The Idiots Guide to GIS and Remote Sensing
|
|
- Clyde West
- 7 years ago
- Views:
Transcription
1 The Idiots Guide to GIS and Remote Sensing 1. Picking the right imagery 1 2. Accessing imagery 1 3. Processing steps 1 a. Geocorrection 2 b. Processing Landsat images layerstacking 4 4. Landcover classification 6 a. Unsupervised 6 b. Supervised 8 c. Accuracy assessment Overlaying GPS points (ArcGIS) 11 Important references The ERDAS field guide gives lots of good info on processes in ERDAS and background: Ormsby et al. Getting to know ArcGIS 2 nd ed. Michael DeMers. GIS for Dummies. Congalton R. G A Review of Assessing the Accuracy of Classification of Remotely Sensed Data. Remote Sensing of the Environment 37: Daniel Friess : Postdoc Research Fellow : Biological Sciences/Civil Engineering : dan.friess@nus.edu.sg :
2 1. Picking the right imagery There are lots of different imagery sources from a wide number of sensors, both air- and spaceborne. How to choose? Temporal scale cannot use a modern sensor if you want historical imagery. Also, different sensors have different resolutions of data collection (one a day vs. once a year) Spatial scale different sensors have different areal coverage per single image. Pixel size no point in using imagery with a pixel size of 30 metres if the process of interest occurs at a 2 metre scale... Band selection what features are you trying to look for? Sensors are panchromatic (black and white), multispectral (different spectral bands e.g. visible, infrared, thermal) and hyperspectral (100 s of bands). Looking at terrestrial vegetation requires a different bandset from calculating sediment concentration in coastal waters. 2. Accessing imagery Free (or mostly free) Global Land Cover Facility, University of Maryland - ASTER, IKONOS, Quickbird, Landsat, MODIS, Orbview - United States Geological Survey - Landsat, ASTER, MODIS - Commercial CRISP, National University of Singapore SPOT, IKONOS, others Digital Globe - Worldview 1 & 2 panchromatic v. high resolution - DES Mapping solutions - Quickbird Processing steps To make accurate models or measurements from images, you have to ensure your imagery is accurate and contains no artifacts. E.g. if you are doing spectral statistics you have to make sure your bands have no spectral noise, and each flight strip has the same spectral calibration (radiometric correction). But that s quite technical; the most common processing steps you might need to do are a) geocorrection, and b) layerstacking. 1
3 a) Geocorrection This step is really important if you are taking measurements from the image then you have to be confident that your image is correct and not stretched or distorted. This is a big problem with trying to display a sphere (the Earth) as a flat image (your data). This is the main ERDAS Imagine toolbar: 1. Open the image you want to correct to e.g. line data or correctly geocorrected image 2. Open uncorrected image 3. On uncorrected image Raster Geometric Correction 4. For flat landscapes choose polynomial 5. Polynomial Model Properties appears. Click on Add/Change Projection and choose your projection. Map units should be in metres. 6. On geocorrection tools click on Start GCP Editor (the target symbol). 2
4 You will be asked where to collect the reference points from: click existing viewer and OK, and then click into the reference image. Click OK a few times (approximate statistics window). 7. Several screens will appear, with the uncorrected image on the left, the reference image on the right, and the GCP tool at the bottom. Make sure this is selected to choose a point 8. Select a point in the left image and the corresponding point in the reference image (e.g. building corner, ditch intersection, creek junction). To select a point the target symbol must be selected. 9. Make sure your first 3 points are spread out as far as possible in a triangle arrangement (not a line). After 3 points the model will predict the other points you choose. 10. If the predicted points are matching where they should be, or the RMS value is below your threshold then enough GCPs have been taken. 11. Click on Display Resample Image Dialog This one! On the following dialog choose an output file name and location and press OK 12. Once the process has run open the file in a new viewer. If needed, go file new AOI layer to draw an AOI to mask the photograph frame and save in the same location. 13. Repeat for the remaining images. 3
5 b) Processing Landsat images - layerstacking Landsat images are often distributed as Geotiff files (with separate Geotiff files for each band). A Geotiff is like a standard.tiff image file but has geographical information (coordinates) embedded. Each spectral band may be given to you as a separate Geotiff, so you ll need to get them overlaid into one master file before analysis. To import and amalgamate into a single image in ERDAS Imagine: 1. CHECK ALL THE BANDS. Open them individually are any blurry or covered in specks? You may want to discard bands with excessive noise. Also think about what bands you need if you re doing vegetation analysis you probably don t need the thermal bands, but you would if you were looking at soils. 2. Go to Import from the main ERDAS Imagine toolbar. Select Import, Type: Geotiff, Media: File, then select the Geotiff for band 1. Enter a file name in the output file (*.img). Click OK and then OK again on Import Tiff window. 3. Repeat this process for each of the other bands. 4
