GEOG 400 Week 1 Lecture 2, Fall 21

Transcript

1. GEOG 400: Advanced GIS - Raster Week 1 – Lecture 2 What’s a Raster?
2. The GIS Certificate at Fort Lewis College
3. The GIS Certificate at Fort Lewis College Required Courses GEOG 310 – INTRO TO GIS/COMPUTER MAPPING [4] GEOG 315 – GIS PROGRAMMING AND WEB MAPPING [2, Fall] GEOG 350 – INTERMEDIATE GIS (VECTOR) [3, Spring] GEOG 400 – ADVANCED GIS (RASTER) [3, Fall]
4. The GIS Certificate at Fort Lewis College Required Courses GEOG 310 – INTRO TO GIS/COMPUTER MAPPING [4] GEOG 315 – GIS PROGRAMMING AND WEB MAPPING [2, Fall] GEOG 350 – INTERMEDIATE GIS (VECTOR) [3, Spring] GEOG 400 – ADVANCED GIS (RASTER) [3, Fall] Geoscience Track: GEOG 325 [4] (Remote Sensing) Elective Courses (choose one) Engineering Track: ENGR 205 [4, Odd Year Falls] (Engineering Surveying) AND MATH 121 [4] (Pre-Calc)
5. The GIS Certificate at Fort Lewis College Required Courses Elective Courses (choose one) Capstone (choose one) GEOG 499: Independent Study [1-3] GEOG 480: Internship in GIS [1-3] GEOG 310 – INTRO TO GIS/COMPUTER MAPPING [4] GEOG 315 – GIS PROGRAMMING AND WEB MAPPING [2, Fall] GEOG 350 – INTERMEDIATE GIS (VECTOR) [3, Spring] GEOG 400 – ADVANCED GIS (RASTER) [3, Fall] Geoscience Track: GEOG 325 [4] (Remote Sensing) Engineering Track: ENGR 205 [4, Odd Year Falls] (Engineering Surveying) AND MATH 121 [4] (Pre-Calc)
6. 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 This is generally an opportunity that you bring to the table, but we occasionally post opportunities. Talk with me outside of class to explore internship opportunities in the Durango area. 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.
7. 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 This is generally an opportunity that you bring to the table, but we occasionally post opportunities. Talk with me outside of class to explore internship opportunities in the Durango area. 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. For either of these, it’s your responsibility to contact a faculty member well in advance (i.e., the semester prior to starting) to arrange a project.
8. Thanks for listening! Now back to our regularly-scheduled GIS stuff: A quick review of GIS data models A short discussion about vector data A much longer introduction to raster data Things to think about when dealing with rasters: • Format • Resolution • Data Type • Bit Depth
9. Data models used in Geographic Information Systems [there are two different ways we can display spatial data on a computer screen] These two data models are at the foundation of every bit of future GIS work you’ll do Vector Data represent the world as points with exact locations. We can connect these points to form lines (or polylines), and close those lines in loops to form polygons. But they’re all points. Raster Data represent the world as pixels, or cells, where each cell has a particular value. A simple trick for telling the difference: Because vector data are just specific locations (points) in space, they won’t distort or pixelate, when zoomed in. Because raster data have a specific cell size, or resolution, they will become blurry/distorted/pixelated when zoomed in.
10. What’s a Vector? [the etymological definition]
11. Vector Data Types (there are only three of them): Point Line (connected points) Polygon (closed loop of points) A Fairly Rapid Introduction to Vector Data
12. 1 2 3 4 5 6 Point Number Point Color 1 Red 2 Blue 3 Green 4 Orange 5 Pink 6 Purple Vector Data Have Attributes: Point Data A Fairly Rapid Introduction to Vector Data
13. 1 2 3 4 5 6 Point Number Point Color 1 Red 2 Blue 3 Green 4 Orange 5 Pink 6 Purple Vector Data Have Attributes: Stream Name Dominant Species 1 Animas River Brown Trout 2 Junction Creek Rainbow Trout 3 Hermosa Creek Mountain Whitefish 1 2 3 Point Data Line Data A Fairly Rapid Introduction to Vector Data
14. 1 2 3 4 5 6 Point Number Point Color 1 Red 2 Blue 3 Green 4 Orange 5 Pink 6 Purple Vector Data Have Attributes: Stream Name Dominant Species 1 Animas River Brown Trout 2 Junction Creek Rainbow Trout 3 Hermosa Creek Mountain Whitefish 1 2 3 Lot Number Business Type 1 Maria’s Bookshop Retailer 2 Carver Brewing Restaurant 3 Himalayan Kitchen Restaurant 1 2 3 Point Data Line Data Polygon Data A Fairly Rapid Introduction to Vector Data
15. 1 2 3 4 5 6 Point Number Location 1 50º N, 53º W 2 30º N, 20º W 3 30º N, 10º E 4 20º S, 50º E 5 20º S, 25º W 6 30º S, 60º E Stream Length (km) 1 60 2 30 3 15 1 2 3 Point Data Line Data We can ask different questions of the data, depending on their type! A Fairly Rapid Introduction to Vector Data
16. 1 2 3 4 5 6 Point Number Location 1 50º N, 53º W 2 30º N, 20º W 3 30º N, 10º E 4 20º S, 50º E 5 20º S, 25º W 6 30º S, 60º E Stream Length (km) 1 60 2 30 3 15 1 2 3 Lot Number Area (m2) 1 2500 2 1800 3 1000 1 2 3 Point Data Line Data Polygon Data We can ask different questions of the data, depending on their type! A Fairly Rapid Introduction to Vector Data
