of cells while vector uses points, lines and polygons.
4) Topology and spatial relationships between objects like containment, overlap and adjacency.
5) Organizing and managing spatial data in
What is GIS ?
Dimensions Modeling in GIS ?
GIS Models real word(Raster, Vector)
GIS Challenges ? Data and Tech.
GIS Functionality
Building information modeling (BIM) ?
GIS Components
Spatial Data
GIS in Public Health Research: Understanding Spatial Analysis and Interpretin...hpaocec
Geographic information systems (GIS) allow us to visualize data to better understand public health issues in our communities. Maps help recognize patterns for hypothesis generation; however, spatial analysis is necessary to substantiate relationships and produce meaningful outcomes. In this presentation we will discuss a few of the basic questions related to spatial analysis:
This document discusses the importance of data in geographical information systems (GIS). It states that data is the core component of GIS, as GIS relies on data to perform analysis and display results. The document outlines the different types of data used in GIS, including spatial data that represents geographic locations and attributes, and non-spatial attribute data. It also describes how data is structured, captured, integrated, and edited within a GIS to ensure accuracy and allow for analysis across different data layers. The key role of data in enabling the functionality of GIS tools and applications is emphasized throughout the document.
Data Visualization GIS and Maps, The Visualization Process Visualization Strategies: Present or explore? The cartographic toolbox: What kind of data do I have?, How can I map my data? How to map?: How to map qualitative data, How to map quantitative data, How to map the terrain elevation, How to map time series Map Cosmetics, Map Dissemination
Topics:
1. Mapping Concepts
2. Analysis with paper based Maps
3. Limitations of Paper based Maps
4. Computer Aided Cartography History and Development
5. GIS Definition
6. Advantage of Digital Maps
This document provides an overview of remote sensing and geographical information systems (GIS) in civil engineering. It discusses key concepts like vector and raster data models, data coding, representation of geographic features as points, lines and areas, common vector data structures including topology and dual independent map encoding, and data compression techniques. The course will cover GIS software, spatial queries, analysis functions, and practice generating hydrological modeling inputs like digital elevation models and flow maps from terrain data.
This document discusses geographic information and phenomenology. It proposes that geographic data should be structured based on real-world phenomena rather than forced into vector or raster models. The key points are:
1) Geographic data models have traditionally focused on vector or raster structures, but these can create unrealistic representations of real-world phenomena.
2) A better approach is to represent geographic information based on the actual structures and relationships of phenomena in the real world, independent of any particular application.
3) Phenomena can be described by functional categories and topological properties, spatially referenced in a geographic knowledge base. The interpretation and analysis of relationships between phenomena constitutes cognition.
The present study evaluates the possibility of spatial heterogeneity in the effects on municipal-level crime rates of both demographic and socio-economic variables. Geoggraphically weighted regression (GWR) is used for exploring spatial heterogeneity and confirms that place matters.
IJRET-V1I1P3 - Remotely Sensed Images in using Automatic Road Map CompilationISAR Publications
High Resolution satellite Imagery is an important source for road network extraction for
roads database creation, refinement and updating. Various sources of imagery are known for their
differences in spectral, spatial, radioactive and temporal characteristics and thus are suitable for
different purposes of vegetation mapping. A number of shape descriptors are computed to reduce
the misclassification between road and other spectrally similar objects. The detected road segments
are further refined using morphological operations to form final road network, which is then
evaluated for its completeness, correctness and quality. The proposed methodology has been tested
on updating on road extraction from remotely-sensed imagery.
This document discusses GIS topology, which establishes rules for how geographic features share geometry and spatial relationships. Topology ensures data quality, enhances analysis, and manages coincident geometry. It has three components: connectivity between nodes and arcs, area definition using polygon boundaries, and contiguity to determine adjacent features. Topological rules prevent errors like overlaps, gaps, dangles and ensure proper containment of points and boundaries.
GIS.INTRODUCTION TO GIS PACKAGES &GEOGRAPHIIC ANALYSISTessaRaju
A geographic information system (GIS) allows users to integrate and analyze spatial data from a variety of sources through mapping and visualization. GIS provides tools to gather, store, retrieve, analyze and output geographic data. Spatial analysis techniques in GIS, such as buffering, proximity analysis and overlay analysis, enable users to model and understand relationships within and between spatial datasets to gain insights and solve problems.
Dynamic Land-Use Map Based on Twitter DataYuyun Wabula
This document describes a study that uses Twitter check-in data to characterize dynamic urban land use in Makassar City, Indonesia. The researchers collected over 170,000 Twitter check-in records over 6 weeks. They divided the city into grid blocks and removed blocks without check-ins, leaving 398 blocks. Text mining of user posts identified 85 venues that were categorized into 6 land use types. Two methods, rank and k-means clustering, were used to group the blocks and compare approaches for land use identification.
In this study various techniques for exploratory spatial data analysis are reviewed : spatial autocorrelation, Moran's I statistic, hot spots analysis, spatial lag and spatial error models.
The document discusses spatial data and spatial analysis. It defines spatial data as data connected to locations on Earth, with three main components - geometric data describing location, thematic data providing attribute values, and identifiers linking the geometric and thematic components. Spatial analysis in GIS involves functions like measurements, queries, classifications and modeling to analyze spatial relationships in the data and address real-world problems. Common analysis functions in GIS include measurements, queries, extractions, proximity analysis, and network analysis.
This document discusses various types of spatial analysis that can be performed using GIS. It describes how GIS allows for visual representation of data, precise vector analysis, integration of spatial and non-spatial data, and updatable analysis. The document then outlines specific spatial analysis techniques including map production, geovisualization, querying and measurement, descriptive summaries, and modeling. It provides examples for each type of analysis like cartograms for geovisualization and buffering and overlay for transformation.
THE NATURE AND SOURCE OF GEOGRAPHIC DATANadia Aziz
The document discusses various topics related to geographic data, including data formats, data capture, and data management. It describes the differences between raster and vector data formats and when each is generally used. It outlines methods for primary and secondary geographic data capture, including remote sensing, surveying, scanning, and digitizing. It also covers managing data capture projects, data editing, data conversion between formats, and linking geographic data.
Remote sensing and GIS can be applied in civil engineering for spatial analysis and to answer geographic queries. Spatial analysis examines how the locations of objects impact analysis results and can reveal patterns. GIS uses methods like overlay, proximity, density, and network analysis to study spatial relationships. Common analyses include measuring distances, areas and shapes, transforming datasets, descriptive summaries of data, and optimizing locations.
TYBSC IT PGIS Unit I Chapter II Geographic Information and Spacial DatabaseArti Parab Academics
This document discusses geographic information systems and spatial databases. It covers several key topics:
1) Models and representations of the real world in digital form, including raster and vector data models. Raster models use a grid approach while vector models represent points, lines and polygons.
