Skip to main content

Geographic Information Systems (GIS)

Welcome to Geographic Information Systems!

Introduction to GIS

About this Course

 

This course is designed to provide a basic understanding of how Geographic Information Systems (GIS) and satellite imagery can be used to visualize and analyze spatial data.  Students will learn basic techniques for analyzing, manipulating, and creating geospatial data in both pixel-based (e.g., satellite imagery and digital terrain models) and vector-based (e.g., point, line, and polygon representations of spatial data) formats.  Students will also learn how to acquire high-resolution satellite imagery and other GIS data from online data servers.

About the Instructor

 

 

Matthew L. Sisk is the Geographic Information Systems (GIS) and Anthropology Librarian in the Center for Digital Scholarship at the University of Notre Dame.  He received his Ph.D. from Stony Brook University where he focused on archaeology and ecological modeling.  At Notre Dame he collaborates with researchers and students on spatial analysis and mapping, and he teaches on a series of GIS related topics.

About the CDS

 

The Hesburgh Libraries Center for Digital Scholarship (CDS) provides specialized expertisetechnologies, and technology-enriched collaborative spaces in support of research and scholarship that is conducted by or enhanced through the use of digital scholarship tools and methodologies.  Integrated expertise in the Center accelerates knowledge creation and offers advanced technological support throughout the full life cycle of research in the digital age.

One-on-one consultationsworkshops, and specialty software are available in several interdisciplinary areas, including:  Data Use and AnalysisData ManagementDigitization and MetadataGeographic Information Systems, and Text Mining, Analysis, and Encoding.

Additional services include professional digitization, self-service scanning, and 3D modeling and printing.  Faculty and students also have access to a high-tech Classroom and Conference Room, collaborative group project pods, audio and video recording studios, a transcription station, GPS units, and inventor kits (e.g., Arduino, Raspberry Pi, MakeyMakey).

Not sure where to start?  E-mail cds@nd.edu with any questions or visit library.nd.edu/cds for more information about our services and expertise.

Overview of Course Structure

General Overview

There are a total of 13 modules in this course.  Each module covers a specific topic and includes the following:

  • 1 lecture video
  • 1 demonstration video
  • 1 dataset (linked; for all module demonstrations except Module 1)
  • Assignment details where applicable

Each lecture and each demonstration video will have a corresponding set of materials.  Lectures will have PDFs of slides that Professor Sisk refers to throughout the lecture video.  Demo videos will include corresponding notes and data files. 

All related demo files can be found here--corresponding links are also located in each section of the course.

Course Tour

New to edX Edge?  This short course tour will walk you through some of the platform's features in the context of this course.  

Module 1: What is GIS and ArcGIS?

Lecture 1 Video: What is GIS? 

This module provides an overview of the main concepts in Geographic Information Systems, common data models, and some applications of GIS data.  

Download GIS Demo 1 Data File

Demo 1 Video: Loading Data 

Each demonstration section will contain a link to the specific data for that section.  When the link is clicked, the .zip file will automatically begin downloading.  

Transcript:

Download SubRip(.srt) File

Module 2: The Raster Data Model

Lecture 2: Raster Data Model

 

This module represents the first of two main GIS data models--raster data.  Raster data are a pixel-based way of representing spatial data.  This module discusses their strengths and weaknesses and introduces how to work with them using GIS software.

Transcripts:

Lecture 2 Slides

Demo 2 Video: Displaying Raster Data

Transcripts:

Demo 2 Notes

Module 2 Assignment

 

Assignment for Module 02:  Raster Data Models

To do the assignment, you will follow the instructions for the in the demo notes. The data can be found in the zip file for Demo 2.

Respond to the following points.  Illustrate your work by inserting screen captures into a Word document along with the appropriate explanatory text.  To make screen captures, press Print Screen (PrtSc) to copy the entire screen or Alt-PrtSc to capture only the active window; you can then paste (Ctrl-V) the screen capture into a MS Word document.  Make sure your file contains your last name, both in the text and in the filename (e.g., smith_lab01.doc), and then upload it onto the course site via the link.  If you must upload multiple files, please use the ZIP utility to compress them into a single .zip file.

