EAT 233/3 GEOGRAPHIC INFORMATION SYSTEM (GIS)

Size: px
Start display at page:

Download "EAT 233/3 GEOGRAPHIC INFORMATION SYSTEM (GIS)"

Transcription

1 EAT 233/3 GEOGRAPHIC INFORMATION SYSTEM (GIS) CO3: Ability to produce detail mapping using geographic information systems (GIS) BY : AYU WAZIRA AZHARI

2 SPATIAL DATA & THE MODELLING

3 Spatial Data in GIS Spatial data in GIS has two primary data formats (the arrangement of data for storage or display): i.raster Generalizes the scene O OO O into a grid cells, each 1 OO2 1 1 with a code to indicate O1 the feature being depicted ii.vector Has polygons that appear normal, much like map OO 2 O O OO O 1

4 Raster & Vector Data Models In both (raster & vector) models, the spatial information is represented using finite, discrete homogeneous units. In the raster model, the homogeneous units are grid cells (or pixels). In the vector model, the homogeneous units are points, lines and polygons.

5 Figure 1: Raster: Grid cells ; Vector: Points, lines, polygons

6 Raster Data Model Vector Data Model Raster data model uses an array of cells, or pixels, to represent real-world objects. Because the raster cell s value or code represents all of the features within the grid, it does not maintain true size, shape, or location for individual features. Even where nothing exists (no data), the cells must be coded. Most GIS themes depict only the necessary features in area; showing everything on the landscape would be confusing. By definition, vectors are data elements describing position and direction. In GIS, vector is the map-like drawing of features, without the generalizing effect of a raster grid. The lines are analog, which means they are not broken into cells or fragments, but continue from start to finish in a continuous manner. Therefore, shape is better retained, much like an actual map.

7 Figure 2: Real world scene of raster and vector models

8 Raster Coding In the raster world a range of different methods is used to encode a spatial entity for storage and representation in the computer. Figure 3 shows the most straightforward method of coding raster data.

9 Figure 3: Feature coding of cells in the raster world

10 Resolution The minimum linear dimension of the smallest unit of geographical space for which data are recorded. In the raster model, the smallest units are rectangular (for most systems). The smallest units are known as cells or pixels. The array of cells is known as lattice, grid or matrix. High resolution refers to raster with small cells.

11 Gridding A higher density of cells in a raster system usually implies more accurate measurements. The size of the raster cells is therefore important. Figure 4 shows the effects of grid size than can create spatial inaccuracies.

12 Figure 4

13 Vector Data Based on vectors The fundamental primitive is points. Objects are created by connecting points with straight lines (or arcs). Areas are defined by sets of lines.

14 Figure 5: Vector

15 Raster & Vector Structures Raster and vector structures have different methods of storing and displaying spatial data. Figure 6 shows the difference between raster and vector data structure

16 Figure 6: The difference between raster and vector data structure

17 Comparision between Raster & Vector RASTER VECTOR Advantages: Advantages: 1. It is a simple data structure. 2. The simple grid structure makes analysis easier. 3. Because of the relative simplicity of raster formats, the computer platform can be low tech and inexpensive. 4. Remote sensing imagery is typically obtained in raster format easily integrated into a raster format GIS because of the identical data formats 1. The geographic data is more accurate and credible than the raster format. 2. Vector data is very high resolution. 3. The high resolution supports high spatial accuracy. 4. Vector formats have storage advantages. 5. The general public usually understands what is shown on vector maps. 6. Vector data can be topological. Disadvantages: 1. Spatial inaccuracies are common with raster systems. 2. Because each cell tends to generalize a landscape, the result is relatively low resolution compared to the vector format. 3. Because of spatial inaccuracies caused by data generalization, a raster format cannot tell precisely what exists at a given location. 4. Each cell must have a code, even where nothing exists. That is, even NO DATA must be coded, usually 0 value. Disadvantages: 1. It is a more complex data structure than a simple raster. 2. Vector formats require more powerful, hightech machines. 3. The use of better computers, increased management needs, and other considerations often make the vector format more expensive. 4. Learning the technical aspects of vector systems is more difficult than understanding the raster format, particularly when topology is introduced.

Spatial Data Models. Raster uses individual cells in a matrix, or grid, format to represent real world entities

Spatial Data Models. Raster uses individual cells in a matrix, or grid, format to represent real world entities Spatial Data Models Raster uses individual cells in a matrix, or grid, format to represent real world entities Vector uses coordinates to store the shape of spatial data objects David Tenenbaum GEOG 7

More information

17/07/2013 RASTER DATA STRUCTURE GIS LECTURE 4 GIS DATA MODELS AND STRUCTURES RASTER DATA MODEL& STRUCTURE TIN- TRIANGULAR IRREGULAR NETWORK