2) Types of geographic phenomena like fields and objects that can be represented. Fields have values across a continuous space like elevation, while objects are discrete like roads.
3) Computer representations including raster and vector formats. Raster uses a grid of cells while vector uses points, lines and polygons.
4) Topology and spatial relationships between objects like containment, overlap and adjacency.
5) Organizing and managing spatial data in
What is GIS ?
Dimensions Modeling in GIS ?
GIS Models real word(Raster, Vector)
GIS Challenges ? Data and Tech.
GIS Functionality
Building information modeling (BIM) ?
GIS Components
Spatial Data
GIS in Public Health Research: Understanding Spatial Analysis and Interpretin...hpaocec
Geographic information systems (GIS) allow us to visualize data to better understand public health issues in our communities. Maps help recognize patterns for hypothesis generation; however, spatial analysis is necessary to substantiate relationships and produce meaningful outcomes. In this presentation we will discuss a few of the basic questions related to spatial analysis:
This document discusses the importance of data in geographical information systems (GIS). It states that data is the core component of GIS, as GIS relies on data to perform analysis and display results. The document outlines the different types of data used in GIS, including spatial data that represents geographic locations and attributes, and non-spatial attribute data. It also describes how data is structured, captured, integrated, and edited within a GIS to ensure accuracy and allow for analysis across different data layers. The key role of data in enabling the functionality of GIS tools and applications is emphasized throughout the document.
Data Visualization GIS and Maps, The Visualization Process Visualization Strategies: Present or explore? The cartographic toolbox: What kind of data do I have?, How can I map my data? How to map?: How to map qualitative data, How to map quantitative data, How to map the terrain elevation, How to map time series Map Cosmetics, Map Dissemination
Topics:
1. Mapping Concepts
2. Analysis with paper based Maps
3. Limitations of Paper based Maps
4. Computer Aided Cartography History and Development
5. GIS Definition
6. Advantage of Digital Maps
This document provides an overview of remote sensing and geographical information systems (GIS) in civil engineering. It discusses key concepts like vector and raster data models, data coding, representation of geographic features as points, lines and areas, common vector data structures including topology and dual independent map encoding, and data compression techniques. The course will cover GIS software, spatial queries, analysis functions, and practice generating hydrological modeling inputs like digital elevation models and flow maps from terrain data.
This document discusses geographic information and phenomenology. It proposes that geographic data should be structured based on real-world phenomena rather than forced into vector or raster models. The key points are:
1) Geographic data models have traditionally focused on vector or raster structures, but these can create unrealistic representations of real-world phenomena.
2) A better approach is to represent geographic information based on the actual structures and relationships of phenomena in the real world, independent of any particular application.
3) Phenomena can be described by functional categories and topological properties, spatially referenced in a geographic knowledge base. The interpretation and analysis of relationships between phenomena constitutes cognition.
Geographic Information System (GIS) is a computer system for capturing, storing, analyzing and managing data and associated attributes which are spatially referenced to the Earth. GIS allows users to visually see relationships, patterns and trends hidden within geographic datasets. It allows analysis and output of geographically referenced data. GIS also refers to spatial information systems and the tools used to gather, store, retrieve, analyze and display geographic or spatial data.
TYBSC IT PGIS Unit I Chapter I- Introduction to Geographic Information SystemsArti Parab Academics
A Gentle Introduction to GIS The nature of GIS: Some fundamental observations, Defining GIS, GISystems, GIScience and GIApplications, Spatial data and Geoinformation. The real world and representations of it: Models and modelling, Maps, Databases, Spatial databases and spatial analysis
The document discusses maps and geographic information systems. It defines maps as any geographic image of the environment, including mental maps held solely in our minds. Traditionally, cartography focused on producing maps through scaling, generalization, symbolization and transformation. However, geographic information systems now provide capabilities for more sophisticated mapping and analysis by combining automated mapping with linkages that allow complex queries, overlays and spatial modeling. The document argues future systems should address more complex geographic problems and better communicate results using various methods.
This document discusses expert systems for interrogating infrastructure. It defines an expert system as an arrangement of information related to form a unified whole, with skill and training in a specialized field. The document outlines that expert systems could help with relief operations, search and rescue, and route planning by interrogating infrastructure data. It describes key components of an expert system, including communication modules to interact with users, and the ability to provide timely, accurate responses tailored to users' needs.
Applying association rules and co location techniques on geospatial web servicesAlexander Decker
This document summarizes a study that applies spatial data mining techniques like association rule mining and co-location analysis to geospatial data from different crisis management systems. The study develops a web service that integrates data from traffic, medical, and civil defense systems about road accidents and fires. Spatial rule mining reveals relationships between accidents, fires, road cuts, and losses. A case study applies the approach to emergency response data from Alexandria, Egypt. Regression analysis confirms the validity of rules discovered from mining the integrated geospatial data.
The basic intention of this presentation is to help the beginners in GIS to understand what GIS is? It is a simple presentation about GIS, i mean an introductory one. Hope anyone finds it useful.
A hybrid approach for analysis of dynamic changes in spatial dataijdms
Any geographic location undergoes changes over a period of time. These changes can be observed by
naked eye, only if they are huge in number spread over a small area. However, when the changes are small
and spread over a large area, it is very difficult to observe or extract the changes. Presently, there are few
methods available for tackling these types of problems, such as GRID, DBSCAN etc. However, these
existing mechanisms are not adequate for finding an accurate changes or observation which is essential
with respect to most important geometrical changes such as deforestations and land grabbing etc.,. This
paper proposes new mechanism to solve the above problem. In this proposed method, spatial image
changes are compared over a period of time taken by the satellite. Partitioning the satellite image in to
grids, employed in the proposed hybrid method, provides finer details of the image which are responsible
for improving the precision of clustering compared to whole image manipulation, used in DBSCAN, at a
time .The simplicity of DBSCAN explored while processing portioned grid portion.
The document discusses spatial data and spatial databases. It defines spatial data as data related to space, including location, shape, size and orientation of objects. It discusses the types of spatial data like points, lines, polygons and pixels. It also discusses non-spatial data and how spatial data is organized using coordinates. The key properties of spatial data are geometry, distribution of objects in space, temporal changes and data volume. Spatial databases allow for efficient storage and querying of spatial data through the use of spatial data types and indexes.
Understanding Map Integration Using GIS Software_ffMichelle Pasco
This document discusses map integration methods for road network data from two sources, the Virginia Department of Transportation's Linear Referencing System (LRS) and proprietary data from INRIX (XD). Two methods, spatial join and transfer attributes, are evaluated on five Virginia interstates. Spatial join joins features based on intersecting geometry, while transfer attributes joins on common attributes within a search distance. The accuracy of each method is calculated based on the number of features that match between the datasets. Spatial join is tested using different coordinate systems and LRS layers, while transfer attributes varies the search distance. Visualizing the buffers helps understand how distance affects matching.