1.  You should have two images for Notre Dame, one is a multispectral image and one is a panchromatic image.  Which is which?  How do you know?

2. Change the stretch applied to the SPOT image.  Provide screen-shots and description of 2 of the pre-made stretches and 1 that you did yourself (for this one also provide a shot of the histograms).

3. Perform 3 different filters on either image, provide screen-shots and briefly describe what has changed.  The ESRI help file can give you a bit more detail on these filters

4. Zoom in and make sure you have both the Landsat MSS and the SPOT image in your table of contents.  Experiment with the swipe and flicker commands.  Provide a screen-shot of the swipe (I doubt you can catch the flicker).

Lecture 3: The Vector Data Model

Lecture 3 Video: The Vector Data Model

 

The second of two main GIS data models, vector data are geometric representations of spatial information.  This module discusses their strengths and weaknesses and introduces how to work with them in GIS software.

Transcripts

Lecture 3 Slides

Demo 3 Video: Displaying Vector Data

Transcripts

Demo 3 Notes

Module 3 Assignment

 

For the assignment I want you to to explore different ways of visualizing vector data.  In the zip file, I have provided a compressed file of a few different layers for Indiana.

Specifically, I would like screen-shots and a brief description of the following:

1). Using the Identify tool to Determine which Quad Sheet(s) the University of the Notre Dame is in. Do this with the  IN_QuadIndex.shp file. You may want to add in one of the raster images from module 2 to locate the precise area.

2). Calculating Statistics for a field in an attribute table.  Note, this must be a numeric field.

3). Measuring the distance between two features

4). Selecting features by both attributes and locations

5). Symbolizing features in three different ways, with at least one as a chart

This means you should have at least 8 screen-shots in your final file.  Try to keep the extent somewhat consistent and please be clear in describing what each screen-shot is showing.

Lecture 4: Projections and Georeferencing

Lecture 4 Video: Projections and Georeferencing

 

The way we take spherical geographic data and convert it to a flat map (or computer screen) is complicated.  This module introduces the process of projecting spherical data onto a flat surface and outlines how to take an unreferenced image and assign it world coordinates.

Transcripts

Lecture 4 Notes

Demo 4 Video: Georeferencing Maps in ArcGIS

Transcripts

Demo 4 Notes

Module 4 Assignment

 

Assignment for Module 04: Projections and Georeferencing

  1. Provide a screenshot of the full mosaicked image and one that is a zoom in on the boundary. (Sections II and III)
  2. As you reproject the image from Lat/Long to UTM, provide a screenshot of the Project Raster window and another screenshot of the image with UTM coordinates visible in the background (you may need to open a new Map Document and add it back in) (Section IV and VII)
  3. Follow the steps outlined in V. Georeferencing Imagery above.  Georeference the image using either the quad sheet or the Spot Imagery from Module 01.  Once it is rectified, give me a screenshot of the new image with the Table of Contents and the coordinates visible in the bottom right corner of the screen.  Also, zoom in on and use the Swipe command to give me a screenshot of the Aerial1998 compared to the image you used to georeference it. (Section V)
  4. Crop the georeferenced Aerial1998 to the limits of the Notre Dame campus.  Turn off all other layers except this new cropped image and the ND_Outlines.shp layer (with the features only visible as a colored boundary).  Zoom it to its full extent and take a screenshot. (Section VI)

Lecture 5: Satellite Imagery and Aerial Photographs

Lecture 5 Video: Satellite Imagery and Aerial Photographs

 

 

By sampling wavelengths of light outside what our eyes can perceive, satellite imagery can give us important insight into natural phenomenon.  This module introduces a suite of tools for working with satellite and other remote sensing data.

Transcripts

Lecture 5 Notes

Demo 5 Video: Spectral Enhancement

Transcripts

Demo 5 Notes

Module 5 Assignment

Follow the tasks outlined in the demo notes using the area around Notre Dame.  In a few cases you will need to use the images from previous modules.  Provide the following screenshots for each section.