17/07/2013 RASTER DATA STRUCTURE GIS LECTURE 4 GIS DATA MODELS AND STRUCTURES RASTER DATA MODEL& STRUCTURE TIN- TRIANGULAR IRREGULAR NETWORK RASTER DATA STRUCTURE GIS LECTURE 4 GIS DATA MODELS AND STRUCTURES Space is subdivided into regular grids of square grid cells or other forms of polygonal meshes known as picture elements (pixels) the

More information

4.0 DIGITIZATION, EDITING AND STRUCTURING OF MAP DATA

4.0 DIGITIZATION, EDITING AND STRUCTURING OF MAP DATA .0 DIGITIZATION, EDITING AND STRUCTURING OF MAP DATA The process of digitizing existing maps is a transformation from one analog) form of information to another digital) form. Data input is the operation

More information

Review of Cartographic Data Types and Data Models

Review of Cartographic Data Types and Data Models Review of Cartographic Data Types and Data Models GIS Data Models Raster Versus Vector in GIS Analysis Fundamental element used to represent spatial features: Raster: pixel or grid cell. Vector: x,y coordinate

More information

SPATIAL DATA MODELS Introduction to GIS Winter 2015

SPATIAL DATA MODELS Introduction to GIS Winter 2015 SPATIAL DATA MODELS Introduction to GIS Winter 2015 GIS Data Organization The basics Data can be organized in a variety of ways Spatial location, content (attributes), frequency of use Come up with a system

More information

GIS Data Models. 4/9/ GIS Data Models

GIS Data Models. 4/9/ GIS Data Models GIS Data Models 1 Conceptual models of the real world The real world can be described using two conceptually different models: 1. As discrete objects, possible to represent as points, lines or polygons.

More information

layers in a raster model

layers in a raster model layers in a raster model Layer 1 Layer 2 layers in an vector-based model (1) Layer 2 Layer 1 layers in an vector-based model (2) raster versus vector data model Raster model Vector model Simple data structure

More information

DATA MODELS IN GIS. Prachi Misra Sahoo I.A.S.R.I., New Delhi

DATA MODELS IN GIS. Prachi Misra Sahoo I.A.S.R.I., New Delhi DATA MODELS IN GIS Prachi Misra Sahoo I.A.S.R.I., New Delhi -110012 1. Introduction GIS depicts the real world through models involving geometry, attributes, relations, and data quality. Here the realization

More information

Cell based GIS. Introduction to rasters

Cell based GIS. Introduction to rasters Week 9 Cell based GIS Introduction to rasters topics of the week Spatial Problems Modeling Raster basics Application functions Analysis environment, the mask Application functions Spatial Analyst in ArcGIS

More information

Data Models and Data processing in GIS

Data Models and Data processing in GIS PDHonline Course L155G (5 PDH) Data Models and Data processing in GIS Instructor: Steve Ramroop, Ph.D. 2012 PDH Online PDH Center 5272 Meadow Estates Drive Fairfax, VA 22030-6658 Phone & Fax: 703-988-0088

More information

Introduction to Geographic Information Science. Some Updates. Last Lecture 4/6/2017. Geography 4103 / Raster Data and Tesselations.

Introduction to Geographic Information Science. Some Updates. Last Lecture 4/6/2017. Geography 4103 / Raster Data and Tesselations. Geography 43 / 3 Introduction to Geographic Information Science Raster Data and Tesselations Schedule Some Updates Last Lecture We finished DBMS and learned about storage of data in complex databases Relational

More information

LECTURE 2 SPATIAL DATA MODELS

LECTURE 2 SPATIAL DATA MODELS LECTURE 2 SPATIAL DATA MODELS Computers and GIS cannot directly be applied to the real world: a data gathering step comes first. Digital computers operate in numbers and characters held internally as binary

More information

Figure 1: Workflow of object-based classification

Figure 1: Workflow of object-based classification Technical Specifications Object Analyst Object Analyst is an add-on package for Geomatica that provides tools for segmentation, classification, and feature extraction. Object Analyst includes an all-in-one

More information

Graphic Display of Vector Object

Graphic Display of Vector Object What is GIS? GIS stands for Geographic Information Systems, although the term Geographic Information Science is gaining popularity. A GIS is a software platform for storing, organizing, viewing, querying,

More information

Representing Geography

Representing Geography Data models and axioms Chapters 3 and 7 Representing Geography Road map Representing the real world Conceptual models: objects vs fields Implementation models: vector vs raster Vector topological model

More information

Accuracy, Support, and Interoperability. Michael F. Goodchild University of California Santa Barbara

Accuracy, Support, and Interoperability. Michael F. Goodchild University of California Santa Barbara Accuracy, Support, and Interoperability Michael F. Goodchild University of California Santa Barbara The traditional view Every object has a true position and set of attributes with enough time and resources

More information

Topic 5: Raster and Vector Data Models

Topic 5: Raster and Vector Data Models Geography 38/42:286 GIS 1 Topic 5: Raster and Vector Data Models Chapters 3 & 4: Chang (Chapter 4: DeMers) 1 The Nature of Geographic Data Most features or phenomena occur as either: discrete entities