6 4. On the main ERDAS toolbar, go to the Interpreter/Utilities/Layer Stack module to combine your individual *.img files into a single multilayer *.img file. From the Layer Selection and Stacking dialog box, select your first band, then click the Add button to add it to the list of files that you want to combine into a single multilayer.img file. Then select the second input file and click the Add button again to add to your list of input.img files. Continue this process for all bands that you want to add. 5. After adding all the layers, specify an output filename and click OK. After this is finished, you can go to a Viewer window and open the image. Go to Utilities/Layer Information. You will note that, since this was imported from Geotiff files, there is complete map projection information. Go to Edit-Change Layer Name to give each layer a more descriptive name (e.g. something like TM_Band1, instead of the default name of simply Layer 1 ). This renaming is particularly important if you have imported only the non-thermal bands. In this case, the default layer names are potentially confusing (e.g., Layer 6 is really TM Band 7). 5
7 4. Landcover classification It can be very hard to tell different landcover types/vegetation communities/species from a truecolour image. However these classes all have different spectral signatures as they absorb and reflect different wavelengths. Below describes the processes used to classify land cover; the ERDAS Imagine field guide has lots of information on the principles, algorithms etc. a) Unsupervised This is a completely automated process where the system separates classes by distinct spectral differences. It has no user input, so requires no knowledge of what is actually on the ground. It is a fast process so good for classifying large areas over multiple images. 1. ERDAS main toolbar classifier unsupervised classification 2. Enter the input Raster file (e.g. the layerstacked Landsat image), output Raster and output signature file. The signature file is the description of your classes. 3. Under clustering options, the number of classes is really important. This should be representative of your scene. What is reasonable? How many classes do you expect? E.g. Urban_buildings + urban_roads + agriculture1 + agriculture2 + forest_species1 + forest_species2 + forest_mixed + cleared_forest + open_water = 9 potential classes. 6
8 4. Click OK and run the process. 5. Open output file in a new viewer The above is an example of a mangrove forest with cleared areas, new regrowth and an urban area. The process was run with 11 classes, but they should be more separability within the mangrove (brown/grey class, see arrow). In which case we can run again with more classes. 6. Also open the signature file produced, main toolbar classifier signature editor then open file. Under the view and evaluate menus you can see all sorts of statistics to show the separability of each class (e.g. contingency matrix). 7
9 b) Supervised classification This is a semi-automated classification, so requires user input to define areas. This means you can utilise your field knowledge to potentially make a more accurate classification. Use the unsupervised classification as a guide what classes to look out for etc. 1. Open signature editor 2. Open original spectral image in viewer. Go AOI tools. Select the polygon tool. 3. Draw AOIs (Areas of Interest) around areas that are uniform in their spectral response. These will be your training areas (to train the classification). Play around with the band combinations to check they are uniform under all wavelengths. You should also use ground-reference data or local site knowledge to pick these training areas. 8
10 4. After you ve drawn each AOI add it to the signature editor (See arrow). Rename it to what you think it is, and recolour. 5. In the signature editor go to classify supervised. Give the output file name (e.g. <image>_class1.img. Press OK to create the classified image, and open in a new viewer. 6. Compare the classified image (left) with the original (right). Are all the classes covered, and are they accurate? In this example, mature forest is not so well represented by the classification to the east of the creek (shaded area). It has also classified some parts of the forest as urban (the red class). 9
11 So on the original image add more AOIs and signatures to cover the areas that are not well represented. In this example we may need to add more AOIs to cover the mature forest class. We may need to do several iterations of classification until we get the most accurate landcover classification. Number all of these files <image>_class2.img, <image>_class3.img etc so you can compare them all. 7. You can also evaluate the signatures, similar to the unsupervised classification process. c) Accuracy Assessment This is the most important step in the whole process a remote sensing image is only a representation before you start doing any stats or analysis you have to be super confident that what you re showing is actually what is on the ground. With landcover classification, we use groundreference data that you have collected (e.g. vegetation quadrats with % species cover). There are a few ways of using this information: 1. Go main toolbar classifier accuracy assessment 2. Go file load image (your classified image) 3. Go edit import user-defined points 4. You ll also have to assign class values under Class Value Assignment Options. This will be a numeric value that you can find in your original signature editor. 5. Edit show class values 6. Report options select Kappa coefficient, error matrix, accuracy totals. 10
12 7. Report accuracy report The error matrix compares the reference points to the classified points. The Kappa coefficient expresses the proportionate reduction in error generated by a classification process compared with the error of a completely random classification. For example, a value of.82 would imply that the classification process was avoiding 82% of the errors that a completely random classification would generate. See the ERDAS field guide for more info. You can also do this by hand if you have your ground-reference data and a way to overlay your GPS points Overlaying GPS points If you ve been in the field, you probably have some data points you want to overlay on a base map, or you have field data that you want to use to assess the accuracy of your classification. Well, this is how you do it. 1. Get your GPS points into the right format. E.g. two columns with one header (x and y). If you do this in excel save it as.csv or.txt (tab delimited). You can then open it up in notepad to check it should look a little something like this: 2. Now SWITCH TO ArcMap/ArcGIS 3. Right click on layers and select add data 11