Layer Stack (Section II in the Demo Notes)

1).  The stacked 7 band Landsat ETM image of all of Michiana, symbolized with Band 4 in the Red Gun, Band 3 in the Green Gun and Band 2 in the Blue Gun.  You can be at any scale, but make sure that I can see that image is in color and the Table of Contents showing the band combinations.

2). This website (http://gdsc.nlr.nl/gdsc/en/information/earth_observation/band_combinations) gives a list of several different RGB composites for landsat TM / ETM imagery.  Choose one other than the 321 or 432 and display your image using that combination.  Provide a screenshot and give a description of  what you chose, why and a few examples of what you think it is showing you.

Cropping Imagery (Section III in the Demo Notes)

3).  The 7 band Landsat cropped to the extent of the South Bend quad sheets

4).  Band 8 of the Landsat cropped to the extent of the South Bend quad sheets

Pan Sharpening (Section IV in the Demo Notes)

5).  The pan-sharpened image. Make sure you are at the full extent of this layer

6).  Zoom in on the pan-sharpened image.  Make note of a feature (building, road, etc) that has been made visible by the sharpening

Vegetation Index (Section V in the Demo Notes)

7). The NDVI of the Landsat ETM from this module (what you stacked and cropped above).  Zoom to the full extent and change the color ramp.  

8). Run a NDVI analysis on the Landsat MSS image from the Raster Dame module.  You will need to change the bands used by the analysis in the Image Analysis Options (Section V.C.1.ii).  Zoom to the full extent and change the color ramp.  Briefly discuss (1-2 sentences) any differences between the two NDVI results and what you think may have caused them

Module 6: Creating and Manipulating Vector Data

Lecture 6 Video: Creating and Manipulating Vector Data

 

Frequently, vector data will need to be created from a variety of sources.  This module works through the process of creating vector data.

Transcripts

Lecture 6 Notes

Demo 6 Video: Creating Vector Data

Transcripts

Demo 6 Notes

Module 6 Assignment

 

Your assignment this module is simple, if a bit time intensive.  

You should fully vectorize the soil map for Notre Dame campus.  This may seem like a mind-numbingly monotonous task, but creating features is a crucial ArcGIS skill the best way to learn is through repetition.  Make sure you save the final shapefiles (soils and extent) to a permanent location as we will use them again

I would like to see the following screenshots during the process of vectorizing your soil map:

1). You creating a new feature using the standard Polygon tool (Section IV.d).   It is possible that you will only use this tool for the first feature you create, so be sure to take this screenshot early.  The feature should be completed, but not finished (i.e. missing the final double-click) when you press Print Screen (like the example to the right).  Also, unlike the example, the raster soil map should be visible.

2).  You creating a new feature using the Auto-complete Polygon tool (Section V.a), with the same requirements as before.

3).  You creating a new feature using the Cut Polygons Tool.  This can either be cutting one feature in two (Section V.b),  or dealing with an island polygon (Section V.c).  Again, the feature should be unfinished with the raster soils map visible underneath.

4). Once the soil map is vectorized, a view of the whole of your new shapefile. The soils layer should be symbolized with each soil type in a different color.  The table of contents showing this symbology (i.e. the layer is not minimized) should be visible.

 

5). Finally, a screenshot of the completed attribute table of the soils map, with all of the features filled out.

Module 7: Table and Databases

Lecture 7 Video: Table and Databases - Making a Spatial Database

 

A major strength of GIS is this ability to work with many different spatial and non-spatial data tables.  In this module the main concepts of linking these tables and analyzing the data are covered in this module.

Lecture 7 Notes

Demo 7 Video: Tables

Transcripts

Demo 7 Notes

Module 7 Assignment

 

Your assignment for this module is divided between working on your Soils shapefile from the Creating Vectors module and the USGS water sampling data

For the Soils Shapefile:

A). First, follow the process outlined in Section II and join SoilDescriptions_StJoseph to your soils shapefile from the Creating Vectors module.  Export the file to make it permanent and remove the duplicate fields. Show a screenshot of the final attribute table.