More information

Geographic Information Systems. using QGIS

Geographic Information Systems. using QGIS Geographic Information Systems using QGIS 1 - INTRODUCTION Generalities A GIS (Geographic Information System) consists of: -Computer hardware -Computer software - Digital Data Generalities GIS softwares

More information

Keywords: vectorization, satellite images, interpolation, Spline, zooming

Keywords: vectorization, satellite images, interpolation, Spline, zooming Volume 6, Issue 10, October 2016 ISSN: 2277 128X International Journal of Advanced Research in Computer Science and Software Engineering Research Paper Available online at: www.ijarcsse.com Vectorization

More information

Introduction :- Storage of GIS Database :- What is tiling?

Introduction :- Storage of GIS Database :- What is tiling? Introduction :- GIS storage and editing subsystems provides a variety of tools for storing and maintaining the digital representation of a study area. It also provide tools for examining each theme for

More information

Understanding Geospatial Data Models

Understanding Geospatial Data Models Understanding Geospatial Data Models 1 A geospatial data model is a formal means of representing spatially referenced information. It is a simplified view of physical entities and a conceptualization of

More information

Measure the Perimeter of Polygons Over a Surface. Operations. What Do I Need?

Measure the Perimeter of Polygons Over a Surface. Operations. What Do I Need? Measure the Perimeter of Polygons Over a Surface Operations What Do I Need? Incremental Frontage Score To measure the perimeter of polygons over a surface you need to have two input map layers. The first

More information

Raster GIS. Raster GIS 11/1/2015. The early years of GIS involved much debate on raster versus vector - advantages and disadvantages

Raster GIS. Raster GIS 11/1/2015. The early years of GIS involved much debate on raster versus vector - advantages and disadvantages Raster GIS Google Earth image (raster) with roads overlain (vector) Raster GIS The early years of GIS involved much debate on raster versus vector - advantages and disadvantages 1 Feb 21, 2010 MODIS satellite

More information

Introduction to Geographic Information Systems Dr. Arun K Saraf Department of Earth Sciences Indian Institute of Technology, Roorkee

Introduction to Geographic Information Systems Dr. Arun K Saraf Department of Earth Sciences Indian Institute of Technology, Roorkee Introduction to Geographic Information Systems Dr. Arun K Saraf Department of Earth Sciences Indian Institute of Technology, Roorkee Lecture 04 Raster data model and comparisons with vector Hello friends,

More information

Class #2. Data Models: maps as models of reality, geographical and attribute measurement & vector and raster (and other) data structures

Class #2. Data Models: maps as models of reality, geographical and attribute measurement & vector and raster (and other) data structures Class #2 Data Models: maps as models of reality, geographical and attribute measurement & vector and raster (and other) data structures Role of a Data Model Levels of Data Model Abstraction GIS as Digital

More information

Terms and definitions * keep definitions of processes and terms that may be useful for tests, assignments

Terms and definitions * keep definitions of processes and terms that may be useful for tests, assignments Lecture 1 Core of GIS Thematic layers Terms and definitions * keep definitions of processes and terms that may be useful for tests, assignments Lecture 2 What is GIS? Info: value added data Data to solve

More information

Lab.4 & Assignment 2. Lab4. Conversion of Hardcopy Map to ArcGIS Map

Lab.4 & Assignment 2. Lab4. Conversion of Hardcopy Map to ArcGIS Map EATS4400 GIS Lab.4 & Assignment 2 Lab4 Conversion of Hardcopy Map to ArcGIS Map In this lab exercise you will have chance to go through the steps to convert hardcopy map into digital map for ArcGIS. Digitizing

More information

Metadata or "data about data" describe the content, quality, condition, and other characteristics of data. The Federal Geographic Data Committee

Metadata or data about data describe the content, quality, condition, and other characteristics of data. The Federal Geographic Data Committee Metadata or "data about data" describe the content, quality, condition, and other characteristics of data. The Federal Geographic Data Committee (http://www.fgdc.gov/) approved the Content Standard for

More information

Metadata or "data about data" describe the content, quality, condition, and other characteristics of data. The Federal Geographic Data Committee

Metadata or data about data describe the content, quality, condition, and other characteristics of data. The Federal Geographic Data Committee Metadata or "data about data" describe the content, quality, condition, and other characteristics of data. The Federal Geographic Data Committee (http://www.fgdc.gov/) approved the Content Standard for

More information

v Importing Rasters SMS 11.2 Tutorial Requirements Raster Module Map Module Mesh Module Time minutes Prerequisites Overview Tutorial

v Importing Rasters SMS 11.2 Tutorial Requirements Raster Module Map Module Mesh Module Time minutes Prerequisites Overview Tutorial v. 11.2 SMS 11.2 Tutorial Objectives This tutorial teaches how to import a Raster, view elevations at individual points, change display options for multiple views of the data, show the 2D profile plots,

More information

Longley Chapter 3. Representations

Longley Chapter 3. Representations Longley Chapter 3 Digital Geographic Data Representation Geographic Data Type Data Models Representing Spatial and Temporal Data Attributes The Nature of Geographic Data Representations Are needed to convey

More information

Line Generalisation Algorithms Specific Theory

Line Generalisation Algorithms Specific Theory Line Generalisation Algorithms Specific Theory Digital Generalisation Digital generalisation can be defined as the process of deriving, from a data source, a symbolically or digitally-encoded cartographic

More information

Purpose: To explore the raster grid and vector map element concepts in GIS.

