Raster Data in QGIS Matthew Rosencrans Tom DiLiberto.

Slides:



Advertisements
Similar presentations
Reconstruction from Voxels (GATE-540)
Advertisements

Spatial Analysis – vector data analysis
GIS Matthew Rosencrans Tom DiLiberto. Outline What is GIS? What can we do with it? What data can we work with?
University of Wisconsin-Milwaukee Geographic Information Science Geography 625 Intermediate Geographic Information Science Instructor: Changshan Wu Department.
WFM 6202: Remote Sensing and GIS in Water Management © Dr. Akm Saiful IslamDr. Akm Saiful Islam WFM 6202: Remote Sensing and GIS in Water Management Akm.
ANALYSIS 3 - RASTER What kinds of analysis can we do with GIS? 1.Measurements 2.Layer statistics 3.Queries 4.Buffering (vector); Proximity (raster) 5.Filtering.
Z – Surface Interpolation…. INTERPOLATION Procedure to predict values of attributes at unsampled points Why? Can’t measure all locations: Time Money Impossible.
Week 17GEOG2750 – Earth Observation and GIS of the Physical Environment1 Lecture 14 Interpolating environmental datasets Outline – creating surfaces from.
GIS Actors in Kepler - Java-based, GDAL-JNI, and C++(Grass) Routines Dan Higgins - UC Santa Barbara (NCEAS) Chad Berkley – UC Santa Barbara (NCEAS) Jianting.
Lecture 4. Interpolating environmental datasets
WILD 5750/6750 LAB 5 10/04/2010 IMAGE MOSAICKING.
More GeoProcessing Matthew Rosencrans Tom DiLiberto.
What Geoprocessing? Geoprocessing is the processing of geographic information. Commonly used to describe a process when geographic objects are manipulated.
ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, KEEP THIS TEXT BOX this slide includes some ESRI fonts. when you save this presentation,
GIS 2, Final Project: Creating a Dasymetric Map for Two Counties in Minnesota By: Hamidreza Zoraghein Melissa Cushing Caitlin Lee Fall 2013.
Geographic Information Systems Applications in Natural Resource Management Chapter 14 Raster GIS Database Analysis II Michael G. Wing & Pete Bettinger.
Slope and Aspect Calculated from a grid of elevations (a digital elevation model) Slope and aspect are calculated at each point in the grid, by comparing.
Basic Spatial Analysis
School of Geography FACULTY OF ENVIRONMENT Raster GIS.
Spatial Analyst Toolbox Lecture 17. Spatial Analyst Tool Sets  Conditional  Density  Distance  Generalization  Ground Water  Interpolation  Conditional.
ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, KEEP THIS TEXT BOX this slide includes some ESRI fonts. when you save this presentation,
Applied Cartography and Introduction to GIS GEOG 2017 EL
Using ESRI ArcGIS 9.3 Spatial Analyst
Interpolation.
Orthorectification using
GIS concepts, skills and tools
Spatial Analysis.
Intro. To GIS Lecture 9 Terrain Analysis April 24 th, 2013.
Interpolation Tools. Lesson 5 overview  Concepts  Sampling methods  Creating continuous surfaces  Interpolation  Density surfaces in GIS  Interpolators.
A.Batchimeg GDAL Geospatial Data Abstraction Library GDAL Geospatial Data Abstraction Library
GEOSTATISICAL ANALYSIS Course: Special Topics in Remote Sensing & GIS Mirza Muhammad Waqar Contact: EXT:2257.
Chapter 8 – Geographic Information Analysis O’Sullivan and Unwin “ Describing and Analyzing Fields” By: Scott Clobes.
Chernobyl Nuclear Power Plant Explosion
GIS Data Structures How do we represent the world in a GIS database?
Spatial Interpolation Chapter 13. Introduction Land surface in Chapter 13 Land surface in Chapter 13 Also a non-existing surface, but visualized as a.
CFR 250/590 Introduction to GIS, Autumn 1999 View Basics © Phil Hurvitz, intro.ppt 1 Overview Getting data into ArcView Displaying themes Theme.
Interpolation of Surfaces Spatial Data Analysis. Spatial Interpolation Spatial interpolation is the prediction of exact values of attributes at un-sampled.
Concepts and Applications of Kriging
NR 143 Study Overview: part 1 By Austin Troy University of Vermont Using GIS-- Introduction to GIS.
1 Overview Importing data from generic raster files Creating surfaces from point samples Mapping contours Calculating summary attributes for polygon features.
L7 - Raster Algorithms L7 – Raster Algorithms NGEN06(TEK230) – Algorithms in Geographical Information Systems.
Grid-based Map Analysis Techniques and Modeling Workshop
Central Region Snowfall Analysis Brian P. Walawender NWS Central Region Headquarters Matt W. Davis NWS WFO La Crosse, WI 5/26/2011.
Esri UC 2014 | Technical Workshop | Concepts and Applications of Kriging Eric Krause Konstantin Krivoruchko.
Statistical Surfaces Any geographic entity that can be thought of as containing a Z value for each X,Y location –topographic elevation being the most obvious.
L15 – Spatial Interpolation – Part 1 Chapter 12. INTERPOLATION Procedure to predict values of attributes at unsampled points Why? Can’t measure all locations:
U.S. Department of the Interior U.S. Geological Survey Automatic Generation of Parameter Inputs and Visualization of Model Outputs for AGNPS using GIS.
Spatial Analysis – vector data analysis Lecture 8 10/12/2006.
INTERPOLATION Procedure to predict values of attributes at unsampled points within the region sampled Why?Examples: -Can not measure all locations: - temperature.
Interpolation Local Interpolation Methods –IDW – Inverse Distance Weighting –Natural Neighbor –Spline – Radial Basis Functions –Kriging – Geostatistical.
Geospatial Data Abstraction Library(GDAL) Sabya Sachi.
Labs Put your name on your labs! Layouts: Site 1 Photos Title Legend
Chapter 8 Raster Analysis.
GIS Analysis Queries Operations Non-spatial Spatial Vector Raster
Spatial Models – Raster Stacy Bogan
An Integrated Approach for Subsidence Monitoring and Sinkhole Formation in the Karst Terrain of Dougherty County, Georgia Matthew Cahalan1 and Adam Milewski1.
URBDP 422 Urban and Regional Geo-Spatial Analysis
Lidar Image Processing
Spatial Analysis: Raster
Chapter 10 Problems Even problems are at end of text. 19. What is a kernel in a moving window operation? Does the kernel size or shape change for different.
Interpolation of Surfaces
Review- vector analyses
Interpolation - applications
Interpolation & Contour Maps
Spatial interpolation
Concepts and Applications of Kriging
Spatial Analysis: Raster
Interpolating Surfaces
Concepts and Applications of Kriging
Geostatistical Simulations – Preparing for Worst-Case Scenarios
Presentation transcript:

Raster Data in QGIS Matthew Rosencrans Tom DiLiberto

Outline What is Raster Data? Supported Formats What can one do with Raster Data?

Raster Data Raster Data = gridded data – NWP Model Output – Imagery – LDAS outputs – LIDAR/RADAR – Interpolated fields from point/line/polygon data

Raster Data QGIS uses GDAL libraries – GDAL = Geospatial Data Abstraction Library

Supported Formats ArcInfo Grid (ASCII or Binary) GeoTIFF/GeoPDF ERDAS IMAGINE/ ENVI GIF/JPG/PNG netCDF HDF4/5 NGSGEOID USGS DEM OGC formats Grib2

Raster Data What good is data without interpretation? Need to colorize/stylize/query

Symbologies Singleband Psuedocolors Multiband

Symbologies Pseudocolor – Scalar fields – Temperature – Precipitation – Satellite Index Choose colors Decide your thresholds Apply

Creating Raster Data Interpolation of point data – Multiple methods Inverse distance weighted (CPC) Natural Neighbor (used by CPC and USDA) Kriging – SAGA GIS - open source for making Gridded Data

Creating Raster Data Inverse distance weighted (CPC) – Power Value higher = emphasis on the nearest points, less smooth lower = emphasis on further points, smoother – Control number of points – Non physical

Creating Raster Data Natural Neighbor (used by CPC and USDA) – Voronoi (Thiessen) polygons constructed – Sample point, new Thiessen polygon constructed – Weight = proportion of overlap new/initial poly

Creating Raster Data Kriging – SAGA GIS – Some issues with software – Assumes distance or direction between sample points can be used to explain variation in the surface – forms weights from surrounding values to predict unmeasured locations

Raster Processing Clipping – GDAL Clip Raster By Extent. Instead of masking out ocean, or able to subset for country or province Extracting Point Sampling Extracting by value Resampling (helps to match resolution) Mathematical operations within and across rasters Raster Addition/subtraction Creating Totals, Climatologies, Anomalies Local Statistics (Zonal Statistics)

Raster Processing Clipping – GDAL Clip Raster By Extent.

Raster Processing Resampling (helps to match resolution)

Raster Processing Extracting Point Sampling –QGIS Plugin or SAGA tool Extracting by value

Raster Processing Mathematical operations within and across rasters Raster Addition/subtraction Creating Totals, Climatologies, Anomalies Covered in Day 3 Local Statistics (Zonal Statistics)

Raster Processing Lab Work will cover Symbolizing Rasters Querying rasters Clipping Raster Calculator Calculations Interpolations Querying rasters at points