GEOG 400, Advanced GIS, Fall 2020; Week 1 Lecture 2

Transcript

1. GEOG 400: Advanced GIS - Raster Week 1 – Lecture 2 What’s a Raster?
2. A brief plug for two upper-level courses! If you are pursuing a certificate in GIS at Fort Lewis… 1. GEOG 480 Internship in GIS (1, 2, or 3 credits) 2. GEOG 499 Independent Study (1, 2, or 3 credits) 1 credit hour equates to 50 work hours! Work (not necessarily paid) with an outside employer that consists of at least 50% GIS We’ll help you set this up, but feel free to bring your own employment ideas to the table! Contact Scott White (white_s@fortlewis.edu) to arrange enrollment and an internship Individual research conducted in collaboration with an FLC faculty member; for the GIS certificate, this is a GIS-oriented project. Final product can be written report, set of maps, online repository of products, etc. Contact me or a faculty member of interest if you’d like to pursue a GIS independent study project.
3. Introduce Yourselves! 1. Your name 2. Your major 3. Your previous GIS experience/courses 4. Whether you’ve used ArcPro 5. A landscape that has meaning to you
4. What’s a Raster? [the etymological definition]
5. What’s a Raster? [our practical definition] A raster is a regularly spaced grid of cells, or pixels. -Me Raster data models define space as discrete cells, in which each cell has a value associated with it that represents certain characteristics of that area. - Bolstad, GIS Fundamentals
6. Let’s go to the farm.
7. Let’s rasterize the farm. What’s in the BLUE cell?
8. What’s in the BLUE cell? VALUE = HORSE Let’s rasterize the farm.
9. What’s in the BLUE cell? Let’s rasterize the farm.
10. What’s in the BLUE cell? VALUE = TURKEY Let’s rasterize the farm.
11. What’s in the BLUE cell? VALUE = COW Let’s rasterize the farm.
12. What’s in the BLUE cell? Let’s rasterize the farm.
13. What’s in the BLUE cell? VALUE = NOTHING …or ‘NULL’ …or ‘NO DATA’ Let’s rasterize the farm.
14. What’s in the BLUE cell? Let’s rasterize the farm.
15. What’s in the BLUE cell? VALUE = some NO DATA some DUCK some PIGEON NODIGEON? Let’s rasterize the farm.
16. Are our raster cells big enough… to resolve a pig? to resolve a pigeon?
17. What’s a Raster? [our practical definition] A raster is a regularly spaced grid of cells, or pixels. -Me Raster data models define space as discrete cells, in which each cell has a value associated with it that represents certain characteristics of that area. - Bolstad, GIS Fundamentals
18. But wait, there’s more! In Intro GIS, you might have discussed two data types, raster and vector What’s the difference?
19. But wait, there’s more! In Intro GIS, you might have discussed two data types, raster and vector What’s the difference? Rasters represent the world as a continuous grid of cells Vectors represent the world as points (and subsequently lines, and polygons) SQL Server Rider
20. But wait, there’s more! In Intro GIS, you might have discussed two data types, raster and vector What’s the difference? Rasters represent the world as a continuous grid of cells Vectors represent the world as points, lines, and polygons 2.bp.blogspot.com
21. Is this a raster or vector data model? Rasters represent the world as a continuous grid of cells Vectors represent the world as points, lines, and polygons You’ll get really good at doing this quickly, but the most intuitive way? Just zoom in. Vectors are discrete points or connected points, so they’ll always be sharp Rasters are pixels of a given size, so they’ll get “pixelated” or blurry up close. Shutterstock Adobe
22. Is this a raster or vector data model? Rasters represent the world as a continuous grid of cells Vectors represent the world as points, lines, and polygons A map of wetlands in the Rocky Mountains
23. Is this a raster or vector data model? Rasters represent the world as a continuous grid of cells Vectors represent the world as points, lines, and polygons An aerial photo of the Rocky Mountains
24. Is this a raster or vector data model? Rasters represent the world as a continuous grid of cells Vectors represent the world as points, lines, and polygons A map of elevations around Flagstaff, AZ
25. Is this a raster or vector data model? Rasters represent the world as a continuous grid of cells Vectors represent the world as points, lines, and polygons A map of elevations around Flagstaff, AZ
26. Cool, then why not always just use vectors? Because over large areas, vector data is much, much slower to display and analyze. Arc will let you convert rasters to vectors easily, but it probably shouldn’t…
27. Cool, then why not always just use vectors? And often, rasters just make more sense to answer certain questions. How big is the patch of pine forest in the map? What if the house was twice as large? What’s the area of water in the map?
