How could the content be improved?
We would like to re-arrange the episodes of the Lesson.
This is based on teaching experience, discussion, and comments in the teaching notes about alternate orders.
There is also a beta-lesson in the Incubator that adopts a vector-first approach (GeoSpatial for Urbanism). I think this is pretty strong evidence that the community agrees.
Along the way, we at UC-Santa Barbara talked about making it fewer episodes. Here is a proposed new order. The numbers of the outline items are the originating Episode number.
1 Intro to Vector Data
Project Setup
6 Import Vector Data
6 Spatial Data Attributes
6 Plot a vector layer
6 Vector Layer Metadata & Attributes
7 Query Vector Feature Metadata
7 Load the Data
Single point shapefile
7 Explore Values within One Attribute
Roads
7 Subset Features
7 Customize Plots
Types of Roads
8 Load the Data
8 Plotting Multiple Vector Layers
9 Working With Spatial Data From Different Sources
9 Import US Boundaries - Census Data
9 Read US Boundary File
9 U.S. Boundary Layer
2 Intro to Raster Data
1 View Raster File Attributes
1 Open a Raster in R
1 Understanding CRS in Proj4 Format
The presence of a crs is a strong indicator that you’re looking at
Geo data
1 Calculate Raster Min and Max Values
1 Raster Bands
2 Plot Raster Data in R
2 Plotting Data Using Breaks
2 Layering Rasters
5 Getting Started with Multi-Band Data in R
5 Raster Stacks in R
5 SpatRaster in R
3 Customizing output
13 Before and After
13 Adjust the Plot Theme
13 Adjust the Color Ramp
13 Refine Plot & Tile Labels
13 Change Layout of Panels
4 Export a GeoTIFF
New: Exporting data vs exporting graphics
4 Metadata and Projections
1 Dealing with Missing Data
1 Bad Data Values in Rasters
1 Create A Histogram of Raster Values
3 Raster Projection in R
3 Reproject Rasters
3 Deal with Raster Resolution
9 CRS Units - View Object Extent
9 Reproject Vector Data or No?
6 Spatial Metadata
5 Analysis
10 Spatial Data in Text Format
10 Import .csv
10 Identify X,Y Location Columns
10 .csv to sf object
10 Plot Spatial Object
10 Plot Extent
10 Export to an ESRI shapefile
6 Manipulating Rasters
11 Crop a Raster to Vector Extent
11 Crop a Raster Using Vector Extent
11 Define an Extent
11 Extract Raster Pixels Values Using Vector Polygons
buffers
11 Summarize Extracted Raster Values
11 Extract Data using x,y Locations
7 Raster Calculations
4 Raster Calculations in R
4 Two Ways to Perform Raster Calculations
4 Raster Math & Canopy Height Models
12 About Raster Time Series Data
12 RGB Data
12 Plotting Time Series Data
12 Scale Factors
12 Take a Closer Look at Our Data
12 View Distribution of Raster Values
14 Extract Summary Statistics From Raster Data
14 Calculate Average NDVI
14 Extract Julian Day from row names
14 Convert Julian Day to Date Class
14 Plot NDVI Using ggplot
14 Compare NDVI from Two Different Sites in One Plot
14 Remove Outlier Data
How could the content be improved?
We would like to re-arrange the episodes of the Lesson.
This is based on teaching experience, discussion, and comments in the teaching notes about alternate orders.
There is also a beta-lesson in the Incubator that adopts a vector-first approach (GeoSpatial for Urbanism). I think this is pretty strong evidence that the community agrees.
Along the way, we at UC-Santa Barbara talked about making it fewer episodes. Here is a proposed new order. The numbers of the outline items are the originating Episode number.
1 Intro to Vector Data
Project Setup
6 Import Vector Data
6 Spatial Data Attributes
6 Plot a vector layer
6 Vector Layer Metadata & Attributes
7 Query Vector Feature Metadata
7 Load the Data
Single point shapefile
7 Explore Values within One Attribute
Roads
7 Subset Features
7 Customize Plots
Types of Roads
8 Load the Data
8 Plotting Multiple Vector Layers
9 Working With Spatial Data From Different Sources
9 Import US Boundaries - Census Data
9 Read US Boundary File
9 U.S. Boundary Layer
2 Intro to Raster Data
1 View Raster File Attributes
1 Open a Raster in R
1 Understanding CRS in Proj4 Format
The presence of a crs is a strong indicator that you’re looking at
Geo data
1 Calculate Raster Min and Max Values
1 Raster Bands
2 Plot Raster Data in R
2 Plotting Data Using Breaks
2 Layering Rasters
5 Getting Started with Multi-Band Data in R
5 Raster Stacks in R
5 SpatRaster in R
3 Customizing output
13 Before and After
13 Adjust the Plot Theme
13 Adjust the Color Ramp
13 Refine Plot & Tile Labels
13 Change Layout of Panels
4 Export a GeoTIFF
New: Exporting data vs exporting graphics
4 Metadata and Projections
1 Dealing with Missing Data
1 Bad Data Values in Rasters
1 Create A Histogram of Raster Values
3 Raster Projection in R
3 Reproject Rasters
3 Deal with Raster Resolution
9 CRS Units - View Object Extent
9 Reproject Vector Data or No?
6 Spatial Metadata
5 Analysis
10 Spatial Data in Text Format
10 Import .csv
10 Identify X,Y Location Columns
10 .csv to sf object
10 Plot Spatial Object
10 Plot Extent
10 Export to an ESRI shapefile
6 Manipulating Rasters
11 Crop a Raster to Vector Extent
11 Crop a Raster Using Vector Extent
11 Define an Extent
11 Extract Raster Pixels Values Using Vector Polygons
buffers
11 Summarize Extracted Raster Values
11 Extract Data using x,y Locations
7 Raster Calculations
4 Raster Calculations in R
4 Two Ways to Perform Raster Calculations
4 Raster Math & Canopy Height Models
12 About Raster Time Series Data
12 RGB Data
12 Plotting Time Series Data
12 Scale Factors
12 Take a Closer Look at Our Data
12 View Distribution of Raster Values
14 Extract Summary Statistics From Raster Data
14 Calculate Average NDVI
14 Extract Julian Day from row names
14 Convert Julian Day to Date Class
14 Plot NDVI Using ggplot
14 Compare NDVI from Two Different Sites in One Plot
14 Remove Outlier Data