This document provides an overview of agent-based modeling (ABM) and its applications in geography. It discusses how ABM has evolved from earlier modeling approaches like cellular automata and microsimulation by allowing for the simulation of autonomous individuals with heterogeneous attributes and behaviors that interact within a spatial environment. The document outlines the key steps to building an ABM, including model design, implementation, and evaluation techniques. It also explores how ABM can be integrated with geographic information systems to account for spatial factors. A range of example applications are presented along with ongoing challenges and opportunities for further developing ABM.
A Study on Data Visualization Techniques of Spatio Temporal DataIJMTST Journal
Data visualization is an important tool to analyze complex Spatio Temporal data. The spatio-temporal data
can be visualized using 2D, 3D or any other type of maps. Cartography is the major technique used in
mapping. The data can also be visualized by placing different layers of maps one on other, which is done by
using GIS. Many data visualization techniques are in trend but the usage of the techniques must be decided
by considering the application requirements.
Geographical Information System By Zewde Alemayehu Tilahun.pptxzewde alemayehu
This document provides an overview of Geographic Information Systems (GIS). It discusses key GIS concepts such as geographic phenomena, data types and structures, coordinate systems, map projections, and spatial analysis. GIS is defined as an integrated system for capturing, storing, analyzing and managing data which is spatially referenced to Earth. The document also outlines common data collection methods, applications of GIS, and its ability to answer questions about location, attributes, trends and patterns across geographic space.
Geographical information system by zewde alemayehu tilahunzewde alemayehu
The document summarizes key concepts related to Geographic Information Systems (GIS). It discusses what GIS is, its components and applications. It also covers geographic phenomena, data types, coordinate systems, and methods for data entry, preparation and analysis in GIS.
There have been two main categories of research on mining moving object data: moving object cluster discovery and trajectory clustering. Moving object clustering identifies groups of objects that travel together without defined locations, while trajectory clustering groups locations based on similar object movements but ignores traveling time. Recent studies have proposed concepts like temporal moving object swarms that capture objects moving within non-consecutive time-based clusters, and probabilistic modeling of trajectory sets to identify common paths between trajectories. Future work could focus on clustering algorithms that integrate both location and time dimensions to better characterize moving object behaviors.
Spatial association discovery process using frequent subgraph miningTELKOMNIKA JOURNAL
Spatial associations are one of the most relevant kinds of patterns used by business
intelligence regarding spatial data. Due to the characteristics of this particular type of
information, different approaches have been proposed for spatial association mining.
This wide variety of methods has entailed the need for a process to integrate the activities
for association discovery, one that is easy to implement and flexible enough to
be adapted to any particular situation, particularly for small and medium-size projects
to guide the useful pattern discovery process. Thus, this work proposes an adaptable
knowledge discovery process that uses graph theory to model different spatial relationships
from multiple scenarios, and frequent subgraph mining to discover spatial
associations. A proof of concept is presented using real data.
This document discusses the importance of statistics in geography. It notes that geography seeks to classify phenomena, compare locations, generalize patterns, and determine the influence of natural laws on humans. This makes geography a science that uses statistical techniques. Statistics help geographers understand spatial patterns and relationships between natural, physical, and social characteristics of places. Geography deals with spatial data that has locational attributes, so statistical analysis in geography considers the spatial aspects of data. Statistical techniques allow geographers to describe, summarize, analyze, and interpret spatial patterns in geographical data.
Topographic Information System as a Tool for Environmental Management, a Case...iosrjce
IOSR Journal of Environmental Science, Toxicology and Food Technology (IOSR-JESTFT) multidisciplinary peer-reviewed Journal with reputable academics and experts as board member. IOSR-JESTFT is designed for the prompt publication of peer-reviewed articles in all areas of subject. The journal articles will be accessed freely online.
Similar to Phenomenological Structuring of Geographic Information (20)
Dare to Change 1980Reflections of one of Australia's Military MapmakersRobert (Bob) Williams
1. In the late 1970s, the author was given the opportunity to study cartography and computing science integration at the Canberra College of Advanced Education (now University of Canberra). There, he learned about developing digital mapping applications from his lecturer Waldemar Wassermann.
2. In 1980, the author wrote a discussion paper called "Defence Enquiry System" that proposed a geographic information system for defense applications like tracking personnel and equipment. He also worked on a mapping application called MAPPACK that demonstrated options for education and navigation uses.
3. MAPPACK allowed users to generate different map projections and manipulate continents to simulate plate tectonics. It also produced specialized maps for navigation including strip
This is an overview of a cartographic mapping package developed at the Canberra College of Advanced Education. The package demonstrates educational and navigational applications and was produced for the semester unit Special Studies in Computing in the course for the award of Bachelor of Arts in Computing Studies.
It was 20 years ago!
Dare to Change - Geographic Intelligence – The Key to Information Superiority
Request for assistance:
“I’ve lined up CDF (Chief of the Defence Force) to give a luncheon talk to the members of ASIBA (Australasia Spatial Information Business Association) on Thursday 10 October. Naturally I will have to write his speech! If you have any particular thoughts on what I might include, I would be grateful. The aim will be to give the spatial industry lobby a feeling that Defence recognises, values and needs quality geo information in many areas.
As well, I’ve agreed to speak to AURISA (Australasian Urban and Regional Information Association) on November 27 – guest / keynote speaker I think. Again any ideas you might want to proffer would be welcome”.
[Director, DIGO]
Geospatial Intelligence in Support of the Australian Approach to WarfareRobert (Bob) Williams
This paper (written in 2003) introduces the term geospatial intelligence to the lexicon of Australia’s national security. The paper describes a framework of concepts as they apply to imagery, imagery intelligence, and geographic, infrastructure and environmental information, referred to collectively as Geospatial Intelligence. The paper also describes the means of acquiring, processing and disseminating the range of products and services to the Defence community, referred to as Geospatial Information Infrastructure.
The article linked to (below) is somewhat of an odyssey. It commences with discussion on, possibly, the first land information system in Australia and my association with it - Eurobodalla.
It then briefly describes follow on applications including a military terrain-mapping product. Subsequent products cover the littoral zone for beach landings. So, it could be described as terrain intelligence.
This idea stemmed from the D-Day invasion maps (Benson and Bigot).
And, so, follows the Benson and Bigot story – an amazing cartographic accomplishment. To view a video of this stunning activity view the link at the end of the article
The article linked to (below) is somewhat of an odyssey. It commences with discussion on, possibly, the first land information system in Australia and my association with it - Eurobodalla.
It then briefly describes follow on applications including a military terrain-mapping product. Subsequent products cover the littoral zone for beach landings. So, it could be described as terrain intelligence.