13 4. Add the background image (e.g. the classified image) 5. Your image will be displayed. Now go to tools add x y data. Load up the GPS point file and choose the right columns. Don t click OK yet! 12
14 6. Now we have to define the coordinate system for the points. Click edit. Since we already have a coordinate system just click on import. Or else you can find it manually by clicking on select. When you ve finished, click OK. That s all folks. 13
Supervised Classification workflow in ENVI 4.8 using WorldView-2 imagery
Supervised Classification workflow in ENVI 4.8 using WorldView-2 imagery WorldView-2 is the first commercial high-resolution satellite to provide eight spectral sensors in the visible to near-infrared
More informationUniversity of Arkansas Libraries ArcGIS Desktop Tutorial. Section 2: Manipulating Display Parameters in ArcMap. Symbolizing Features and Rasters:
: Manipulating Display Parameters in ArcMap Symbolizing Features and Rasters: Data sets that are added to ArcMap a default symbology. The user can change the default symbology for their features (point,
More informationResolutions of Remote Sensing
Resolutions of Remote Sensing 1. Spatial (what area and how detailed) 2. Spectral (what colors bands) 3. Temporal (time of day/season/year) 4. Radiometric (color depth) Spatial Resolution describes how
More informationSpectral Response for DigitalGlobe Earth Imaging Instruments
Spectral Response for DigitalGlobe Earth Imaging Instruments IKONOS The IKONOS satellite carries a high resolution panchromatic band covering most of the silicon response and four lower resolution spectral
More informationOpen icon. The Select Layer To Add dialog opens. Click here to display
Mosaic Introduction This tour guide gives you the steps for mosaicking two or more image files to produce one image file. The mosaicking process works with rectified and/or calibrated images. Here, you
More informationSAMPLE MIDTERM QUESTIONS
Geography 309 Sample MidTerm Questions Page 1 SAMPLE MIDTERM QUESTIONS Textbook Questions Chapter 1 Questions 4, 5, 6, Chapter 2 Questions 4, 7, 10 Chapter 4 Questions 8, 9 Chapter 10 Questions 1, 4, 7
More informationReview for Introduction to Remote Sensing: Science Concepts and Technology
Review for Introduction to Remote Sensing: Science Concepts and Technology Ann Johnson Associate Director ann@baremt.com Funded by National Science Foundation Advanced Technological Education program [DUE
More informationRESOLUTION MERGE OF 1:35.000 SCALE AERIAL PHOTOGRAPHS WITH LANDSAT 7 ETM IMAGERY
RESOLUTION MERGE OF 1:35.000 SCALE AERIAL PHOTOGRAPHS WITH LANDSAT 7 ETM IMAGERY M. Erdogan, H.H. Maras, A. Yilmaz, Ö.T. Özerbil General Command of Mapping 06100 Dikimevi, Ankara, TURKEY - (mustafa.erdogan;
More informationRemote Sensing and Land Use Classification: Supervised vs. Unsupervised Classification Glen Busch
Remote Sensing and Land Use Classification: Supervised vs. Unsupervised Classification Glen Busch Introduction In this time of large-scale planning and land management on public lands, managers are increasingly
More informationUsing Google Earth for Environmental Science Research
Using Google Earth for Environmental Science Research This document is up-to-date as of August 2013. If you have any questions or additions to this material please email dan.friess@nus.edu.sg. Note: this
More informationENVI THE PREMIER SOFTWARE FOR EXTRACTING INFORMATION FROM GEOSPATIAL IMAGERY.
ENVI THE PREMIER SOFTWARE FOR EXTRACTING INFORMATION FROM GEOSPATIAL IMAGERY. ENVI Imagery Becomes Knowledge ENVI software uses proven scientific methods and automated processes to help you turn geospatial
More informationENVI Classic Tutorial: Classification Methods
ENVI Classic Tutorial: Classification Methods Classification Methods 2 Files Used in this Tutorial 2 Examining a Landsat TM Color Image 3 Reviewing Image Colors 3 Using the Cursor Location/Value 4 Examining
More informationEnvironmental Remote Sensing GEOG 2021
Environmental Remote Sensing GEOG 2021 Lecture 4 Image classification 2 Purpose categorising data data abstraction / simplification data interpretation mapping for land cover mapping use land cover class
More informationStep-by-Step guide for IMAGINE UAV workflow
Step-by-Step guide for IMAGINE UAV workflow Overview This short guide will go through all steps of the UAV workflow that are needed to produce the final results. Those consist out of two raster datasets,
More informationSoftware requirements * :
Title: Product Type: Developer: Target audience: Format: Software requirements * : Data: Estimated time to complete: Fire Mapping using ASTER Part I: The ASTER instrument and fire damage assessment Part
More informationDigital image processing
746A27 Remote Sensing and GIS Lecture 4 Digital image processing Chandan Roy Guest Lecturer Department of Computer and Information Science Linköping University Digital Image Processing Most of the common
More informationData Visualization. Prepared by Francisco Olivera, Ph.D., Srikanth Koka Department of Civil Engineering Texas A&M University February 2004
Data Visualization Prepared by Francisco Olivera, Ph.D., Srikanth Koka Department of Civil Engineering Texas A&M University February 2004 Contents Brief Overview of ArcMap Goals of the Exercise Computer
More informationThe premier software for extracting information from geospatial imagery.