Purpose: To explore the raster grid and vector map element concepts in GIS. GIS INTRODUCTION TO RASTER GRIDS AND VECTOR MAP ELEMENTS c:wou:nssi:vecrasex.wpd Purpose: To explore the raster grid and vector map element concepts in GIS. PART A. RASTER GRID NETWORKS Task A- Examine

More information

Output Primitives. Dr. S.M. Malaek. Assistant: M. Younesi

Output Primitives. Dr. S.M. Malaek. Assistant: M. Younesi Output Primitives Dr. S.M. Malaek Assistant: M. Younesi Output Primitives Output Primitives: Basic geometric structures (points, straight line segment, circles and other conic sections, quadric surfaces,

More information

Startup. Why are you here? What are your experiences? What are your major working/research topics? What do you want to learn?

Startup. Why are you here? What are your experiences? What are your major working/research topics? What do you want to learn? Startup Why are you here? What are your experiences? What are your major working/research topics? What do you want to learn? Introduction to Geographic information systems Description of a GIS GIS is a

More information

Lecture 06. Raster and Vector Data Models. Part (1) Common Data Models. Raster. Vector. Points. Points. ( x,y ) Area. Area Line.

Lecture 06. Raster and Vector Data Models. Part (1) Common Data Models. Raster. Vector. Points. Points. ( x,y ) Area. Area Line. Lecture 06 Raster and Vector Data Models Part (1) 1 Common Data Models Vector Raster Y Points Points ( x,y ) Line Area Line Area 2 X 1 3 Raster uses a grid cell structure Vector is more like a drawn map

More information

Points and lines. x x 1 + y 1. y = mx + b

Points and lines. x x 1 + y 1. y = mx + b Points and lines Point is the fundamental element of the picture representation. It is nothing but the position in a plan defined as either pairs or triplets of number depending on whether the data are

More information

CS4620/5620: Lecture 14 Pipeline

CS4620/5620: Lecture 14 Pipeline CS4620/5620: Lecture 14 Pipeline 1 Rasterizing triangles Summary 1! evaluation of linear functions on pixel grid 2! functions defined by parameter values at vertices 3! using extra parameters to determine

More information

Lecture notes: Object modeling

Lecture notes: Object modeling Lecture notes: Object modeling One of the classic problems in computer vision is to construct a model of an object from an image of the object. An object model has the following general principles: Compact

More information

GIS DATA MODELS AND SPATIAL DATA STRUCTURE

GIS DATA MODELS AND SPATIAL DATA STRUCTURE UNIT 5 GIS DATA MODELS AND SPATIAL DATA STRUCTURE GIS Data Models and Spatial Data 5.1 Introduction Objectives 5.2 GIS Data Models Raster Data Models Vector Data Models Comparison of Raster and Vector

More information

Lecture 6: GIS Spatial Analysis. GE 118: INTRODUCTION TO GIS Engr. Meriam M. Santillan Caraga State University

Lecture 6: GIS Spatial Analysis. GE 118: INTRODUCTION TO GIS Engr. Meriam M. Santillan Caraga State University Lecture 6: GIS Spatial Analysis GE 118: INTRODUCTION TO GIS Engr. Meriam M. Santillan Caraga State University 1 Spatial Data It can be most simply defined as information that describes the distribution

More information

Ray Tracing Acceleration Data Structures

Ray Tracing Acceleration Data Structures Ray Tracing Acceleration Data Structures Sumair Ahmed October 29, 2009 Ray Tracing is very time-consuming because of the ray-object intersection calculations. With the brute force method, each ray has

More information

Watershed Sciences 4930 & 6920 GEOGRAPHIC INFORMATION SYSTEMS

Watershed Sciences 4930 & 6920 GEOGRAPHIC INFORMATION SYSTEMS HOUSEKEEPING Watershed Sciences 4930 & 6920 GEOGRAPHIC INFORMATION SYSTEMS Quizzes Lab 8? WEEK EIGHT Lecture INTERPOLATION & SPATIAL ESTIMATION Joe Wheaton READING FOR TODAY WHAT CAN WE COLLECT AT POINTS?