This idea stemmed from the D-Day invasion maps (Benson and Bigot).
And, so, follows the Benson and Bigot story – an amazing cartographic accomplishment. To view a video of this stunning activity view the link at the end of the article.
Hydrospatial 21 [Education] - Dr Bob Williams
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My Hydrospatial 21 presentation titled "Back to the Future: The Climate for Change and the Hydrographer of the Future" contained a number of slides noting supplement.
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Information contained in this product has been compiled from a range of sources from the Internet.
Information has NOT been independently validated.
This product has been developed as a ‘proof of concept’ for electronic geographic briefs (eGeoBrief)
There are moments in one’s career that, in retrospect, hold significance. The 24th August 2001 is one of those days – 20 years ago today.
On 23rd August I travelled from Adelaide to Canberra and gave a number of presentations on my recent overseas trip on 24 August 2001.
In this document I introduce two audacious initiatives: Aeronatical Intelligence and eGeoBriefs (via an avatar).
Twenty years ago various organisations and professional bodies were developing leading edge capability in geospatial infrastructures. This presentation following an overseas visit was given to various groups in Canberra on 24 August 2001.
This document discusses two approaches to incorporating data quality statements into spatial databases. It describes the Vector Product Format (VPF) used by the Digital Chart of the World project, which contains data quality information at different levels to allow users to evaluate data utility. VPF includes seven types of data quality information such as source, positional accuracy, and logical consistency. The document also discusses guidelines from the International Cartographic Association to provide a consistent approach to assessing data quality.
This is a story of an amazing military mapping organisation and its iconic home - Fortuna Villa, Bendigo. The document include many photographs, figures, and descriptions.
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𝐃𝐢𝐬𝐜𝐮𝐬𝐬 𝐭𝐡𝐞 𝐄𝐏𝐏 𝐂𝐮𝐫𝐫𝐢𝐜𝐮𝐥𝐮𝐦 𝐢𝐧 𝐭𝐡𝐞 𝐏𝐡𝐢𝐥𝐢𝐩𝐩𝐢𝐧𝐞𝐬:
- Understand the goals and objectives of the Edukasyong Pantahanan at Pangkabuhayan (EPP) curriculum, recognizing its importance in fostering practical life skills and values among students. Students will also be able to identify the key components and subjects covered, such as agriculture, home economics, industrial arts, and information and communication technology.
𝐄𝐱𝐩𝐥𝐚𝐢𝐧 𝐭𝐡𝐞 𝐍𝐚𝐭𝐮𝐫𝐞 𝐚𝐧𝐝 𝐒𝐜𝐨𝐩𝐞 𝐨𝐟 𝐚𝐧 𝐄𝐧𝐭𝐫𝐞𝐩𝐫𝐞𝐧𝐞𝐮𝐫:
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Making of a Nation.
From the NZ Wars to Liberals,
Richard Seddon, George Grey,
Social Laboratory, New Zealand,
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Chapter wise All Notes of First year Basic Civil Engineering
Syllabus
Chapter-1
Introduction to objective, scope and outcome the subject
Chapter 2
Introduction: Scope and Specialization of Civil Engineering, Role of civil Engineer in Society, Impact of infrastructural development on economy of country.
Chapter 3
Surveying: Object Principles & Types of Surveying; Site Plans, Plans & Maps; Scales & Unit of different Measurements.
Linear Measurements: Instruments used. Linear Measurement by Tape, Ranging out Survey Lines and overcoming Obstructions; Measurements on sloping ground; Tape corrections, conventional symbols. Angular Measurements: Instruments used; Introduction to Compass Surveying, Bearings and Longitude & Latitude of a Line, Introduction to total station.
Levelling: Instrument used Object of levelling, Methods of levelling in brief, and Contour maps.
Chapter 4
Buildings: Selection of site for Buildings, Layout of Building Plan, Types of buildings, Plinth area, carpet area, floor space index, Introduction to building byelaws, concept of sun light & ventilation. Components of Buildings & their functions, Basic concept of R.C.C., Introduction to types of foundation
Chapter 5
Transportation: Introduction to Transportation Engineering; Traffic and Road Safety: Types and Characteristics of Various Modes of Transportation; Various Road Traffic Signs, Causes of Accidents and Road Safety Measures.
Chapter 6
Environmental Engineering: Environmental Pollution, Environmental Acts and Regulations, Functional Concepts of Ecology, Basics of Species, Biodiversity, Ecosystem, Hydrological Cycle; Chemical Cycles: Carbon, Nitrogen & Phosphorus; Energy Flow in Ecosystems.
Water Pollution: Water Quality standards, Introduction to Treatment & Disposal of Waste Water. Reuse and Saving of Water, Rain Water Harvesting. Solid Waste Management: Classification of Solid Waste, Collection, Transportation and Disposal of Solid. Recycling of Solid Waste: Energy Recovery, Sanitary Landfill, On-Site Sanitation. Air & Noise Pollution: Primary and Secondary air pollutants, Harmful effects of Air Pollution, Control of Air Pollution. . Noise Pollution Harmful Effects of noise pollution, control of noise pollution, Global warming & Climate Change, Ozone depletion, Greenhouse effect
Text Books:
1. Palancharmy, Basic Civil Engineering, McGraw Hill publishers.
2. Satheesh Gopi, Basic Civil Engineering, Pearson Publishers.
3. Ketki Rangwala Dalal, Essentials of Civil Engineering, Charotar Publishing House.
4. BCP, Surveying volume 1
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ISO/IEC 27001, ISO/IEC 42001, and GDPR: Best Practices for Implementation and...PECB
Denis is a dynamic and results-driven Chief Information Officer (CIO) with a distinguished career spanning information systems analysis and technical project management. With a proven track record of spearheading the design and delivery of cutting-edge Information Management solutions, he has consistently elevated business operations, streamlined reporting functions, and maximized process efficiency.
Certified as an ISO/IEC 27001: Information Security Management Systems (ISMS) Lead Implementer, Data Protection Officer, and Cyber Risks Analyst, Denis brings a heightened focus on data security, privacy, and cyber resilience to every endeavor.
His expertise extends across a diverse spectrum of reporting, database, and web development applications, underpinned by an exceptional grasp of data storage and virtualization technologies. His proficiency in application testing, database administration, and data cleansing ensures seamless execution of complex projects.
What sets Denis apart is his comprehensive understanding of Business and Systems Analysis technologies, honed through involvement in all phases of the Software Development Lifecycle (SDLC). From meticulous requirements gathering to precise analysis, innovative design, rigorous development, thorough testing, and successful implementation, he has consistently delivered exceptional results.