B). Next follow the process in Section III and create an Area and SizeClass field.  Calculate the Area field using Calculate Geometry (Make sure you select square kilometers).  Calculate the SizeClass using the process outlined in III.e.  Note that the size classes used in the demo may not work for a different area.  When finished, show a screenshot of the attribute table.  Symbolize the layer by the SizeClass variable  (Layer Properties → Symbology Tab → Categories → Unique Values → Change the Value Field to Size Class → Add All Values) and show a screenshot of the full extent.

C). Follow VI.b to create a summary table of the average and total size for the soil types.  Show a screenshot of this table.

For the USGS Water Data

A). Create a new shapefile from the Water_Sites table (Section IV).  Give a screenshot of this new shapefile at full extent.  Set up the relate as outlined in Section V.  Show a screenshot of the Relate window.  Make a unique selection in either file, tell me what the selection is, and then show a screenshot of the two tables.

B). Create a unique summary table for the sites (as outlined in Section VI.c).  Do not use the one I did in the demo.  This can be any of the other Parameter values or the years (for example, after 1980 or between 1990 and 2000).  Tell me what this selection is and give a screenshot of the summary table alone, and the attribute table for Water_Sites_Spatial with the summary data joined on.

 

Module 8: Time and Temporal Data

Lecture Video 8: Time and Temporal Data

 

When spatial data also have a temporal component, this can be more difficult to visualize and analyze.  This module presents the tools that can be used to add a temporal level to GIS analysis.

Transcripts

Lecture 8 Notes

Demo 8 Video: Temporal Data

Transcripts

Demo 8 Notes

Module 8 Assignment

 

This module's assignment will be relatively simple.  I want to see that you have successfully visualized a few time layers and learned how to use the ArcGIS online basemap and search interfaces.

Now, show me the following things:

1). How many states were there in 1850? Note that this is more than just moving the time slider. You will also need to do a selection based on the attribute that tells you whether the polygons are states, territories or other entities. Give me the number and a screenshot of the map in 1850.

2). Symbolize the US_StatesHistorical layer according to whether each polygon is a state or not. Choose whatever colors you think make this clear. Export a movie at whatever interval you like and submit it along with your assignment

3). After adding the NetCDF precipitation data and the fire data, do you think there is a link between the rainfall and number of fires? What about time of year? Answer these questions and give me a few screenshots to illustrate your point.

Module 9: Making Maps

Lecture 9 Video: Making Maps

 

Once a GIS database is complete and analysis is finished, creating a final map for publication and/or presentation is almost always necessary.  In this module techniques and tools for creating effective maps are presented.

Transcripts

Lecture 9 Notes

Demo 9 Video: Cartography

Transcripts

Demo 9 Notes

Module 9 Assignment

 

Your only assignment for this module is to make three publication-quality final maps, export them as 2-300 dpi JPEGs and upload these to the assignment.  Please note, these are not screenshots, they are uploaded jpg files.

A few notes:

- Remember all maps should have a scale bar, north arrow and (most likely) a legend.

- There is no upper or lower limit to how many layers you have on the map.

- Unless it is obvious where your map is, it should also have coordinates

- Make sure you export JPEGs.  Screenshots in a word document will not count.  For once, you will be graded more on the final product than the process.

- You can make maps using whatever data you like

- Again, the data are not important, but your use of them are.  Do not give me meaningless data.  Make sure that if you put it on the map, it serves a purpose.  

- At least one of your maps should have a chart or table associated with it.

Module 10: Digital Terrain Models and Interpolation

Lecture 10 Video: Digital Terrain Analysis

 

Using Digital Terrain Models, a GIS analyst can quickly perform many different terrain analyses.  Terrain analysis tools are presented in this module.