Imagery Becomes Knowledge ENVI The premier software for extracting information from geospatial imagery. ENVI Imagery Becomes Knowledge Geospatial imagery is used more and more across industries because
More informationWATER BODY EXTRACTION FROM MULTI SPECTRAL IMAGE BY SPECTRAL PATTERN ANALYSIS
WATER BODY EXTRACTION FROM MULTI SPECTRAL IMAGE BY SPECTRAL PATTERN ANALYSIS Nguyen Dinh Duong Department of Environmental Information Study and Analysis, Institute of Geography, 18 Hoang Quoc Viet Rd.,
More informationImage Draping & navigation within Virtual GIS
Image Draping & navigation within Virtual GIS Draping of Geo Corrected data such as aerial imagery or map data enables virtual 3D field tours to be conducted in an area of interest. This document covers
More informationImage Registration. Using Quantum GIS
Using Quantum GIS Tutorial ID: IGET_GIS_004 This tutorial has been developed by BVIEER as part of the IGET web portal intended to provide easy access to geospatial education. This tutorial is released
More informationGeography 3251: Mountain Geography Assignment III: Natural hazards A Case Study of the 1980s Mt. St. Helens Eruption
Name: Geography 3251: Mountain Geography Assignment III: Natural hazards A Case Study of the 1980s Mt. St. Helens Eruption Learning Objectives: Assigned: May 30, 2012 Due: June 1, 2012 @ 9 AM 1. Learn
More informationENVI Classic Tutorial: Atmospherically Correcting Hyperspectral Data using FLAASH 2
ENVI Classic Tutorial: Atmospherically Correcting Hyperspectral Data Using FLAASH Atmospherically Correcting Hyperspectral Data using FLAASH 2 Files Used in This Tutorial 2 Opening the Uncorrected AVIRIS
More informationMosaicking and Subsetting Images
Mosaicking and Subsetting Images Using SAGA GIS Tutorial ID: IGET_RS_005 This tutorial has been developed by BVIEER as part of the IGET web portal intended to provide easy access to geospatial education.
More informationSymbolizing your data
Symbolizing your data 6 IN THIS CHAPTER A map gallery Drawing all features with one symbol Drawing features to show categories like names or types Managing categories Ways to map quantitative data Standard
More informationENVI Classic Tutorial: Atmospherically Correcting Multispectral Data Using FLAASH 2
ENVI Classic Tutorial: Atmospherically Correcting Multispectral Data Using FLAASH Atmospherically Correcting Multispectral Data Using FLAASH 2 Files Used in this Tutorial 2 Opening the Raw Landsat Image
More informationWHAT IS GIS - AN INRODUCTION
WHAT IS GIS - AN INRODUCTION GIS DEFINITION GIS is an acronym for: Geographic Information Systems Geographic This term is used because GIS tend to deal primarily with geographic or spatial features. Information
More informationUnderstanding Raster Data
Introduction The following document is intended to provide a basic understanding of raster data. Raster data layers (commonly referred to as grids) are the essential data layers used in all tools developed
More informationRaster Tutorial. Copyright 1995-2010 Esri All rights reserved.
Copyright 1995-2010 Esri All rights reserved. Table of Contents Introduction to the ArcGIS raster tutorial......................... 3 Exercise 1: Creating a mosaic dataset.......................... 4 Exercise
More informationHow to georectify an image in ArcMap 10
How to georectify an image in ArcMap 10 The University Library has a large collection of historical aerial photos for some North Carolina Counties ( http://www.lib.unc.edu/reference/gis/usda/index.html
More informationGIS Lesson 6 MAPS WITH RASTER IMAGES III: SATELLITE IMAGERY TEACHER INFORMATION
GIS Lesson 6 MAPS WITH RASTER IMAGES III: SATELLITE IMAGERY TEACHER INFORMATION Lesson Summary: During this lesson students use GIS to load and view truecolor and enhanced satellite images of Alaska. Based
More informationFiles Used in this Tutorial
Generate Point Clouds Tutorial This tutorial shows how to generate point clouds from IKONOS satellite stereo imagery. You will view the point clouds in the ENVI LiDAR Viewer. The estimated time to complete
More informationDigital Classification and Mapping of Urban Tree Cover: City of Minneapolis
Digital Classification and Mapping of Urban Tree Cover: City of Minneapolis FINAL REPORT April 12, 2011 Marvin Bauer, Donald Kilberg, Molly Martin and Zecharya Tagar Remote Sensing and Geospatial Analysis
More informationArcGIS. Image Server tutorial
ArcGIS 9 ArcGIS Image Server tutorial Copyright 2006, 2007, and 2008 Zanja Technologies, Inc. All rights reserved. The information contained in this work is the property of Zanja Technologies, Inc., under
More informationAPPLICATION OF MULTITEMPORAL LANDSAT DATA TO MAP AND MONITOR LAND COVER AND LAND USE CHANGE IN THE CHESAPEAKE BAY WATERSHED
APPLICATION OF MULTITEMPORAL LANDSAT DATA TO MAP AND MONITOR LAND COVER AND LAND USE CHANGE IN THE CHESAPEAKE BAY WATERSHED S. J. GOETZ Woods Hole Research Center Woods Hole, Massachusetts 054-096 USA
More informationCafcam: Crisp And Fuzzy Classification Accuracy Measurement Software
Cafcam: Crisp And Fuzzy Classification Accuracy Measurement Software Mohamed A. Shalan 1, Manoj K. Arora 2 and John Elgy 1 1 School of Engineering and Applied Sciences, Aston University, Birmingham, UK
More informationCreating Slope-Enhanced Shaded-Relief Using Global Mapper
