GUS: 0265 Fundamentals of GIS Lecture Presentation 4: Raster Data Model and Operations Jeremy Mennis Department of Geography and Urban Studies Temple University.

Slides:

Advertisements

Similar presentations

Desktop, Mobile & Web Based GIS/ Collaborative GIS

Advertisements

GUS: 0262 Fundamentals of GIS

GIS Operations and Spatial Analysis Turns raw data into useful information by adding greater informative content and value Reveals patterns, trends, and.

School of Environmental Sciences University of East Anglia

Cartographic and GIS Data Structures

Lecture 04: Data Storage and Representation & Access to Spatial Data Geography 128 Analytical and Computer Cartography Spring 2007 Department of Geography.

Department of Geography University of Portsmouth Fundamentals of GIS: What is GIS? Dr. Ian Gregory, Department of Geography, University of Portsmouth.

Lecture by Austin Troy © 2005 Lecture 13: Introduction to Raster Spatial Analysis Using GIS-- Introduction to GIS Lecture Notes by Austin Troy, University.

What is Where? Lecture 5 Introduction to GISs Geography 176A Department of Geography, UCSB Summer 06, Session B.

Introduction to Geographic Information Systems Miles Logsdon

Introduction to Geographic Information Systems Miles Logsdon

Maps as Numbers Lecture 3 Introduction to GISs Geography 176A Department of Geography, UCSB Summer 06, Session B.

Map Analysis with Raster Datasets Francisco Olivera, Ph.D., P.E. Department of Civil Engineering Texas A&M University.

Geographic Information Systems : Data Types, Sources and the ArcView Program.

1 Spatial Databases as Models of Reality Geog 495: GIS database design Reading: NCGIA CC ’90 Unit #10.

Week 18GEOG2750 – Earth Observation and GIS of the Physical Environment1 Lecture 15 Principles of Grid-based modelling Outline – introduction – linking.

GEOG5060 GIS & Environment Lecture 4 GEOG GIS and Environment1 Lecture 4. Grid-based modelling Outline – introduction – linking models to GIS – basics.

Dr. David Liu Objectives  Understand what a GIS is  Understand how a GIS functions  Spatial data representation  GIS application.

GI Systems and Science January 23, Points to Cover  What is spatial data modeling?  Entity definition  Topology  Spatial data models Raster.

GIS Functions and Operators The functions associated with raster cartographic modeling can be divided into five types: The functions associated with raster.

Cartographic modelling

Data Quality Data quality Related terms:

Prepared by Abzamiyeva Laura Candidate of the department of KKGU named after Al-Farabi Kizilorda, Kazakstan 2012.

Geographic Information Systems (GIS) Data Marcel Fortin Geographic Information Systems (GIS) and Map Librarian Map and Data Library December 7, 2009.

Raster Data Analysis Chapter 11. Introduction  Regular grid  Value in each cell corresponds to characteristic  Operations on individual, group, or.

Fundamentals of GIS Lecture Materials by Austin Troy except where noted © 2008 Lecture 13: Introduction to Raster Spatial Analysis Using GIS-- By.

©2005 Austin Troy. All rights reserved Lecture 3: Introduction to GIS Understanding Spatial Data Structures by Austin Troy, Leslie Morrissey, & Ernie Buford,

GIS2: Geo-processing and Metadata Treg Christopher.

MSc in Geoinformatics – Managing Energy, Resources, Environment Teacher Training Dushanbe, – TEMPUS This project has.

Applied Cartography and Introduction to GIS GEOG 2017 EL

Coordinate Systems Global Coordinate System – Latitude, Longitude and elevation UTM – eastings and northings, reference points are the equator and the.

GUS: 0262 Fundamentals of GIS Lecture Presentation 6: Raster Data Model Jeremy Mennis Department of Geography and Urban Studies Temple University.

Faculty of Applied Engineering and Urban Planning Civil Engineering Department Geographic Information Systems Vector and Raster Data Models Lecture 3 Week.

Spatial Analysis.

CHAPTER 12 RASTER DATA ANALYSIS 12.1 Data Analysis Environment

Chapter 3 Digital Representation of Geographic Data.

Raster Data Model.

GUS: 0262 Fundamentals of GIS Lecture Presentation 3: Relational Data Model Jeremy Mennis Department of Geography and Urban Studies Temple University.

Introduction to Raster Spatial Analysis Using GIS-- Introduction to GIS Raster Query Map Calculation Zonal statistics Terrain functions Viewshed.

URBDP 422 Urban and Regional Geo-Spatial Analysis Lecture 2: Spatial Data Models and Structures Lab Exercise 2: Topology January 9, 2014.

Intro to Raster GIS GTECH361 Lecture 11. CELL ROW COLUMN.

GUS: 0262 Fundamentals of GIS Lecture Presentation 8: Data Input and Editing Jeremy Mennis Department of Geography and Urban Studies Temple University.