More information

Culling. Computer Graphics CSE 167 Lecture 12

Culling. Computer Graphics CSE 167 Lecture 12 Culling Computer Graphics CSE 167 Lecture 12 CSE 167: Computer graphics Culling Definition: selecting from a large quantity In computer graphics: selecting primitives (or batches of primitives) that are

More information

Object modeling and geodatabases. GEOG 419: Advanced GIS

Object modeling and geodatabases. GEOG 419: Advanced GIS Object modeling and geodatabases GEOG 419: Advanced GIS CAD Data Model 1960s and 1970s Geographic data stored as points, lines, and areas No attributes; each feature type stored on a different layer No

More information

Using ArcGIS for Landcover Classification. Presented by CORE GIS May 8, 2012

Using ArcGIS for Landcover Classification. Presented by CORE GIS May 8, 2012 Using ArcGIS for Landcover Classification Presented by CORE GIS May 8, 2012 How to use ArcGIS for Image Classification 1. Find and download the right data 2. Have a look at the data (true color/false color)

More information

Introduction to Computer Graphics

Introduction to Computer Graphics Introduction to 1.1 What is computer graphics? it would be difficult to overstate the importance of computer and communication technologies in our lives. Activities as wide-ranging as film making, publishing,

More information

Spatial data and QGIS

Spatial data and QGIS Spatial data and QGIS Xue Jingbo IT Center 2017.08.07 A GIS consists of: Spatial Data. Computer Hardware. Computer Software. Longitude Latitude Disease Date 26.870436-31.909519 Mumps 13/12/2008 26.868682-31.909259

More information

Multidimensional Data and Modelling

Multidimensional Data and Modelling Multidimensional Data and Modelling 1 Problems of multidimensional data structures l multidimensional (md-data or spatial) data and their implementation of operations between objects (spatial data practically

More information

GEOGRAPHIC INFORMATION SYSTEMS Lecture 02: Feature Types and Data Models

GEOGRAPHIC INFORMATION SYSTEMS Lecture 02: Feature Types and Data Models GEOGRAPHIC INFORMATION SYSTEMS Lecture 02: Feature Types and Data Models Feature Types and Data Models How Does a GIS Work? - a GIS operates on the premise that all of the features in the real world can

More information

Maps as Numbers: Data Models

Maps as Numbers: Data Models Maps as Numbers: Data Models vertices E Reality S E S arcs S E Conceptual Models nodes E Logical Models S Start node E End node S Physical Models 1 The Task An accurate, registered, digital map that can

More information

The GIS Spatial Data Model

The GIS Spatial Data Model The GIS Spatial Data Model Introduction: Spatial data are what drive a GIS. Every piece of functionality that makes a GIS separate from another analytical environment is rooted in the spatially explicit

More information

Triangle Rasterization

Triangle Rasterization Triangle Rasterization Computer Graphics COMP 770 (236) Spring 2007 Instructor: Brandon Lloyd 2/07/07 1 From last time Lines and planes Culling View frustum culling Back-face culling Occlusion culling

More information

Parallel Rendering. Johns Hopkins Department of Computer Science Course : Rendering Techniques, Professor: Jonathan Cohen

Parallel Rendering. Johns Hopkins Department of Computer Science Course : Rendering Techniques, Professor: Jonathan Cohen Parallel Rendering Molnar, Cox, Ellsworth, and Fuchs. A Sorting Classification of Parallel Rendering. IEEE Computer Graphics and Applications. July, 1994. Why Parallelism Applications need: High frame

More information

Texture Analysis. Selim Aksoy Department of Computer Engineering Bilkent University

Texture Analysis. Selim Aksoy Department of Computer Engineering Bilkent University Texture Analysis Selim Aksoy Department of Computer Engineering Bilkent University saksoy@cs.bilkent.edu.tr Texture An important approach to image description is to quantify its texture content. Texture

More information

Welcome to NR402 GIS Applications in Natural Resources. This course consists of 9 lessons, including Power point presentations, demonstrations,

Welcome to NR402 GIS Applications in Natural Resources. This course consists of 9 lessons, including Power point presentations, demonstrations, Welcome to NR402 GIS Applications in Natural Resources. This course consists of 9 lessons, including Power point presentations, demonstrations, readings, and hands on GIS lab exercises. Following the last

More information

GRID BASED CLUSTERING

GRID BASED CLUSTERING Cluster Analysis Grid Based Clustering STING CLIQUE 1 GRID BASED CLUSTERING Uses a grid data structure Quantizes space into a finite number of cells that form a grid structure Several interesting methods

More information

Thoughts on Representing Spatial Objects. William A. Huber Quantitative Decisions Rosemont, PA

Thoughts on Representing Spatial Objects. William A. Huber Quantitative Decisions Rosemont, PA Thoughts on Representing Spatial Objects William A. Huber Quantitative Decisions Rosemont, PA Overview 1. Some Ways to Structure Space 2. What to Put into a Grid 3. Objects and Fields 4. Hybrid Structures

More information

Computer Database Structure for Managing Data :-

Computer Database Structure for Managing Data :- The Map as an Abstraction of Space :- We begin the process of abstraction by conceptualizing what we encounter as a group of points, lines, areas and surfaces. We make decision about which object to take