Creating Slope-Enhanced Shaded-Relief Using Global Mapper Kent D. Brown Utah Geological Survey Introduction The purpose of this document is to demonstrate that slope-enhanced hillshade, or shaded-relief
More informationLand Use/Land Cover Map of the Central Facility of ARM in the Southern Great Plains Site Using DOE s Multi-Spectral Thermal Imager Satellite Images
Land Use/Land Cover Map of the Central Facility of ARM in the Southern Great Plains Site Using DOE s Multi-Spectral Thermal Imager Satellite Images S. E. Báez Cazull Pre-Service Teacher Program University
More informationGEOGRAPHIC INFORMATION SYSTEMS Lecture 20: Adding and Creating Data
Adding Existing Data Into ArcGIS - there are many different ways to get data into ArcGIS GEOGRAPHIC INFORMATION SYSTEMS Lecture 20: Adding and Creating Data Add Data - normally we use the Add Data button
More informationTo Begin Customize Office
To Begin Customize Office Each of us needs to set up a work environment that is comfortable and meets our individual needs. As you work with Office 2007, you may choose to modify the options that are available.
More informationIntroduction to Imagery and Raster Data in ArcGIS
Esri International User Conference San Diego, California Technical Workshops July 25, 2012 Introduction to Imagery and Raster Data in ArcGIS Simon Woo slides Cody Benkelman - demos Overview of Presentation
More informationRESULTS. that remain following use of the 3x3 and 5x5 homogeneity filters is also reported.
RESULTS Land Cover and Accuracy for Each Landsat Scene All 14 scenes were successfully classified. The following section displays the results of the land cover classification, the homogenous filtering,
More informationIntroduction to ILWIS 3.11 using a data set from Kathmandu valley.
Introduction to ILWIS 3.11 using a data set from Kathmandu valley. C.J. van Westen Dept. of Environmental System Analysis, International Institute Geo-Information Science and Earth Observation (ITC), P.O.
More informationUsing Remote Sensing Imagery to Evaluate Post-Wildfire Damage in Southern California
Graham Emde GEOG 3230 Advanced Remote Sensing February 22, 2013 Lab #1 Using Remote Sensing Imagery to Evaluate Post-Wildfire Damage in Southern California Introduction Wildfires are a common disturbance
More informationRemote sensing is the collection of data without directly measuring the object it relies on the
Chapter 8 Remote Sensing Chapter Overview Remote sensing is the collection of data without directly measuring the object it relies on the reflectance of natural or emitted electromagnetic radiation (EMR).
More informationJACIE Science Applications of High Resolution Imagery at the USGS EROS Data Center
JACIE Science Applications of High Resolution Imagery at the USGS EROS Data Center November 8-10, 2004 U.S. Department of the Interior U.S. Geological Survey Michael Coan, SAIC USGS EROS Data Center coan@usgs.gov
More informationThe USGS Landsat Big Data Challenge
The USGS Landsat Big Data Challenge Brian Sauer Engineering and Development USGS EROS bsauer@usgs.gov U.S. Department of the Interior U.S. Geological Survey USGS EROS and Landsat 2 Data Utility and Exploitation
More informationRemote sensing and GIS applications in coastal zone monitoring
Remote sensing and GIS applications in coastal zone monitoring T. Alexandridis, C. Topaloglou, S. Monachou, G.Tsakoumis, A. Dimitrakos, D. Stavridou Lab of Remote Sensing and GIS School of Agriculture
More informationLab #8: Introduction to ENVI (Environment for Visualizing Images) Image Processing
Lab #8: Introduction to ENVI (Environment for Visualizing Images) Image Processing ASSIGNMENT: Display each band of a satellite image as a monochrome image and combine three bands into a color image, and
More informationA remote sensing instrument collects information about an object or phenomenon within the
Satellite Remote Sensing GE 4150- Natural Hazards Some slides taken from Ann Maclean: Introduction to Digital Image Processing Remote Sensing the art, science, and technology of obtaining reliable information
More informationAssessing Hurricane Katrina Damage to the Mississippi Gulf Coast Using IKONOS Imagery
Assessing Hurricane Katrina Damage to the Mississippi Gulf Coast Using IKONOS Imagery Joseph P. Spruce Science Systems and Applications, Inc. John C., MS 39529 Rodney McKellip NASA Project Integration
More informationMyths and misconceptions about remote sensing
Myths and misconceptions about remote sensing Ned Horning (graphics support - Nicholas DuBroff) Version: 1.0 Creation Date: 2004-01-01 Revision Date: 2004-01-01 License: This document is licensed under
More informationWhat do I do first in ArcView 8.x? When the program starts Select from the Dialog box: A new empty map
www.library.carleton.ca/find/gis Introduction Introduction to Georeferenced Images using ArcGIS Georeferenced images such as aerial photographs or satellite images can be used in many ways in both GIS
More informationImagery. 1:50,000 Basemap Generation From Satellite. 1 Introduction. 2 Input Data
1:50,000 Basemap Generation From Satellite Imagery Lisbeth Heuse, Product Engineer, Image Applications Dave Hawkins, Product Manager, Image Applications MacDonald Dettwiler, 3751 Shell Road, Richmond B.C.