Transcripts

Lecture 10 Notes

Demo 10 Video: Terrain

Transcripts

Demo 10 Notes

Module 10 Assignment

 

You should submit the following screenshots:

1). Your ArcMap document at the end of Section III.  You should only have the three clipped shapefiles present.  Make sure you are at the full extent.

2). The full extent of the TIN you build for the area around Notre Dame (Section IV).  

3). The DEM you create from the TIN (Section IV.d)

4). The Spline Interpolation for all of Michiana (Section V) with the color ramp changed to one of the two default elevation ramps.

5). A swipe comparing the SRTM Data to the raster DEM you created from your TIN (Section IV.d)

6). One of your topographic datasets (the raster DEM or your TIN) processed to show slope (either Section VII.d.2 or Section VII.e.5).

7). The other of your topographic datasets (the raster DEM or your TIN) processed to show aspect (either Section VII.d.3 or Section VII.e.5).  If you used the raster DEM for 6, this should be the TIN (and vice-versa)

8). A Hillshade calculation for the raster DEM (Section VII.d.4)

9). A new contour shapefile at 5 m interval created using the Contour tool in the Spatial Analyst (Section VII.d.5)

9). A single contour (Section VIII.c.3) or Steepest Path (Section VIII.c.4). created using the 3d Analyst toolbar.

10). A Line of Sight created using the 3d Analyst toolbar (Section VIII.c.5).

11).  A Profile Graph (Section VIII.c.7) for either the Line of Sight or for another 3d Line you made using the Interpolate Line tool (Section VIII.c.6).

Module 11: Basic Spatial Modeling

Lecture 11 Video: Basic Spatial Modeling

 

By combining several different layers of data, spatial models of to answer particular questions can be created in GIS.  This module provides examples of several types of spatial models and walks through the process of creating your own using relevant data.

Transcripts

Lecture 11 Notes

Demo 11 Video: Basic Spatial Modeling

Transcripts

Demo 11 Notes

Module 11 Assignment

This module's assignment is a bit different.  Rather than have you follow directly along the demo notes, I want to see that you understand the spatial modeling techniques.  Thus, you will need to think a bit about how you can use these tools as you do the following 4 things.

1). Do two Select by Location using the Indiana data.  These should be two-staged: First you should select features in one layer (ex. Schools in particular Zip Codes or Census Zones within a graphic). Then you use these features to select features in another layer (ex. Places within 10 km of the selected schools or roads that intersect the selected Census Zones). Do not repeat the example from the demo notes. One of these selections should include a Select by Graphic.  If you have trouble, just work through Section II.C.3 using different layers.  Give me a screenshot of each selection when it is done (try to keep the Select by Location window visible) and briefly describe what you did.

2). Do a Spatial Join between two layers.  This can be anything except what we did in the Demo (Towns and Zip Codes).  I want you to think about this a bit beforehand. What kind of data from one file would be useful in another layer?  Do not just grab two random files as join them.  Give me a screenshot of the Attribute Table of the new shapefile (after the join) and a brief description of what you did.

3). Follow Section III (Zonal Statistics) for the study area.  This is the only section that will be exactly like the demo.  Give me a screenshot of the Zonal Statistics raster (Section III.c) at the extent of your soils shapefile. I also want a screenshot of one of the tables created from Zonal Statistics as a Table (Section III.e).

4). Complete a spatial model with at least three different layers (like the hobo example above). For this part of the assignment, I want you to use the skills you learned in Sections IV. Distance Measurements and V. Raster Math to create a model of optimal locations around Notre Dame.  You should include at least three layers and use at least one Euclidean Distance and one Cost Weighted Distance (based on slope). These layers should then be reclassified to either a 1-10 (ordinal) or a 0/1 (binary) scale.  You will then use the raster calculator to combine them into a single layer representing suitability.  Show screenshots of each of the three reclassifications (with description of what it is and why you chose it) and a screenshot of the final model with a sentence or two discussing the best locations in your park.