Throughout his career, he has taken on multifaceted roles, from leading technical project management teams to owning solutions that drive operational excellence. His conscientious and proactive approach is unwavering, whether he is working independently or collaboratively within a team. His ability to connect with colleagues on a personal level underscores his commitment to fostering a harmonious and productive workplace environment.
Date: May 29, 2024
Tags: Information Security, ISO/IEC 27001, ISO/IEC 42001, Artificial Intelligence, GDPR
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Phenomenological Structuring of Geographic Information
1. 1
PHENOMENOLOGICALPHENOMENOLOGICAL
STRUCTURING OFSTRUCTURING OF
GEOGRAPHIC INFORMATIONGEOGRAPHIC INFORMATION22
Major R.J.Williams
TECHNICAL PAPERS
8
th
Australian Cartographic
Conference
In association with the ICA
DARWIN, AUSTRALIA
30 April - 3 May, 1990
1990
BIOGRAPHICAL DETAILS
Robert Williams has twenty-four years experience in the disciplines of surveying and
mapping. After enlisting in the Australian Regular Army in 1965 he joined the Royal
Australian Survey Corps Over the next nine years he attended a series of technical
courses in geodesy, topographic surveying, photogrammetry, and mapping topics, as
well as working in technical and managerial roles in the map production process. In
1976 he became the first supervisor of the photogrammetric and manual digitizer
input sub-system of RASVY’s AUTOMAP I computer-assisted mapping system.
During the period 1977-79 Robert studied for the award of BA Computing Studies
majoring in cartography and undertaking his major project in oblique aspect map
projections. Then followed managerial roles in aeronautical chart and topographic
map projection. In 1983-85 Robert undertook further studies, this time at the
University of Wisconsin-Madison obtaining an MSc (Cartography) and specializing
in computerized land information systems and contemporary cartography. On return
to Australia Robert was employed as a research officer at the Army Survey Regiment
at Bendigo, Victoria before undertaking research at the Australian Defence Force
Academy leading to a PhD. His current employment is again as a research officer at
Army Survey Regiment.
Robert specializes in contemporary cartography, the evolution in digital processing of
geographic information and geographic data structures.
1 Published by the 8th
Australian Cartographic Conference Committee, Darwin, Australia, 1990.
ISBN 0 7316 90362
2 This paper has been re-typed and figures redrawn but has not been altered in any other way from the
original paper. The presentation of this paper was given in Session 6 – Land and Geographic
Information Systems.
2. 2
ABSTRACT
Current trends in processing digital geographic data indicate a shift towards integrated
decision-support systems and operations management. This paper reviews
developments in managing and structuring digital cartographic data and observes that,
although developments have been rational, they have often been technology and
application driven. The trend to decision-support systems, however, requires data to
have far more intelligence than for the more conventional map and overlay analysis
applications.
The paper notes that intelligence can be achieved by two fundamental, but integrated
sources. These sources are those of data relationships and structure, and techniques
and procedures for manipulating and analysing the data relationships. These
characteristics are subsequently equated to the notions of geographic knowledge rules,
the former notion being concerned with the organization and structuring of
geographic phenomena, while the latter notion is concerned with analysing and
interpreting aspects and relationships (or cognitive aspects) of the geographic reality.
This paper concentrates on Geographic Knowledge-Bases and emphasizes that the
structure of geographic information from a phenomenological viewpoint is concerned
with finding out what things are.
INTRODUCTION
Computers have been used to process geographic data for up to two and a half
decades. Major technological advances occurred when scientists at the Experimental
Cartographic Unit (UK) developed the first digitizing tables (Bickmore, 1964);
academic researchers realized the potential of applying analytical techniques to three
dimensional models (Yoelli, 1959), as well as managing natural and man-made
resources (Tomlinson, 1972); and photogrammetrists first began using analytical
techniques for photogrammetric mensuration and adjustments (Friedman et al, 1980,
p.703).
However, because of different emphases placed on the management and use of
geographic data by mapping agencies and resource management organizations, two
distinct trends occurred in the evolution and development of digital cartography. The
trend followed by the mapping organizations has become known as computer-assisted
mapping. This trend emphasized graphic representation of data, classification and
categorization of geographic features, and is characterized by the importance placed
on coordinate referencing and positional accuracies. The second trend, generally
known or associated with geographic information systems, has been favoured by
resource and utility managers. This second primary trend, in turn, consists of three
definite sub-trends; these being terrain modeling, remote sensing, and land
information systems (or multipurpose cadastre systems).
Throughout the development of digital mapping and geographic information systems,
there has been a competition between three basic models for data structure: raster,
computer-aided design, and topological. The raster model describes the geometric
elements as cells in an integer space. Using the simplicity of enumerating objects in
the integer space, the raster approach has many proponents, but most of the arguments
3. 3
are based on technical considerations. Grid cell and raster models are types of
tessellation models. . The two vector models adopt geometry of continuous space to
position points, lines and areas. The computer-aided design model places the
primitive objects into separate layers, but does not introduce any further data
structure. The topological model takes the same primitive objects, but places them
into a network of relationships (Peuquet, 1979; Chrisman, 1987). These data models
were originally driven by technology. The reason for the grid cell was the simplicity
of programming, and the related raster pixel was determined by the simplicity of
hardware designs for remote sensing. Similarly, the vector approach reduced complex
graphics to tractable primitives.
The purpose of a spatial data structure is to provide a model of spatial knowledge
(Chrisman, 1978). The spatial data structure provides a basis upon which spatial
queries may be performed; these queries entail an examination of the encoded spatial
entities and their attributes and relationships (Tomlinson, 1978; Smith et al, 1987)3
.
Until recently, the development trends, along with their relevant data structures, were
often viewed as non-compatible approaches designed for different markets. But
current trends indicate a shift toward integrated decision-support systems and
operations management. The trend to decision-support systems, that is systems that
seek to assist a human manager by taking over the more structured parts of a larger
only partially formalizable problem domain, however, requires data to have far more
intelligence than for more conventional map and overlay applications (Lee, 1986;
Hayes-Roth et al, 1983; Williams, 1987; Williams, 1989). The sources for this
intelligence are those of data relationships and structure; and techniques and
procedures for manipulating and analyzing the data relationships. These
characteristics can be equated to the notions of geographic knowledge bases and
geographic knowledge rules; the former being concerned with the organizing and
structuring of geographic phenomena while the latter notion is concerned with
analyzing and interpreting aspects and relationships (or cognitive aspects) of the
geographic reality.
This paper concentrates on geographic knowledge bases and emphasizes that the
structure of geographic information from a phenomenological viewpoint is concerned
with finding out what things are.