Spatial & Terrain Analysis Nigel Trodd Coventry University in 3D.

1 ANALYZING TIME SERIES OF SATELLITE IMAGERY USING TEMPORAL MAP ALGEBRA Jeremy Mennis 1 and Roland Viger 1,2 1 Dept. of Geography, University of Colorado.

Fundamentals of GIS Lecture Materials by Austin Troy except where noted © 2008 Lecture 13: Introduction to Raster Spatial Analysis Using GIS-- By.

GIS Data Models Vector Data Models Vector File Formats Raster Data Models Raster File Formats.

ISPRS Congress 2000 Multidimensional Representation of Geographic Features E. Lynn Usery Research Geographer U.S. Geological Survey.

Raster data models Rasters can be different types of tesselations SquaresTrianglesHexagons Regular tesselations.

Raster Analysis. Learning Objectives Develop an understanding of the principles underlying lab 4 Introduce raster operations and functions Show how raster.

URBPD 442 Urban and regional geospatial analysis This course provides theoretical and practical skills for analyzing spatial patterns and phenomena in.

NR 143 Study Overview: part 1 By Austin Troy University of Vermont Using GIS-- Introduction to GIS.

GUS: 0262 Fundamentals of GIS Lecture Presentation 7: Raster Operations Jeremy Mennis Department of Geography and Urban Studies Temple University.

CFR 250/590 Introduction to GIS, Autumn 1999 Raster Analysis I © Phil Hurvitz, raster1.ppt 1  Overview Grid themes Setting grid theme and analysis.

Spatial Analysis with Raster Datasets-1 Francisco Olivera, Ph.D., P.E. Srikanth Koka Department of Civil Engineering Texas A&M University.

What is GIS? “A powerful set of tools for collecting, storing, retrieving, transforming and displaying spatial data”

Raster Data Models: Data Compression Why? –Save disk space by reducing information content –Methods Run-length codes Raster chain codes Block codes Quadtrees.

Introduction to GIS All materials by Austin Troy © 2003, except where noted Lecture 8: Site Selection and Suitability Analysis and Criterion- based mapping.

Geog 495 Final Exam Review 11/23/05 Final exam on 11/28/05 Mon.

Storage Media Traditionally, the paper map has performed a storage function for spatial information Computer cartography requires information to be digital.

Geographical Information Systems

GEOGRAPHICAL INFORMATION SYSTEM

Raster Analysis Ming-Chun Lee.

URBDP 422 Urban and Regional Geo-Spatial Analysis

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.

Statistical surfaces: DEM’s

Lecture 6 Implementing Spatial Analysis

Data Queries Raster & Vector Data Models

Review- vector analyses

5. Zonal Analysis 5.1 Definition of a zone 5.2 Zonal statistics

Spatial Analysis with Raster Datasets-1

Presentation transcript:

GUS: 0265 Fundamentals of GIS Lecture Presentation 4: Raster Data Model and Operations Jeremy Mennis Department of Geography and Urban Studies Temple University

A raster representation is composed a series of layers, each with a theme Typically used to represent ‘field- like’ geographic phenomena Raster Data Model

Raster Resolution The distance that one side of a grid cell represents on the ground = grid cell resolution The higher the resolution (smaller the grid cell), the higher the precision, but the greater the cost in data storage

Raster Data: ArcGIS

Data Compression Common Methods: –run length encoding –value point encoding –chain codes –block codes –quadtrees

Run Length Encoding and Value Point Encoding

Map Algebra and Cartographic Modeling A raster modeling language, and an approach to GIS analysis design, developed by J.K. Berry and C. Dana Tomlin in the late 1970s - early 1980s. It now forms the basis for grid-based analysis in ArcInfo (GRID and Spatial Analyst) and other GIS packages.

Map Algebra A set of formally defined manipulations on raster data. Operators: Fundamental mathematical and logical operations on raster data Functions: Complex combinations of operations

Functions: Types Higher order data manipulations on raster grids built from the more basic operators. Local: compute on single-cell basis Focal: compute on a neighborhood Zonal: use zones derived from a separate grid for evaluation Block: like zonal, but the result is assigned to an entire ‘block’ of cells Global: compute on the entire grid

Functions: Local – Single Values

Functions: Local - Mean

Functions: Focal – Immediate Neighborhood

Functions: Focal – Majority Min Mean

Functions: Zonal – Entire Zones

Functions: Zonal - Max

Functions: Global - Distance

Program Control: Statements and Programs Statement: notation to represent operations and functions e.g. NEWLAYER = LocalFUNCTION of FIRSTLAYER and SECONDLAYER Program: notation to represent a procedure; i.e. a sequence of statements in which each statement operates on the result of a previous statement

Program Control: Programs

Cartographic Modeling in ArcInfo: ModelBuilder Locating Suitable Sites for a Waste Dump

Cartographic Modeling in ArcInfo: ModelBuilder