What you decide to model is up to you, but here is another fanciful example that you are welcome to use:

It is some point in the near future and things are not going well.  A chemical spill from Gary has caused mutation among most domesticated species.  A DNA sequence previously thought to code for facial symmetry and ocular magnitude has activated protein chains causing latent aggressive tendencies in juvenile hosts.  Even worse, these protein chains are lethal to humans.  Cuteness now kills, and kittens* are the greatest threat humanity has ever faced. Chaos reigns over the Midwest as fuzzy terrors systematically decimate the populace. The airports are closed and Indiana is quarantined. Your only hope lies in retreat to less populated areas, where the lack of giant balls of yarn and sunbeams has thus far kept the kitten hordes at bay.  But the study area is a big place.  How will you know where the best areas are?  If only there was some System for analyzing Information about Geographic data.  But wait! You, plucky young GIS student, have exactly the right skills and data to model optimal locations for humanity's last stand!

Potential calculations may include:

  • Elevation ranked 1-10 with the highest elevations at 10.  These areas could be more easily protected.
  • Proximity to water ranked 1-10 with higher values being closer to water.  Kittens hate water.
  • Soils converted to a raster with most having a value of 1, but any sandy soils having a zero.  You don't want to live where the kittens are likely to go (pun intended).
  • Hillshade or aspect ranked 1-10 with shaded areas at 10 and brighter areas at 1. Kittens love sunbeams.

Module 12: Hydrology

Lecture 12 Video: Hydrology

 

Hydrological models can provide valuable insight into how water is likely to flow across a surface.  This module presents some of the existing hydrology tools available to GIS analysts.

Transcripts

Lecture 12 Notes

Demo 12 Video: Hydrology

Transcripts

Demo 12 Notes

Module 12 Assignment

 

This module's assignment will be a bit like the previous one, albeit with fewer homicidal kittens and more erosion risk calculations.  In essence, I want you to first follow the demo notes and create a hydrological model for the study area (flow direction, stream channels, etc).  You can then use these data with your previous material to create an accurate model of erosion risk.

Part 1:  I want to see the following to demonstrate that you have completed the demo. This part you do have to do

1). Screenshots comparing your raw DEM with your filled DEM (After Fill Sinks in Section III.b.4).  Make sure that they have the same symbology (ie color ramp).  This should be two screenshots.  Not a swipe.

2). Screenshots comparing the Flow Direction from your raw DEM with he Flow Direction from  your filled DEM (After Section III.b.6).  They do not have to have the exact same symbology, but make sure they are both set to “Unique Values” and that their symbology is visible in the Table of Contents.

3). A screenshot of your Flow Accumulation layer

4). A screenshot of the tool window used to make the Stream Raster. Depending on which method you used this will either be the Reclassify window or the Raster Calculator Window.

5). A screenshot of your Stream Order Raster.  This layer should be the only one visible and make sure its symbology is visible in the Table of Contents.

6). A screenshot of your final Streams shapefile symbolized as outlined in Section III.f.3 (Most likely Graduated Symbols).  For the screenshot, only the Streams Shapefile and your DEM should be visible, with the Streams on top and clearly visible. The image to the right is an example of how this should look.

7). A screenshot of the Flow Length raster with your final Streams Shapefile (symbolized as in #6) over it.

8). Screenshots comparing the Watersheds layer you made directly from the shapefile (Section IV.d.4) and the one you made using the Snap Pour Points layer (Section IV.d.6).  They do not have to be the same symbology, but make sure that the symbology for each is visible in the Table of Contents.

Part 2: Here, I want you to use methods from previous modules to model erosion risk.  I am not going to walk you though every step of this, but I will give an overview and references to where the methods are found.

One side note: As you do these it is a good idea to always change the Output Cell Size to 15 (or so) if you have the option (Features to Raster and the Distance tools). The calculations always take the lowest resolution of the inputs, so this will make sure you don't accidentally have a very low resolution.

The data you should use are:

1). Soil Types: Some soil types are more susceptible to erosion that others.