17. A Fairly Rapid Introduction to Vector Data There are many vector data formats, but you’ll encounter three on the regular: 1. Comma-Separated Values (.csv) files • You can open these in any text editor (Notepad) or in Excel; • This is what’s called human-readable, and it’s super useful • These are used for point data, not lines or polygons • You’ll see these if you ever go collect data in the field • and bring it back to the office
18. A Fairly Rapid Introduction to Vector Data There are many vector data formats, but you’ll encounter three on the regular: 2. Keyhole Markup Language (.kmz, .kml) files • These get used in many GPS devices, but the most common place you’ll see them is in Google Earth • You can also bring them into ArcGIS and export them from ArcGIS • They can be used for points, lines, or polygons; small file size • We can’t read them, though
19. A Fairly Rapid Introduction to Vector Data There are many vector data formats, but you’ll encounter three on the regular: 3. Shapefiles (.shp, but really they’re composed of several small files) • Many GIS programs can load these, they’re preferred in ArcGIS • They can be used for points, lines, or polygons; small file size • We can’t read them
20. A Fairly Rapid Introduction to Vector Data There are many vector data formats, but you’ll encounter three on the regular: 3. Shapefiles (.shp, but really they’re composed of several small files) • Many GIS programs can load these, they’re preferred in ArcGIS • They can be used for points, lines, or polygons; small file size • We can’t read them
21. Some very dense information on shapefiles, but you’ll probably want to return to this slide for reference REQUIRED OPTIONAL IMPORTANT
22. Some very dense information on shapefiles, but you’ll probably want to return to this slide for reference REQUIRED OPTIONAL IMPORTANT IF YOU WANT TO SEND SOMEONE A SHAPEFILE, YOU’VE GOTTA SEND THEM ALL THESE!
23. What’s a Raster? [the etymological definition]
24. 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
25. 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
26. Rasters represent the world as a continuous grid of cells Vectors represent the world as points (and subsequently lines, and polygons) SQL Server Rider
27. 2.bp.blogspot.com Rasters represent the world as a continuous grid of cells Vectors represent the world as points (and subsequently lines, and polygons)
28. Let’s go to the farm.
29. Let’s rasterize the farm. What’s in the BLUE cell?
30. What’s in the BLUE cell? VALUE = HORSE Let’s rasterize the farm.
31. What’s in the BLUE cell? Let’s rasterize the farm.
32. What’s in the BLUE cell? VALUE = TURKEY Let’s rasterize the farm.
33. What’s in the BLUE cell? VALUE = COW Let’s rasterize the farm.
34. What’s in the BLUE cell? Let’s rasterize the farm.
35. What’s in the BLUE cell? VALUE = NOTHING …or ‘NULL’ …or ‘NO DATA’ Let’s rasterize the farm.
36. What’s in the BLUE cell? Let’s rasterize the farm.
37. What’s in the BLUE cell? VALUE = some NO DATA some DUCK some PIGEON DIGEON? NODATA? PIGEON? Let’s rasterize the farm.
38. Are our raster cells big enough… to resolve a pig? to resolve a pigeon?
39. 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
40. 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
41. 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
42. 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
43. 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
44. 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
45. 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
46. 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
47. 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…
48. 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? Can anybody think of a question that’s much easier to answer with vectors?
49. Excellent uses of raster data E. AERIAL IMAGERY
50. Not-so-excellent uses of raster data Things with discrete boundaries between them (e.g., states, cities, counties, nations)
51. Not-so-excellent uses of raster data Things that are inherently linear (e.g., streams)
52. 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
53. Not-so-excellent uses of raster data Things that are inherently Point-based (e.g., GPS surveys, animal capture locations) Arizona Daily Star
54. Not-so-excellent uses of raster data Individual structures Google Maps
55. 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
56. 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
57. 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.
58. 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.
59. Raster Considerations 3: Data Type Discrete (or thematic, or categorical) rasters divide the world into a number of categories, which are assigned different symbologies
60. Raster Considerations 3: Data Type Continuous (or field, or surface) rasters display a continuous gradient of information across a color ramp
61. 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?
62. 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
63. 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
64. 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
65. 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
66. 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 NoData (stream or not stream)
67. Let’s go through a quick (5-10 minute) exercise. courses.fortlewis.edu