KNOWLEDGE STRUCTURING
Nyerges (1980) and Moellering (1983) observe that “it is only relatively recently that
cartographers have come to realize that when one desires to work with cartographic
information in the digital domain that the cartographic representation is only one
fundamental aspect of map information. Many other kinds of relationships have been
recognized which are not necessarily graphic. Two distinct concepts of surface and
deep structure exist in the cartographic domain. Surface structure of cartographic
information is the graphic representation of the terminal elements which appear in the
3 A data model specifies the sets of components and the relationships among the components
pertaining to the specific phenomena defined by the data reality (phenomena that actually exists). A
data model is independent of specific systems or data structures that organize and manage the data. A
data structure specifies the logical organization of the components of a data model and the manner in
which relationships among components are to be explicitly defined.
4. 4
form of a map. However, there are many other explicit and implicit relationships
between cartographic objects contained in the data that are not graphic. Deep
structure relates to these relationships between cartographic objects that are not
necessarily graphic. The relationships can be phenomenological, spatial, in some
cases non-terminal graphic elements, or a combination of these. Such relationships are
not evident from the surface structure”. The notion deep structure is fundamental to
the creation of knowledge bases.
This paper expands on this idea of structuring the cartographic data to include the
broader domain of geographic data. However, before endeavoring to describe what
things are by using commonly used definitions of geography, cognitive views of
geographic information, analysis of the domain of geographic features, interpretation
of the domain, forms of representation and location, and sources of information, it is
appropriate to examine knowledge representation in general.
Knowledge representation
Several researchers have noted that artificial intelligence can play a role in the
development of advanced geographic information systems. If we view geographic
information in an application area for the use of artificial intelligence technology an
approaches, there are several sub-areas of artificial intelligence that may hold promise
such as knowledge representation and utilization, knowledge acquisition, and
computer vision. McKeown (1987) suggests “tasks where artificial intelligence
techniques may find utility include non-traditional representations of factual
information based on semantic networks of information”. McKeown notes that “meta-
knowledge about relationships of objects, normally reserved for application-specific
systems, should be more closely linked with the topological properties and attributes
of spatial objects and their relation to other spatial objects”.
Knowledge representation has long been a research issue in cartography with non-
traditional representations and meta-knowledge being considered important. Global
and local structures and multi-element characteristics have been discussed for more
than a decade.
Nyerges (1980) points out that “many researchers contend that global data structures
are impractical because large volumes of data are stored in main memory while
checking topological relationships. In contrast, local processing of data, concerned
only with sections of the model at any given time, proves to be beneficial because of
reduced processing time and storage needs. Unfortunately, a local network data
structure is not amenable to complex analytical operation at a global level. This
requires global relationship specification”. Nyerges further notes that “global network
data structures are more suited for data base operation, especially operations
undertaken in an interactive problem solving environment”, and indicates that Brassel
(1978) has proposed a global network data structure for multi-element map processing
in which the node is given the highest importance. These nodes (not necessarily
topological) signify locations for phenomenological important points.
Brassel (1978) illustrates desirable characteristics of multi-element map processing
systems by examining the process of information retrieval from a traditional map
feature via map reading. Brassel suggests that “in order to fully appreciate and
interpret a map feature, the map user relates the feature to other map elements in its
neighborhood and even to significant features at greater distances. Similarly, certain
5. 5
complex cartographic processes can only be performed in an appropriate manner if
the global and local information is available to the cartographer. For example, quality
hill-shading takes into consideration the local modulations of the terrain as well as the
global characteristics of the overall mountain range; contour line generalization can
only be satisfactorily performed in an appropriate manner if it is adjusted to the
generalization of the nearby drainage pattern, road network, etc.; name placement
requires adjustment to all map features in the neighborhood as well as some global
considerations. An important requirement of such a structure is therefore its ability to
provide for local links to other map elements as well as global references to
significant features at larger distances”. These characteristics demonstrate the
problem of translation and interpretation, or the hermeneutic problem. Hermeneutics
is a central problem of phenomenology. It is through an appreciation of the
hermeneutic that we best come to see the importance of phenomenology for
information system research.
Although the research by Brassel; is over a decade old and that by Nyerges is just less
than a decade old, the basic ideas are still current and still being speculated on, as in
Guptill’s (1989) ‘Speculation on seamless, scaleless cartographic data bases’, and
other researchers investigating micro and macro interpretations of data. However,
emphasis within the research community is still concerned with structuring and
organizing map elements. Now, if we extend these fundamental ideas to the real
world we first need to establish categories of features from the domain of geographic
features.
The domain of geographic features
Geography is concerned with the description of the earth’s surface, treating of its
forms and physical features, its natural and political divisions, climate, productions,
populations, etc. of the various countries (Haggett, 1972). Such descriptions are
applicable from large scale environments such as nations and regions down to cities
and spaces between buildings, to both built and natural environments, and to the
entire range of physical, social, cultural and economic aspects of man’s world (Moore
and Golledge, 1976). The representation of this description can be organized into a
domain of features and this domain categorized into a set of World Views. These
views should not be considered as authoritative or absolute but are suggested here as a
first attempt to organize the domain of geographic features. It should be noted that
phenomenology does not assert the existence of an absolute knowledge. The views
are administration/institution; population/habitation; road infrastructure; rail
infrastructure; air infrastructure; sea infrastructure; communication; power/fuel; water
resources; industry/commerce; health/medical; tourism/recreation/entertainment;
physiography; hydrography; oceanography; vegetation/cultivation; and meteorology
(Figure 1).
Features listed in the thematic views are not necessarily the total set of features in the
geographic domain. The listing is produced as a first attempt to categorize the domain
of geographic features into functional views or categories.
All of the information in the world views is interrelated in some way or another and
can be composed of regions, networks, complexes and features. The level of
integration, association and detail of representation is influenced by perception and
interpretation.
11. 11
Hermeneutic aspects of the domain
Hermeneutics is concerned with translation and interpretation. It is an appreciation of
translation and interpretation that highlights the importance of structure of
information (Boland, 1986). From a cartographic point of view, interpretation can be
broadly categorized into two concepts; a cognitive concept and a product concept.
The former corresponds to mental and dynamic interpretation of the domain of
geographic features and the second corresponds to formalized and symbolized
representation of the domain. This latter concept equates to map and product-oriented
applications.
A cognitive, or identifiable, concept. Humans are able to interpret and conceive
geographic information as identifiable concepts. Notions such as the Northern
Territory, the Top End and Darwin; all imbue meaning and signify some sort of
geographic region. The precise boundary of the region may, or may not, be well
defined; the interrelationships between different themes may, or may not, be
correlated; and the level of detail of the information within the themes may, or may
not, be similar. What is significant, however, is that with each of these identifiable
concepts there is generally a dominant theme. For example, the Northern Territory is
an administration region; the Top End a physiographic or tourist region; and Darwin a
populated place.