-The zip file contains a table called Soil_ErosionRisk.dbf.  This contains a numeric code (E_Risk) for erosion susceptibility from the SSURGO database.

- Join this table to your soils shapefile using the Soil_Code field (Module 07; Section II)

- Convert the resulting shapefile to a raster based on the E_Risk field (Module 11; Section V.e.2.ii).

2). Slope: Higher slopes are more likely to be eroded

- Reclassify your slope raster into 10 classes with 10 being the highest slope values (Module 11;Section V.e.2.iii).

3). Drainage: Areas near where water flows are more likely to be eroded.

- Create a raster representing distance from drainage channels (Module 11; Section IV.a)

- Reclassify the distance into 10 classes with the closest as a 10 (Module 11; Section V.e.2.iii).  You may want to do this manually as more than a few hundred meters away is unlikely to have an effect.

- Alternatively, you could reclassify a Flow Accumulation Raster into 10 classes (Module 11;Section V.e.2.iii).

4). Water: Areas that are already covered by water cannot be eroded.

- Covert the shapefile representing water into a raster (Module 11;Section V.e.2.ii).

- Reclassify into a binary raster with 1 representing areas without water and 0 representing water (Module 11; Section V.e.4.iv).

You should then create a single layer representing erosion risk by combining these four factors (Module 11; Section V.f).  Remember that water is a binary factor, so you will treat it a bit differently in the final equation.  

For this part of the assignment there are no formal screenshot requirements.  Instead you should decide what needs to be seen or reported.  At minimum you should show the process of how each factor was reclassified and weighted in the final layer.  Also, you should include a brief discussion of what areas are likely to be susceptible to erosion and why.  Feel free to email me with questions.

Module 13: Three-Dimensional Analyses and Visualization

Lecture 13 Video: Three-dimensional Visualization

 

Most modern GIS applications also have the ability to visualize data in three dimensions.  This module provides an overview of these tools.

Lecture 13 Notes

Demo 13 Video: Three-Dimensional Visualization

Transcripts

Demo 13 Notes

Module 13 Assignment

 

This module's assignment will combine skills learned in several previous modules.  In essence I want you to create a 3d building in the best possible location in the study area.  Your data should come from the following:

 

For your optimal location you can use either the last part of the Spatial Analysis module (the kittens) or the erosion risk from part 2 of the Hydrology module, part 2.   

In one of the better areas (low erosion risk or high kitten defense) create a new polygon shapefile representing the footprint of a building (like  NotreDame_Castle.shp).  This can be as simple (a barn) or complex (Versailles) as you like, but should contain more than one polygon and a field for the extrusion height.  This process is outlined in the Creating Vectors module.  Remember you should do this in ArcMap, not ArcScene

 

Now, show me the following things:

 

1). In ArcMap, the new layer and its attribute table in 2d.  Whichever layer you used to find the optimal location should be under it.  Give me a brief description of why you chose this location

2). In ArcScene, your DEM or TIN in 3d with one of the standard color maps and with a vertical exaggeration.

3). Your new building draped and extruded over this DEM or TIN.  Find a good camera angle before you take this screenshot.

4). Your new building draped and extruded over another raster layer.  This should be one of the satellite images from a previous lab.

5). You should then export two jpegs from different views and add them to the word document you submit.  Remember, this is different that a simple screenshot.  Alternatively you can record a movie, but make sure it is not too big to upload.  Less than 15 seconds should be ok.

Conclusion

Conclusion

 

Now that you have gone through these lectures and demonstrations, you should be familiar with the basic concepts of GIS:  data models, types of analyses, and the potential for these tools to contribute to your research.  This has been a quick overview, just scratching the surface of what GIS can do.  I encourage you to look further into topics of particular interest to you.  Finding academic papers and following their methods is a great way to sharpen your skills.  The community of GIS users online is broad and generally very helpful.  For complicated tasks, you may want to even look into a class on Python scripting to get the most out of your analyses.  Also, please do not hesitate to contact us here in the Center for Digital Scholarship if you have any questions or need to know where to look for particular data.