More information

Geographic Surfaces. David Tenenbaum EEOS 383 UMass Boston

Geographic Surfaces. David Tenenbaum EEOS 383 UMass Boston Geographic Surfaces Up to this point, we have talked about spatial data models that operate in two dimensions How about the rd dimension? Surface the continuous variation in space of a third dimension

More information

Introducing ArcScan for ArcGIS

Introducing ArcScan for ArcGIS Introducing ArcScan for ArcGIS An ESRI White Paper August 2003 ESRI 380 New York St., Redlands, CA 92373-8100, USA TEL 909-793-2853 FAX 909-793-5953 E-MAIL info@esri.com WEB www.esri.com Copyright 2003

More information

GOVERNMENT GAZETTE REPUBLIC OF NAMIBIA

GOVERNMENT GAZETTE REPUBLIC OF NAMIBIA GOVERNMENT GAZETTE OF THE REPUBLIC OF NAMIBIA N$7.20 WINDHOEK - 7 October 2016 No. 6145 CONTENTS Page GENERAL NOTICE No. 406 Namibia Statistics Agency: Data quality standard for the purchase, capture,

More information

GEOGRAPHIC INFORMATION SYSTEMS Lecture 25: 3D Analyst

GEOGRAPHIC INFORMATION SYSTEMS Lecture 25: 3D Analyst GEOGRAPHIC INFORMATION SYSTEMS Lecture 25: 3D Analyst 3D Analyst - 3D Analyst is an ArcGIS extension designed to work with TIN data (triangulated irregular network) - many of the tools in 3D Analyst also

More information

Parallel Method for Dasymetric Mapping. Sam Zhang

Parallel Method for Dasymetric Mapping. Sam Zhang Parallel Method for Dasymetric Mapping Sam Zhang Overview Dasymetric mapping is a commonlyapplied algorithm in GIS that can determine the population distribution in a high resolution level. It maps the

More information

Data Representation in Visualisation

Data Representation in Visualisation Data Representation in Visualisation Visualisation Lecture 4 Taku Komura Institute for Perception, Action & Behaviour School of Informatics Taku Komura Data Representation 1 Data Representation We have

More information

(Refer Slide Time 00:17) Welcome to the course on Digital Image Processing. (Refer Slide Time 00:22)

(Refer Slide Time 00:17) Welcome to the course on Digital Image Processing. (Refer Slide Time 00:22) Digital Image Processing Prof. P. K. Biswas Department of Electronics and Electrical Communications Engineering Indian Institute of Technology, Kharagpur Module Number 01 Lecture Number 02 Application

More information

GIS in agriculture scale farm level - used in agricultural applications - managing crop yields, monitoring crop rotation techniques, and estimate

GIS in agriculture scale farm level - used in agricultural applications - managing crop yields, monitoring crop rotation techniques, and estimate Types of Input GIS in agriculture scale farm level - used in agricultural applications - managing crop yields, monitoring crop rotation techniques, and estimate soil loss from individual farms or agricultural

More information

Geographic Information Fundamentals Overview

Geographic Information Fundamentals Overview CEN TC 287 Date: 1998-07 CR 287002:1998 CEN TC 287 Secretariat: AFNOR Geographic Information Fundamentals Overview Geoinformation Übersicht Information géographique Vue d'ensemble ICS: Descriptors: Document

More information

GEOSPATIAL ENGINEERING COMPETENCIES. Geographic Information Science

GEOSPATIAL ENGINEERING COMPETENCIES. Geographic Information Science GEOSPATIAL ENGINEERING COMPETENCIES Geographic Information Science The character and structure of spatial information, its methods of capture, organisation, classification, qualification, analysis, management,

More information

v SMS Tutorials Working with Rasters Prerequisites Requirements Time Objectives

v SMS Tutorials Working with Rasters Prerequisites Requirements Time Objectives v. 12.2 SMS 12.2 Tutorial Objectives Learn how to import a Raster, view elevations at individual points, change display options for multiple views of the data, show the 2D profile plots, and interpolate

More information

Computer Graphics Shadow Algorithms

Computer Graphics Shadow Algorithms Computer Graphics Shadow Algorithms Computer Graphics Computer Science Department University of Freiburg WS 11 Outline introduction projection shadows shadow maps shadow volumes conclusion Motivation shadows

More information

Geodatabase over Taita Hills, Kenya

Geodatabase over Taita Hills, Kenya Geodatabase over Taita Hills, Kenya Anna Broberg & Antero Keskinen Abstract This article introduces the basics of geographical information systems (GIS) and explains how the Taita Hills project can benefit

More information

Map Library ArcView Version 1 02/20/03 Page 1 of 12. ArcView GIS

Map Library ArcView Version 1 02/20/03 Page 1 of 12. ArcView GIS Map Library ArcView Version 1 02/20/03 Page 1 of 12 1. Introduction 1 ArcView GIS ArcView is the most popular desktop GIS analysis and map presentation software package.. With ArcView GIS you can create