More informationCreate a folder on your network drive called DEM. This is where data for the first part of this lesson will be stored.
In this lesson you will create a Digital Elevation Model (DEM). A DEM is a gridded array of elevations. In its raw form it is an ASCII, or text, file. First, you will interpolate elevations on a topographic
More informationLesson 15 - Fill Cells Plugin
15.1 Lesson 15 - Fill Cells Plugin This lesson presents the functionalities of the Fill Cells plugin. Fill Cells plugin allows the calculation of attribute values of tables associated with cell type layers.
More information2.3 Spatial Resolution, Pixel Size, and Scale
Section 2.3 Spatial Resolution, Pixel Size, and Scale Page 39 2.3 Spatial Resolution, Pixel Size, and Scale For some remote sensing instruments, the distance between the target being imaged and the platform,
More informationGetting an ArcGIS Online account, creating a web map with the ArcGIS.com Map Viewer, loading and a shapefile, and then sharing options, step-by-step.
Getting an ArcGIS Online account, creating a web map with the ArcGIS.com Map Viewer, loading and a shapefile, and then sharing options, step-by-step. OK, so to start, point your browser to http://www.arcgis.com,
More informationTutorial 8 Raster Data Analysis
Objectives Tutorial 8 Raster Data Analysis This tutorial is designed to introduce you to a basic set of raster-based analyses including: 1. Displaying Digital Elevation Model (DEM) 2. Slope calculations
More informationRemote Sensing of Environment
Remote Sensing of Environment 115 (2011) 1145 1161 Contents lists available at ScienceDirect Remote Sensing of Environment journal homepage: www.elsevier.com/locate/rse Per-pixel vs. object-based classification
More informationESRI China (Hong Kong) Limited
Tips for Creating 3D Graphics in ArcScene 9.x Article ID : 100003 Software : ArcGIS 3D Analyst 9.x Platform : Windows 2000, Windows XP Date : June 28, 2005 Background Prior to ArcGIS Desktop 9.0, we cannot
More informationData Visualization. Brief Overview of ArcMap
Data Visualization Prepared by Francisco Olivera, Ph.D., P.E., Srikanth Koka and Lauren Walker Department of Civil Engineering September 13, 2006 Contents: Brief Overview of ArcMap Goals of the Exercise
More informationKEYWORDS: image classification, multispectral data, panchromatic data, data accuracy, remote sensing, archival data
Improving the Accuracy of Historic Satellite Image Classification by Combining Low-Resolution Multispectral Data with High-Resolution Panchromatic Data Daniel J. Getman 1, Jonathan M. Harbor 2, Chris J.
More informationRaster Data Structures
Raster Data Structures Tessellation of Geographical Space Geographical space can be tessellated into sets of connected discrete units, which completely cover a flat surface. The units can be in any reasonable
More informationRelating Land Cover Changes to Stream Water Quality in North Carolina
Relating Land Cover Changes to Stream Water Quality in North Carolina STUDENT HANDOUT! Central Question How has land cover within Long Creek Watershed in Charlotte, NC changed between 1988 and 2008? Overview
More informationMASKS & CHANNELS WORKING WITH MASKS AND CHANNELS
MASKS & CHANNELS WORKING WITH MASKS AND CHANNELS Masks let you isolate and protect parts of an image. When you create a mask from a selection, the area not selected is masked or protected from editing.