Figure 2 Identifiable concepts
12. 12
In addition to having a dominant theme, identifiable concepts may be conceived as
having one or more background themes. For example, one may conceive the Northern
Territory as having background information for ocean areas (delineated by its
characteristically shaped coastline), key centres of population, its major road network,
and major physiographic regions. The Top End, similarly, has an ocean area (the
same as the Northern Territory), the city of Darwin, the town of Katherine and other
important communities, the Stuart Highway, and Arnhem Land (a physiographic
region and aboriginal reserve).
Identifiable concepts have the following characteristics:
a. Recognition via a name or unique identifier;
b. Description and categorization including via the use of attributes and fuzzy
relationships;
c. Location via the use of a reference system;
d. Size and composition; and
e. Decomposition into other identifiable concepts.
The formalization and structure of these characteristics constitutes a meta-knowledge
of the identifiable concepts. Meta-knowledge implies more than just object-oriented
structures and simple relational aspects. Meta-knowledge also implies knowledge of
descriptions of dominant and background themes; forms of representation and
location; and statements of lineage and significance. But, before discussing these
properties in greater detail, it should be noted that traditional cartographic products
form logical and formalized concepts.
Product concepts. Maps, both reference and thematic, are commonly accepted forms
of representing geographic data. Interpretation is formalized within well-established
specifications and production methodologies. It should be observed that for limited
scale range and limited series range products, knowledge representation needs only to
be relatively simple. Computer-assisted mapping evolution has shown that unlinked
vector or simple grid cell structures seem to be adequate for these types of products.
In addition, the logical groupings of features are not overly critical and, in practice,
groupings are often influenced by symbolic representation.
However, due to various interpretations and applications by users, an extensive range
of map products are required. In order to satisfy the multi-product requirements,
knowledge representation has to be structured to facilitate macro and micro
interpretations; as is required by small scale and large scale maps. This implies that
data needs to be organized for several representations, and structures have to be found
that provide alternate representations of spatial objects (Bruegger and Frank, 1989).
Again, meta-knowledge which has an ability to apply appropriate data structures and
usage rules to functionally logical groups of features in an efficient way seems to be
an appropriate technique for cognitive, or identifiable, concepts.
Meta-knowledge
Meta-knowledge is a description of information about an identifiable concept. This
knowledge consists of identification and general description; locational description,
resolution, and geographic extent; role and functional descriptions; relationship within
higher level features; and directories of available theme oriented information. As an
example of probable components of meta-knowledge refer to Figure 3.
14. 14
Figure 3.2 Components of meta-knowledge
Meta-knowledge, as McKeown (1987) suggests is a “non-traditional representation of
factual information based on semantic networks of information” and notes that “meta-
knowledge is normally reserved for application specific systems”. This representation
is expandable into progressively lower levels of structure. Initially, cognitive concepts
and product concepts consist of interrelated information from the domain of themes;
each theme being an aggregation of objects.
These objects can be identified, represented, an assigned statements describing role,
dependency and lineage. The objects can in turn be decomposed into features. This
research proposes that objects and features within the themes are unique and
distinctive and require organization and structure to satisfy unique real world
qualities.
Object structures
The characteristics of commonly used data structures such as polygon, grid cell, quad
tree and triangulated irregular network are discussed extensively throughout the
literature. Not discussed previously, however, are a number of specialist structures
that are well suited to real world objects.
15. 15
One such structure takes the form of a graph. A graph is an arbitrary collection of
points called nodes and connections called arcs that go from one node to another. If
we think of the nodes as representing locations in search space, then we naturally
think of the arcs as connections from each location to its successors Arcs may be one
way or directed, two way or bidirectional or alternating (Raphael, 1976). A graph
structure is particularly suited to infrastructure networks, such as road, rail and air.
A special type of graph is a tree. A tree has a unique root, or top node, that has no
predecessors. Every other node of the tree has exactly one predecessor. Tree
structures are well suited to distributive systems such as sewerage drains, and water
resource channels.
Another tree structure worthy of consideration is the strip tree (Ballard, 1981). Strip
trees provide a powerful representation of curves. The representation defines strip
segments as primitives to cover subsets of a line. Organization of these segments into
a tree can be viewed as a particular case of a general strategy of dividing features up
and covering them with arbitrary shapes.
Further, some types of data do not conform adequately to the constraints posed by
geometric structures. Phenomena such as weather and magnetic field information are
possibly better modeled by using a surface fitting function. Additionally, because of
temporal variability these functions may be subject to periodic modification.
Object representation
All objects need to be represented in a geometric form and functionally related. There
are three fundamental forms for geometric representation: these being plan,
generalization and symbolization (Robinson et al, 1978).
Object relationship
Explicit relationships achieved through topologically structured data have been
addressed extensively in the literature. However, aspects of object relationship that
have received only scant attention concern dependency, and relative location.
Feature dependency. Feature dependency occurs via reliance on a higher-order
feature or as being a component of a higher-order feature. As an example of the
reliance on a higher-order feature, bridges, cuttings, and embankments cannot occur
naturally without a road (or railway line or similar type feature). An example of a
component of a higher-order feature would be when individual buildings occur within
a town or city boundary. In this latter example, the city inherits the buildings.
Similarly, an airport inherits (or is composed of) runways, taxiways, tarmacs,
terminals, and so on, Feature dependency implies that features may be primary or
subordinate.
Relative location. Apart from feature dependency another characteristic of real world
phenomena that has yet to be researched in detail concerns fuzzy locational properties.
Fuzzy location refers to those common usage terms such as around, is located near
to, is located south of, is located north-east of, is located to the right of, is located on
the shore of, is located at the mouth of, is located within, crosses the, underpasses,
lies on, and so on. In addition to the direction, magnitude is often expressed within
bands such as within a kilometer of, between 1 and 2 kilometres of greater than 1000
kilometres from, and so on.
16. 16
Figure 4 Quirindi Gorge – stereo image and fuzzy location
REPRESENTATION OF OBJECTS WITHIN THEMES
These notions of object structure, representation and relationship can be demonstrated
by analyzing a representative sample of the world view themes.
Administration / institution. Information within the administration / institution
theme is, in the main, polygonal and symbolic in nature. Administration, cadastral and
census boundaries are polygon in form, while facilities such government
administration buildings, schools, churches, cemeteries and so on are in plan form
17. 17
(and therefore simple polygons) or symbolic depending on the resolution used in its
definition.
Additionally, because of legal and administrative aspects, information within this
theme is characterized by hierarchical qualities. A country is composed of states,
federal planning areas, major census tracts and territorial claims. States are composed
of cities, municipalities and shires as well as conservation parks and census tracts.
Cities and municipalities are in turn composed of parishes, suburbs, etc, and, finally,
subdivisions are composed of parcels, sections and lots. It seems appropriate to
maintain this hierarchical representation, firstly because it is quite possible that
positional aspects of different components might well have been established
according to different standards of accuracy and registration, and secondly as a
techniques to manage the enormous amount of information in a structured way.