More information

Algorithms for GIS csci3225

Algorithms for GIS csci3225 Algorithms for GIS csci3225 Laura Toma Bowdoin College Spatial data types and models Spatial data in GIS satellite imagery planar maps surfaces networks point cloud (LiDAR) Spatial data in GIS satellite

More information

ACGV 2008, Lecture 1 Tuesday January 22, 2008

ACGV 2008, Lecture 1 Tuesday January 22, 2008 Advanced Computer Graphics and Visualization Spring 2008 Ch 1: Introduction Ch 4: The Visualization Pipeline Ch 5: Basic Data Representation Organization, Spring 2008 Stefan Seipel Filip Malmberg Mats

More information

Using ArcGIS 10.x Introductory Guide University of Toronto Mississauga Library Hazel McCallion Academic Learning Centre

Using ArcGIS 10.x Introductory Guide University of Toronto Mississauga Library Hazel McCallion Academic Learning Centre Using ArcGIS 10.x Introductory Guide University of Toronto Mississauga Library Hazel McCallion Academic Learning Centre FURTHER ASSISTANCE If you have questions or need assistance, please contact: Andrew

More information

Introduction to Object Oriented Analysis and Design

Introduction to Object Oriented Analysis and Design A class note on Introduction to Object Oriented Analysis and Design Definition In general, analysis emphasizes an investigation of the problem and requirements of the domain, rather than a solution. Whereas,

More information

3D graphics, raster and colors CS312 Fall 2010

3D graphics, raster and colors CS312 Fall 2010 Computer Graphics 3D graphics, raster and colors CS312 Fall 2010 Shift in CG Application Markets 1989-2000 2000 1989 3D Graphics Object description 3D graphics model Visualization 2D projection that simulates

More information

RASTER ANALYSIS S H A W N L. P E N M A N E A R T H D A T A A N A LY S I S C E N T E R U N I V E R S I T Y O F N E W M E X I C O

RASTER ANALYSIS S H A W N L. P E N M A N E A R T H D A T A A N A LY S I S C E N T E R U N I V E R S I T Y O F N E W M E X I C O RASTER ANALYSIS S H A W N L. P E N M A N E A R T H D A T A A N A LY S I S C E N T E R U N I V E R S I T Y O F N E W M E X I C O TOPICS COVERED Spatial Analyst basics Raster / Vector conversion Raster data

More information

Rasterization. COMP 575/770 Spring 2013

Rasterization. COMP 575/770 Spring 2013 Rasterization COMP 575/770 Spring 2013 The Rasterization Pipeline you are here APPLICATION COMMAND STREAM 3D transformations; shading VERTEX PROCESSING TRANSFORMED GEOMETRY conversion of primitives to

More information

Computer Graphics Introduction. Taku Komura

Computer Graphics Introduction. Taku Komura Computer Graphics Introduction Taku Komura What s this course all about? We will cover Graphics programming and algorithms Graphics data structures Applied geometry, modeling and rendering Not covering

More information

UNIT - V DHARANI KUMAR.S/AP/MECH

UNIT - V DHARANI KUMAR.S/AP/MECH UNIT - V DHARANI KUMAR.S/AP/MECH CAD Standards are a set of guidelines for the way Computer-aided design (CAD) drawings should appear, to improve productivity and interchange of CAD documents between different

More information

Chapter 3: Maps as Numbers

Chapter 3: Maps as Numbers Chapter 3: Maps as Numbers 3. Representing Maps as Numbers 3.2 Structuring Attributes 3.3 Structuring Maps 3.4 Why Topology Matters 3.5 Formats for GIS Data 3.6 Exchanging Data David Tenenbaum EEOS 265

More information

CSE 167: Introduction to Computer Graphics Lecture #9: Visibility. Jürgen P. Schulze, Ph.D. University of California, San Diego Fall Quarter 2018

CSE 167: Introduction to Computer Graphics Lecture #9: Visibility. Jürgen P. Schulze, Ph.D. University of California, San Diego Fall Quarter 2018 CSE 167: Introduction to Computer Graphics Lecture #9: Visibility Jürgen P. Schulze, Ph.D. University of California, San Diego Fall Quarter 2018 Announcements Midterm Scores are on TritonEd Exams to be

More information

Analysis of Change in Polygon Distribution

Analysis of Change in Polygon Distribution Analysis of Change in Polygon Distribution t 1 t 2 These instructions enable you to analyze the change in polygon distribution between two time periods using ArcGIS 8.1 (ArcInfo licensed) software. The

More information

Raster model. Raster model. Resolution. Value and data types. Structure and storage. Cell. Values. Data

Raster model. Raster model. Resolution. Value and data types. Structure and storage. Cell. Values. Data Raster model. Resolution. Values and data types 3. Storage. Fitting rasters 5. Map algebra 6. Interpolation 7. Conversion vectorraster 8. Vector vs. raster Raster model Divides the space into a regular

More information

Spatial Analysis (Vector) II

Spatial Analysis (Vector) II Spatial Analysis (Vector) II GEOG 300, Lecture 9 Dr. Anthony Jjumba 1 A Spatial Network is a set of geographic locations interconnected in a system by a number of routes is a system of linear features

More information

Introduction to GIS. Geographic Information Systems SOCR-377 9/24/2015. R. Khosla Fall Semester The real world. What in the world is GIS?