28. Excellent uses of raster data E. AERIAL IMAGERY
29. Not-so-excellent uses of raster data Things with discrete boundaries between them (e.g., states, cities, counties, nations)
30. Not-so-excellent uses of raster data Things that are inherently linear (e.g., streams)
31. Not-so-excellent uses of raster data Things that are inherently Point-based (e.g., GPS surveys, animal capture locations) Rubke and O’Donnell, 2019 Ferierabend and Kielland, 2015 Flickr
32. Not-so-excellent uses of raster data Things that are inherently Point-based (e.g., GPS surveys, animal capture locations) Arizona Daily Star
33. Not-so-excellent uses of raster data Individual structures Google Maps
34. Raster Considerations 1: Format Raster data come in many formats; here are a few you might see regularly JPEG (.jpg); developed by joint photographic experts group; your standard phone/camera format PDF (.pdf); can house either raster or vector data, so be careful here!; used for many old topo maps PNG (.png); ‘portable network graphics’; low file sizes, used for many web images IMG (.img) TIFF (.tif); ‘tagged image file format’; many air photos and elevation rasters ESRI GRID (no extension); beware of many file name constraints TEXT BASED RASTERS (.asc, .txt); useful for data storage, human-readable, but require some pre-processing for display and often aren’t georeferenced
35. Raster Considerations 1: Format Raster data come in many formats; here are a few you might see regularly JPEG (.jpg); developed by joint photographic experts group; your standard phone/camera format PDF (.pdf); can house either raster or vector data, so be careful here!; used for many old topo maps PNG (.png); ‘portable network graphics’; low file sizes, used for many web images IMG (.img) TIFF (.tif); ‘tagged image file format’; many air photos and elevation rasters ESRI GRID (no extension); beware of many file name constraints TEXT BASED RASTERS (.asc, .txt); useful for data storage, human-readable, but require some pre-processing for display and often aren’t georeferenced
36. Raster Considerations 2: Resolution Raster resolution is a delicate balancing act between the information you want to convey and the size (and processing time) of the file you’re dealing with.
37. Raster Considerations 2: Resolution Raster resolution is a delicate balancing act between the information you want to convey and the size (and processing time) of the file you’re dealing with. “1 m resolution” “0.5 m resolution” 1 m 1 m 1 m 1 m To DOUBLE the resolution, we have to QUADRUPLE the cells So be very careful, because files can get really big, really fast.
38. Raster Considerations 3: Data Type Discrete (or thematic, or categorical) rasters divide the world into a number of categories, which are assigned different symbologies
39. Raster Considerations 3: Data Type Continuous (or field, or surface) rasters display a continuous gradient of information across a color ramp
40. Raster Considerations 4: Bit Depth The information held in each cell, and its precision, varies between different raster types. What might a cell’s value be in each of these rasters?
41. Raster Considerations 4: Bit Depth The information held in each cell, and its precision, varies between different raster types. What might a cell’s value be in each of these rasters? Value = 921.24 m
42. Raster Considerations 4: Bit Depth The information held in each cell, and its precision, varies between different raster types. What might a cell’s value be in each of these rasters? Value = 921.24 m
43. Raster Considerations 4: Bit Depth The information held in each cell, and its precision, varies between different raster types. What might a cell’s value be in each of these rasters? Value = 921.24 m Value = ‘Mixed Forest’ or Value = 22
44. Raster Considerations 4: Bit Depth The information held in each cell, and its precision, varies between different raster types. What might a cell’s value be in each of these rasters? Value = 921.24 m Value = ‘Mixed Forest’ or Value = 22
45. Raster Considerations 4: Bit Depth The information held in each cell, and its precision, varies between different raster types. What might a cell’s value be in each of these rasters? Value = 921.24 m Value = ‘Mixed Forest’ or Value = 22 Value = 1 or 0 (stream or not stream)
46. A quick (5-10 minute) exercise and discussion