More informationContents. The OWRB Floodplain Viewer. Creating Maps... 8. Helpful Tips... 10
Contents QUICK START GUIDE... 2-5 Add layers...9 Search for Layers...9 COMPREHENSIVE GUIDE... 6 Navigate the map...6 Locate specific places...6 Add layer from file...9 Add layer from web...9 Display pop-up
More informationDigital Remote Sensing Data Processing Digital Remote Sensing Data Processing and Analysis: An Introduction and Analysis: An Introduction
Digital Remote Sensing Data Processing Digital Remote Sensing Data Processing and Analysis: An Introduction and Analysis: An Introduction Content Remote sensing data Spatial, spectral, radiometric and
More informationTantalis GATOR Expanded Image Help Guide
Tantalis GATOR Expanded Image Help Guide Instructions for Increasing Image Resolution and Large size Printing The following are suggestions for printing an image using the Enabled MrSID plug-in and for
More informationHyperspectral Satellite Imaging Planning a Mission
Hyperspectral Satellite Imaging Planning a Mission Victor Gardner University of Maryland 2007 AIAA Region 1 Mid-Atlantic Student Conference National Institute of Aerospace, Langley, VA Outline Objective
More informationRemote Sensing and GIS Application In Change Detection Study In Urban Zone Using Multi Temporal Satellite
Remote Sensing and GIS Application In Change Detection Study In Urban Zone Using Multi Temporal Satellite R.Manonmani, G.Mary Divya Suganya Institute of Remote Sensing, Anna University, Chennai 600 025
More informationERDAS IMAGINE The world s most widely-used remote sensing software package
ERDAS IMAGINE The world s most widely-used remote sensing software package ERDAS IMAGINE Geographic imaging professionals need to process vast amounts of geospatial data every day often relying on software
More informationApplication of Remotely Sensed Data and Technology to Monitor Land Change in Massachusetts
Application of Remotely Sensed Data and Technology to Monitor Land Change in Massachusetts Sam Blanchard, Nick Bumbarger, Joe Fortier, and Alina Taus Advisor: John Rogan Geography Department, Clark University
More informationSome elements of photo. interpretation
Some elements of photo Shape Size Pattern Color (tone, hue) Texture Shadows Site Association interpretation Olson, C. E., Jr. 1960. Elements of photographic interpretation common to several sensors. Photogrammetric
More informationINSTRUCTIONS FOR MAKING 3D,.DWG CONTOUR LINES
INSTRUCTIONS FOR MAKING 3D,.DWG CONTOUR LINES A TUTORIAL FROM SPATIAL AND NUMERIC DATA SERVICES NICOLE SCHOLTZ AND GEOFF IVERSON Overview... 2 A. Get a Digital Elevation Model (DEM)... 3 B. Open ArcMap,
More informationSPOT Satellite Earth Observation System Presentation to the JACIE Civil Commercial Imagery Evaluation Workshop March 2007
SPOT Satellite Earth Observation System Presentation to the JACIE Civil Commercial Imagery Evaluation Workshop March 2007 Topics Presented Quick summary of system characteristics Formosat-2 Satellite Archive
More informationStatgraphics Getting started
Statgraphics Getting started The aim of this exercise is to introduce you to some of the basic features of the Statgraphics software. Starting Statgraphics 1. Log in to your PC, using the usual procedure
More informationINVESTIGA I+D+i 2013/2014
INVESTIGA I+D+i 2013/2014 SPECIFIC GUIDELINES ON AEROSPACE OBSERVATION OF EARTH Text by D. Eduardo de Miguel October, 2013 Introducction Earth observation is the use of remote sensing techniques to better
More informationMultiscale Object-Based Classification of Satellite Images Merging Multispectral Information with Panchromatic Textural Features
Remote Sensing and Geoinformation Lena Halounová, Editor not only for Scientific Cooperation EARSeL, 2011 Multiscale Object-Based Classification of Satellite Images Merging Multispectral Information with
More informationHow to create PDF maps, pdf layer maps and pdf maps with attributes using ArcGIS. Lynne W Fielding, GISP Town of Westwood
How to create PDF maps, pdf layer maps and pdf maps with attributes using ArcGIS Lynne W Fielding, GISP Town of Westwood PDF maps are a very handy way to share your information with the public as well
More informationMultinomial Logistics Regression for Digital Image Classification
Multinomial Logistics Regression for Digital Image Classification Dr. Moe Myint, Chief Scientist, Mapping and Natural Resources Information Integration (MNRII), Switzerland maungmoe.myint@mnrii.com KEY
More informationCROP CLASSIFICATION WITH HYPERSPECTRAL DATA OF THE HYMAP SENSOR USING DIFFERENT FEATURE EXTRACTION TECHNIQUES
Proceedings of the 2 nd Workshop of the EARSeL SIG on Land Use and Land Cover CROP CLASSIFICATION WITH HYPERSPECTRAL DATA OF THE HYMAP SENSOR USING DIFFERENT FEATURE EXTRACTION TECHNIQUES Sebastian Mader
More informationANALYSIS OF FOREST CHANGE IN FIRE DAMAGE AREA USING SATELLITE IMAGES
ANALYSIS OF FOREST CHANGE IN FIRE DAMAGE AREA USING SATELLITE IMAGES Joon Mook Kang, Professor Joon Kyu Park, Ph.D Min Gyu Kim, Ph.D._Candidate Dept of Civil Engineering, Chungnam National University 220