Introduction to GIS. Geographic Information Systems SOCR-377 9/24/2015. R. Khosla Fall Semester The real world. What in the world is GIS? Introduction to GIS Geographic Information Systems SOCR-377 What in the world is GIS? GIS is simultaneously the telescope, the microscope, the computer and the Xerox machine of regional analysis and synthesis

More information

Algorithms for GIS. Spatial data: Models and representation (part I) Laura Toma. Bowdoin College

Algorithms for GIS. Spatial data: Models and representation (part I) Laura Toma. Bowdoin College Algorithms for GIS Spatial data: Models and representation (part I) Laura Toma Bowdoin College Outline Spatial data in GIS applications Point data Networks Terrains Planar maps and meshes Data structures

More information

Representing the Real World

Representing the Real World Representing the Real World The theory of representing the real world in a GIS using digital data The nature of digital data and binary notation The discrete object view of the world Entities, data objects,

More information

ENGRG Introduction to GIS

ENGRG Introduction to GIS ENGRG 59910 Introduction to GIS Michael Piasecki April 3, 2014 Lecture 11: Raster Analysis GIS Related? 4/3/2014 ENGRG 59910 Intro to GIS 2 1 Why we use Raster GIS In our previous discussion of data models,

More information

Representing Graphical Data

Representing Graphical Data Representing Graphical Data Chapman & Chapman, chapters 3,4,5 Richardson 1 Graphics in IT82 What does computer graphics cover? IT82 Input, output, and representation of graphical data Creation of graphics

More information

Hidden surface removal. Computer Graphics

Hidden surface removal. Computer Graphics Lecture Hidden Surface Removal and Rasterization Taku Komura Hidden surface removal Drawing polygonal faces on screen consumes CPU cycles Illumination We cannot see every surface in scene We don t want

More information

VALLIAMMAI ENGINEERING COLLEGE

VALLIAMMAI ENGINEERING COLLEGE VALLIAMMAI ENGINEERING COLLEGE SRM Nagar, Kattankulathur 603 203 DEPARTMENT OF MECHANICAL ENGINEERING QUESTION BANK M.E: CAD/CAM I SEMESTER ED5151 COMPUTER APPLICATIONS IN DESIGN Regulation 2017 Academic

More information

Graphics Pipeline 2D Geometric Transformations

Graphics Pipeline 2D Geometric Transformations Graphics Pipeline 2D Geometric Transformations CS 4620 Lecture 8 1 Plane projection in drawing Albrecht Dürer 2 Plane projection in drawing source unknown 3 Rasterizing triangles Summary 1 evaluation of

More information

MRR (Multi Resolution Raster) Revolutionizing Raster

MRR (Multi Resolution Raster) Revolutionizing Raster MRR (Multi Resolution Raster) Revolutionizing Raster Praveen Gupta Praveen.Gupta@pb.com Pitney Bowes, Noida, India T +91 120 4026000 M +91 9810 659 350 Pitney Bowes, pitneybowes.com/in 5 th Floor, Tower

More information

GPS/GIS Activities Summary

GPS/GIS Activities Summary GPS/GIS Activities Summary Group activities Outdoor activities Use of GPS receivers Use of computers Calculations Relevant to robotics Relevant to agriculture 1. Information technologies in agriculture

More information

Graphics in IT82. Representing Graphical Data. Graphics in IT82. Lectures Overview. Representing Graphical Data. Logical / Physical Representation

Graphics in IT82. Representing Graphical Data. Graphics in IT82. Lectures Overview. Representing Graphical Data. Logical / Physical Representation Graphics in IT82 What does computer graphics cover? Representing Graphical Data Chapman & Chapman, chapters 3,4,5 Richardson IT82 Input, output, and representation of graphical data Creation of graphics

More information

Torsional-lateral buckling large displacement analysis with a simple beam using Abaqus 6.10

Torsional-lateral buckling large displacement analysis with a simple beam using Abaqus 6.10 Torsional-lateral buckling large displacement analysis with a simple beam using Abaqus 6.10 This document contains an Abaqus tutorial for performing a buckling analysis using the finite element program

More information

Vectorization Using Stochastic Local Search

Vectorization Using Stochastic Local Search Vectorization Using Stochastic Local Search Byron Knoll CPSC303, University of British Columbia March 29, 2009 Abstract: Stochastic local search can be used for the process of vectorization. In this project,

More information