GIS Data Models. 4/9/ GIS Data Models

Similar documents
LECTURE 2 SPATIAL DATA MODELS

Representing Geography

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

Maps as Numbers: Data Models

GEOGRAPHIC INFORMATION SYSTEMS Lecture 02: Feature Types and Data Models

Representing the Real World

Lecture 2: GIS Data Sources, Data Types and Representation. GE 118: INTRODUCTION TO GIS Engr. Meriam M. Santillan Caraga State University

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

EAT 233/3 GEOGRAPHIC INFORMATION SYSTEM (GIS)

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

SVY2001: Databases for 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?

Longley Chapter 3. Representations

Topic 5: Raster and Vector Data Models

Understanding Geospatial Data Models

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

Maps as Numbers: Data Models

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

Geodatabase over Taita Hills, Kenya

The GIS Spatial Data Model

layers in a raster model

Suitability Modeling with GIS

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

GIS DATA MODELS AND SPATIAL DATA STRUCTURE

Attribute Accuracy. Quantitative accuracy refers to the level of bias in estimating the values assigned such as estimated values of ph in a soil map.

Contents of Lecture. Surface (Terrain) Data Models. Terrain Surface Representation. Sampling in Surface Model DEM

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

Review of Cartographic Data Types and Data Models

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

Cell based GIS. Introduction to rasters

Data Models and Data processing in GIS

9. GIS Data Collection

M. Andrea Rodríguez-Tastets. I Semester 2008

Building Vector Layers

Making Topographic Maps

Computational Geometry

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

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

Spatial data and QGIS

Introducing ArcScan for ArcGIS

GIS Workshop Spring 2016

Coverage data model. Vector-Based Spatial Analysis: Tools Processes. Topological Data Model. Polygons Files. Geographic Information Systems.

GIS and Forest Engineering Applications

Outline. 14. Query, Measurement, and Transformation. Spatial analysis. Definitions. The Snow map. What is spatial analysis?

CPSC 695. Methods for interpolation and analysis of continuing surfaces in GIS Dr. M. Gavrilova

Lecturer 2: Spatial Concepts and Data Models

Geographic Surfaces. David Tenenbaum EEOS 383 UMass Boston

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

Spatial Analysis (Vector) II

Chapter 9. Geographic Representation Models. Emmanuel Stefanakis

RASTER ANALYSIS GIS Analysis Fall 2013

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

Advanced Data Types and New Applications

Geoinformation in Environmental Modelling

NRM435 Spring 2017 Accuracy Assessment of GIS Data

Geographic Information Systems Notes For OC 3902/ OC 2902 Dr. James R. Clynch, 2002

RASTER ANALYSIS GIS Analysis Winter 2016

L1-Spatial Concepts L1 - Spatial Concepts

Module 7 Raster operations

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

Mapping Distance and Density

Advanced Data Types and New Applications

Raster Data. James Frew ESM 263 Winter

Geographic Information Systems (GIS) Spatial Analyst [10] Dr. Mohammad N. Almasri. [10] Spring 2018 GIS Dr. Mohammad N. Almasri Spatial Analyst

THE TOOLS OF AUTOMATED GENERALIZATION AND BUILDING GENERALIZATION IN AN ArcGIS ENVIRONMENT

GEOGRAPHIC INFORMATION SYSTEMS Lecture 17: Geoprocessing and Spatial Analysis

LSGI 521: Principles of GIS. Lecture 5: Spatial Data Management in GIS. Dr. Bo Wu

PART 1. Answers module 6: 'Transformations'

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

GIS Workbook #1. GIS Basics and the ArcGIS Environment. Helen Goodchild

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

Unit 3: Proximity Analysis and Buffering. Lecture Outline

Lecture 20 - Chapter 8 (Raster Analysis, part1)

Lecture 8. Vector Data Analyses. Tomislav Sapic GIS Technologist Faculty of Natural Resources Management Lakehead University

Module 10 Data-action models

SPATIAL DATA MODELS Introduction to GIS Winter 2015

2 Data Models. Introduction

Alaska Department of Transportation Roads to Resources Project LiDAR & Imagery Quality Assurance Report Juneau Access South Corridor

GIS Tools - Geometry. A GIS stores data as different layers of information Different feature types are stored in individual files.

Use of open-source GIS for the preprocessing of distributed hydrological. models

Georeferencing & Spatial Adjustment

CPSC 695. Data Quality Issues M. L. Gavrilova

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

INCREASING CLASSIFICATION QUALITY BY USING FUZZY LOGIC

Overview.! Manual Digitizing! Heads-up Digitizing! Common Errors! Summary! Heads-up Digitizing Tutorial

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

Data handling 3: Alter Process

Computer Database Structure for Managing Data :-

Suitability Analysis in Raster GIS. Combining Multiple Maps

An Introduction to Dynamic Simulation Modeling

FUZZY DIJKSTRA ALGORITHM FOR SHORTEST PATH PROBLEM IN GEOGRAPHIC INFORMATION SYSTEMS

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

Unit 4: Vector Overlay Analysis. Lecture Outline. Possible background reading material: McHarg, Ian 1992 Design with Nature. Wiley and Sons, New York.