More informationWorking with the Raster Calculator
Working with the Raster Calculator The Raster Calculator provides you a powerful tool for performing multiple tasks. You can perform mathematical calculations using operators and functions, set up selection
More informationIII THE CLASSIFICATION OF URBAN LAND COVER USING REMOTE SENSING
The Dynamics of Global Urban Expansion 31 III THE CLASSIFICATION OF URBAN LAND COVER USING REMOTE SENSING 1. Overview and Rationale The systematic study of global urban expansion requires good data that
More informationGEOREFERENCING HISTORIC MAPS USING ARCGIS DESKTOP 10
5/20/2011 BALL STATE UNIVERSITY LIBRARIES GIS RESEARCH AND MAP COLLECTION GEOREFERENCING HISTORIC MAPS USING ARCGIS DESKTOP 10 GEOREFERENCING HISTORIC MAPS USING ARCGIS DESKTOP 10 *This tutorial is appropriate
More informationLand Use/ Land Cover Mapping Initiative for Kansas and the Kansas River Watershed
Land Use/ Land Cover Mapping Initiative for Kansas and the Kansas River Watershed Kansas Biological Survey Kansas Applied Remote Sensing Program April 2008 Previous Kansas LULC Projects Kansas LULC Map
More informationPHASE 2_3 RD SESSION REPORT KU GIS LABS ARCGIS TRAINING: USING ARCGIS (APPLICATIONS) 18 TH - 22 ND AUGUST 2014 SCHOOL OF ENGINEERING COMPUTER LAB
PHASE 2_3 RD SESSION REPORT KU GIS LABS ARCGIS TRAINING: USING ARCGIS (APPLICATIONS) 18 TH - 22 ND AUGUST 2014 SCHOOL OF ENGINEERING COMPUTER LAB PHASE 2_3 rd SESSION REPORT ARCGIS TRAINING: 18 TH - 22
More informationHow Landsat Images are Made
How Landsat Images are Made Presentation by: NASA s Landsat Education and Public Outreach team June 2006 1 More than just a pretty picture Landsat makes pretty weird looking maps, and it isn t always easy
More informationSESSION 8: GEOGRAPHIC INFORMATION SYSTEMS AND MAP PROJECTIONS
SESSION 8: GEOGRAPHIC INFORMATION SYSTEMS AND MAP PROJECTIONS KEY CONCEPTS: In this session we will look at: Geographic information systems and Map projections. Content that needs to be covered for examination
More informationRaster to Vector Conversion for Overlay Analysis
Raster to Vector Conversion for Overlay Analysis In some cases, it may be necessary to perform vector-based analyses on a raster data set, or vice versa. The types of analyses that can be performed on
More informationThere are two distinct working environments, or spaces, in which you can create objects in a drawing.
That CAD Girl J ennifer dib ona Website: www.thatcadgirl.com Email: thatcadgirl@aol.com Phone: (919) 417-8351 Fax: (919) 573-0351 Autocad Model Space and Paper Space Model Space vs. Paper Space Initial
More information'Developments and benefits of hydrographic surveying using multispectral imagery in the coastal zone
Abstract With the recent launch of enhanced high-resolution commercial satellites, available imagery has improved from four-bands to eight-band multispectral. Simultaneously developments in remote sensing
More information2002 URBAN FOREST CANOPY & LAND USE IN PORTLAND S HOLLYWOOD DISTRICT. Final Report. Michael Lackner, B.A. Geography, 2003
2002 URBAN FOREST CANOPY & LAND USE IN PORTLAND S HOLLYWOOD DISTRICT Final Report by Michael Lackner, B.A. Geography, 2003 February 2004 - page 1 of 17 - TABLE OF CONTENTS Abstract 3 Introduction 4 Study
More informationTutorial 6 GPS/Point Shapefile Creation
Tutorial 6 GPS/Point Shapefile Creation The objectives of this tutorial include: 1. Converting GPS field collected point information into a shapefile 2. Creating a shapefile from a simple x,y coordinate
More informationTerraColor White Paper
TerraColor White Paper TerraColor is a simulated true color digital earth imagery product developed by Earthstar Geographics LLC. This product was built from imagery captured by the US Landsat 7 (ETM+)
More informationUser s Guide to ArcView 3.3 for Land Use Planners in Puttalam District
User s Guide to ArcView 3.3 for Land Use Planners in Puttalam District Dilhari Weragodatenna IUCN Sri Lanka, Country Office Table of Content Page No Introduction...... 1 1. Getting started..... 2 2. Geo-referencing...
More informationA GIS helps you answer questions and solve problems by looking at your data in a way that is quickly understood and easily shared.
A Geographic Information System (GIS) integrates hardware, software, and data for capturing, managing, analyzing, and displaying all forms of geographically referenced information. GIS allows us to view,
More informationPreface. Ko Ko Lwin Division of Spatial Information Science University of Tsukuba 2008
1 Preface Remote Sensing data is one of the primary data sources in GIS analysis. The objective of this material is to provide fundamentals of Remote Sensing technology and its applications in Geographical
More informationInformation Contents of High Resolution Satellite Images
Information Contents of High Resolution Satellite Images H. Topan, G. Büyüksalih Zonguldak Karelmas University K. Jacobsen University of Hannover, Germany Keywords: satellite images, mapping, resolution,
More information