Further, information within this theme has relative location both within the theme as
well as to objects and features in other themes having similar relative importance. As
examples, a building or facility would lie within a tract or parcel of land; buildings are
related to electricity and water networks; and an administrative are may be contained
within a physiographic feature.
Road infrastructure. A road transportation network is a complex arrangement of
roads having different functional uses, such as freeways, highways, arterial roads,
distributive roads and local access roads; and different construction details such as
surface and width and associated related features. These related features include
bridges which, in turn, have attributes such as carrying capacity, overpasses and
underpasses, level crossings, cuttings and embankments. These characteristics of the
related features have an impact on the use of the network when the use of the network
concerns different vehicle types (Williams, 1988). Nyerges (1989) observes that
“transportation organizations usually have a broader and deeper perspective on
highway information that other organizations whose main interest is not with the
details of maintenance, management and monitoring of a highway”. Nyerges and
Deuker (1988) further comment that urban applications often differ from state or
federal applications. Because of detailed planning, management and engineering
problems, metropolitan planning organizations interact with local governments and
therefore data resolution, accuracy and detail should be commensurate with other
facility information.
Some extensions to a basic topological model are required above what has normally
been handled by GIS topological data structures. Transportation modelling requires a
non-planar graph to represent directed, non-directed and alternating flows on
networks, rather than a planar graph which is currently the norm. Non-planar graphs
can also support the representation of highway overpasses and underpasses.
Extensions to the basic topological model are also required to ‘embed’ networks of
roads representing the various administrative levels. These extensions are achieved by
the use of relationships for inter-level and intra-level connectivity (Figures 36 and 37;
Williams, 1985a; Williams, 1985b).
Sea infrastructure. Much information within the sea infrastructure theme has been
managed according to strict guidelines developed by hydrographic organizations.
Graphic information has traditionally been represented on conformal projections and
has emphasized approaches to ports and harbours and shipping lanes. Additional
18. 18
attribute information has been published in tide tables, instructional charts and
handbooks, radio and light publications, magnetic variation charts and meteorological
charts; these latter examples indicating relationships within physiographic and
meteorology themes.
In addition to the traditionally accepted information, sea infrastructure could also
include concepts as ports, maintenance facilities, navigable rivers, canals and beach
landing sites. Ports could be represented as enclosing polygons which consist of
features such as wharves, jetties, buildings and the like and linked to information in
themes such as rail infrastructure, power and fuel, etc. Inland waterways and canals
with dependent features such as locks and weirs are suited to graph structures.
Water resources. This theme, too, is a transitional theme, being related to all
infrastructure themes as well as hydrography, physiography and meteorology themes.
Features such as dams are polygonal whereas channels and pipelines are distributive
networks. These types of features have direct relationships to features in the
infrastructure themes.
The water resources theme also contains information about natural landforms and
other components of the hydrologic cycle including the atmosphere and sub-surface
structures. Hydrologic analysis emphasizes the physical structure of a watershed in
describing or predicting water and sediment yield. Land cover parameters are
valuable in these studies by inferring the basin characteristics that include drainage
density and type, stream length, sinuosity, and slope; and basin area, shape, width,
length, slope and aspect. Multispectral imagery, obtained from satellite sensors and
structured in a raster form, is useful in assessing and quantifying components within
the hydrologic cycle.
IDENTIFIABLE CONCEPTS AND WORLD VIEW CONFLICTS
Identifiable concepts have been characterized via recognition by using a name or
unique identifier, description and categorization as in the use of attributes and fuzzy
relationships, location using reference systems, and having size and composition.
World-view concepts, on the other hand, require that information be managed in a
more structured and regulated manner. This implies that area delimitation conflicts
will occur. As an example, the road infrastructure, in the real-world is managed by
governments and the government areas are aligned to state, city and shire
administrative units. The same situation, however, does not occur for objects in the
power and fuel and water resources themes in which facilities and networks are
managed by quasi-government corporations or privately-owned companies. The area
of influence for these objects is determined by the distribution of resources and
customers. This area conflict occurs between most themes with greatest
incompatibility occurring between cultural themes and natural themes, such as
physiography and meteorology.
The dilemma arises through a conflict in the use of data and is little different to the
long standing conflict posed by cartographers as to what they should show on their
maps, which, of course, gave rise to reference maps and thematic maps. This dilemma
has compounded in recent years due to the situation whereby the data gatherers are
also the data users.
19. 19
This problem can be alleviated by establishing archival or multi-purpose databases
or, as Nyerges and Dueker (1988) suggest, subject databases to organize and manage
data that is independent of any one application and application, project, product or
operational databases configured for specific specialist purposes. The subject
databases would contain the geographic information and knowledge structures for
theme-oriented features as discussed in this chapter. The operational and product
databases would contain knowledge of interrelationships between themes for
particular applications and groups of applications and would require knowledge rules
for their creation.
These two databases, in turn, can be modified and improved upon by the addition of
results from previous analyses. One such example might be as a result of determining
a route between two places on a network. If the analysis were likely to be used in the
future then the results might be recorded in an expertise database. Such a technique
would enable private knowledge to be formally managed thereby creating a learning
system (Figure 5).
Figure 5 A model based on phenomenology and cognition
20. 20
CONCLUSION
The approach taken in this paper has been to investigate the representation and
analysis of geographic information from phenomenological and cognitive viewpoints.
This approach implies that structural relationships have been investigated based on
their occurrence in the real world and the way in which features are managed and
processed in the real world. This approach differs from most other research which
essentially investigates geographic data based on cartographic representations of
features, thereby commencing with an abstraction and symbolic representation of
data.
Much research with respect to the analysis of geographic spatial data and cartography,
in recent times, has been reactive; that is, research has tended to follow applications
and low-level techniques and production methodologies. In fact, many of the existing
research papers often commence with discussion on low-level topology, and the like,
and tend to develop from that base. This paper, however, has accepted that theory and
considers such details as primitives, albeit mandatory primitives, and has taken the
conceptually opposite approach by attempting to describe information and processes
using high-level structures. Indeed, in concluding, the definition of cartography could
well be presented from a high-level viewpoint as:
Cartography4
(Figure 6) is the
representation and communication of geographic phenomena.
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NOTES
Figures 2, 4 and 6 have been added to the original paper to enhance description on
topics.
AWARD
AUSTRALIAN INSTITUTE OF CARTOGRAPHERS
CARCARTTOGRAPHICOGRAPHIC EXCELLENCEEXCELLENCE
AWARDAWARD
Category
GEOGRAPHIC INFORGEOGRAPHIC INFORMATION SYSTEMSMATION SYSTEMS
Awarded to
MAJOR BOB WILLIAMSMAJOR BOB WILLIAMS
1990