GEOGRAPHIC INFORMATION SYSTEMS Lecture 18: Spatial Modeling

What can we represent as a Surface?

Prime2 Data Re-engineering timelines

Georeferencing & Spatial Adjustment 2/13/2018

GIS IN ECOLOGY: CREATING RESEARCH MAPS

Bharath Setturu Research scholar, EWRG, Center for Ecological Sciences, IISc, Bangalore & EWRG-CES IIIT-HYDERABAD

Principles of Data Management. Lecture #14 (Spatial Data Management)

Transcription:

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. 2. As a continuous surface with no discrete or distinct borders, like temperature and precipitation. To map houses and roads in an area, discrete objects are more suitable to use since these have a defined spatial extent, but to make a topographic map, a continuous surface should be used since topography has a continuous spatial variation.

Data models in GIS At the end of the lecture you are expected to know: -How GIS data is stored in: Vector data model Raster data model Examples of vector and raster data files 3

What is a Data Model? Data models in GIS A way of representing digital geographic data A set of constructs for describing and representing selected aspects of the real world in a computer (Longley, Goodchild, Maguire & Rhind (2005)) Two basic types of spatial data models have evolved for storing geographic data 1. Raster 2. Vector 4

6

Source: Heywood et al ( 2006 )

Vector data model A Vector data model is an object based representation of the real world, Geographic objects are shown as discrete objects They are separated from each other by defined borderlines. 8

Homework The vector data models can be further sub-divided into spaghetti and topological models. Compare and contrast these 2 types of vector data models. 9

Raster data model 10

This lecture will give you an introduction about the raster data structure, which is particularly useful for handling continuous (data) surfaces, but often used also for other types of data. In a raster database, the data is stored in cells in a matrix and this is a very important difference from the vector data structure that has been discussed in the previous lecture. 11

Raster data model A raster model is a field based representation of the real world. It shows geographic data as continuous surfaces It shows gradual changes in topography with no distinct boarder lines for geographic objects. 12

Raster data model store data in cells in a matrix (Raster) Treats geographic space as populated by one or more spatial phenomenon, which vary continuously over space having no distinct boundaries. They are best used to represent geographic features that are continuous over large areas e.g. soil type and vegetation Each cell in a raster is defined by a coordinate location and an attribute that identifies the feature. 13

14

Data models in GIS When representing geographic phenomena as raster, a raster/matrix/grid with a fixed cell size is placed over the area, and each raster cell is coded with a code representing the feature in that particular area. In this case, cells covering areas of the river are coded as R, cells covering pine forest are coded P, cells covering Spruce forest are coded S and the cell covering the house is coded H. 15

16

17

In this example, a piece of land contains 3 classes (objects): lake, town and forest. To convert this landscape to a raster data structure a grid (matrix) is overlaid on the landscape and the classes are given a unique code (identifier), in this case lake=1, town=2 and forest=3. Each cell in the matrix represents a certain area in the real world, depending on the size of the cell. 19

One may ask what happens if there is more than one geometrical object found within the same cell?. One solution is to take to dominant area within a cell. In this example, the forest covers a bigger area than the other classes so the cell could be coded as forest. Another method is to code the cell with the class found at the center of the cell. In this example, the cell would now be coded as lake. As you can see in the example, the result may differ considerably depending on which coding method that is selected. 20

When creating a raster database, the first step is to decide the resolution of the grid (the size of the cells). Normally, the cells are squares with equal X and Y resolutions. All cells must be given a value (so if there is nothing to represent in the raster, the value zero can be given for example). Raster data therefore requires a lot of storing space in your computer because the raster structure does not allow for empty cells E.g the zero cells in the diagram contain no useful information, but still this has to be stored. 21

22

23

24

A very important problem with the raster data structure is that it does not permit the user to know anything about what happens inside a cell. The cell is the smallest unit in the database and anything that is smaller than the cell will not show in the database. If point data is stored as raster structure data it is not possible to know exactly where the points were situated within the cells. To increase the precision, the cell size should be reduced (but more cells = more data = more storage space in your computer! There is always a tradeoff between resolution and memory. 25

Information about the exact location of linear objects is lost in a similar way when translating to raster data. In this example, both the red and the black line networks will be represented in exactly the same manor using the raster data structure despite the fact that they are very different to each other in reality. 26

The same problem occurs with polygons The longer the border a polygon has, the bigger will the difference between the area as measured in the raster data structure and the true area be. 27

4/9/2017 Source: Heywood 3. GIS Data et Models al ( 2006 ) 28

29

Homework Give examples of geographic features that can be represented using: -Vector data model -Raster data model Compare the raster and vector data models 30