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| # Geospatial Analysis with R <img src="https://s28151.pcdn.co/offices/marketing-and-communications/wp-content/blogs.dir/3/files/sites/106/2019/08/CU_Seal_Red_SM_60_75_v4-768x768.png" align="right" width="120" /> | ||
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| ## Spring 2023 | ||
| ## Spring 2024 | ||
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| Updated on: `r Sys.Date()` | ||
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| <center> | ||
| ------------------ ------------------------------------------------------ | ||
| Instructor Michael Cecil ([email protected]) | ||
| Teaching assistant Arman Bajracharya | ||
| Instructor Lyndon Estes | ||
| Teaching assistant Vanchy Li | ||
| ------------------ ------------------------------------------------------ | ||
| </center> | ||
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@@ -41,75 +41,48 @@ The class materials were designed by Lyndon Estes and Lei Song. | |
| - [Module 2](unit1-module2.html) - R and R fundamentals | ||
| - [Module 3](unit1-module3.html) - Data preparation and operation | ||
| - [Module 4](unit1-module4.html) - Data manipulation and visualization | ||
| - [Unit1 practice answers](unit1-practice-answers.html) - Answers and code for Unit1 practice | ||
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| - [Unit 2](unit2.html) - Overview | ||
| - [Module 1](unit2-module1.html) - Vector data | ||
| - [Module 2a](unit2-module2a.html) - Raster data, part 1 | ||
| - [Module 2b](unit2-module2b.html) - Raster data, part 2 | ||
| - [Unit2 practice answers](unit2-practice-answers.html) - Answers and code for Unit2 practice | ||
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| - [Potential Projects](projects.html) | ||
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| ## Course content | ||
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| - Week 1 (Jan 18) | ||
| - Week 1 (Jan 17) | ||
| - Setup | ||
| - [Class 1 slides](class1.html) | ||
| - Week 2 (Jan 23, 25) | ||
| - Week 2 (Jan 22, 24) | ||
| - Using git and Github; R packages; | ||
| - [Class 2 slides](class2.html) | ||
| - [Class 3 slides](class3.html) | ||
| - Assignment 1 due (Unit 1 Module 1) | ||
| - Week 3 (Jan 30, Feb 1) | ||
| - Week 3 (Jan 29, Jan 31) | ||
| - Continued setup work, RMarkdown, R ecosystem | ||
| - [Class 4 slides](class4.html) | ||
| - [Class 5 slides](class5.html) | ||
| - Week 4 (Feb 6, 8) | ||
| - Week 4 (Feb 5, 7) | ||
| - R data structures, OOP, Environments, Control flow | ||
| - [Class 6 slides](class6.html) | ||
| - [Class 7 slides](class7.html) | ||
| - Assignment 2 due (Unit 1 Modules 2-3) | ||
| - Week 5 (Feb 13, 15) | ||
| - Week 5 (Feb 12, 14) | ||
| - tidyr universe, working with data | ||
| - [Class 8 slides](class8.html) | ||
| - [Class 9 slides](class9.html) | ||
| - Week 6 (Feb 20, 22) | ||
| - Week 6 (Feb 19, 21) | ||
| - regression, plotting | ||
| - [Class 10 slides](class10.html) | ||
| - [Class 11 slides](class11.html) | ||
| - Assignment 3 due (Unit 1 Module 4) | ||
| - Week 7 (Feb 27, Mar 1) | ||
| - Week 7 (Feb 19, 21) | ||
| - more ggplot, intro to vector | ||
| - [Class 12 slides](class12.html) | ||
| - [Class 13 slides](class13.html) | ||
| - Spring Break | ||
| - Week 8 (Mar 13, 15) | ||
| - Week 8 (Feb 26, 28) | ||
| - Vector operations | ||
| - [Class 14 slides](class14.html) | ||
| - [Class 15 slides](class15.html) | ||
| - Assignment 4 due (Unit 2 Module 1) | ||
| - Week 9 (Mar 20, 22) | ||
| - Week 9 (Mar 11, 13) | ||
| - Raster basics | ||
| - [Class 16 slides](class16.html) | ||
| - Mar 22 online (AAG) | ||
| - Week 11 (Mar 27, 29) | ||
| - Week 11 (Mar 18, 20) | ||
| - Raster analysis, neighborhoods | ||
| - Mar 27 project prep (AAG) | ||
| - [Class 17 slides](class17.html) | ||
| - Week 12 (Apr 3, 5) | ||
| - Week 12 (Mar 25, 27) | ||
| - Raster algebra, terrain, modeling | ||
| - [Class 18 slides](class18.html) | ||
| - [Class 19 slides](class19.html) | ||
| - Assignment 5 (Unit 2 Module 2) | ||
| - Week 13-15 (Apr 10, 12, 17, 19, 24, 26, May 1) | ||
| - Project Overview due (Apr 16) | ||
| - [Class 20 slides (leaflet, plotly)](class20.html) | ||
| - [Random Forest - raster classification](wur_rf_demo.html) | ||
| - [Random Forest - ground sensors](sensor_rf_demo.html) | ||
| - [rgee - install](rgee_install.html) | ||
| - [rgee - examples](rgee_examples.html) | ||
| - [Shiny apps](rshiny.html) | ||
| - Week 13-15 (April) | ||
| - Project Overview due | ||
| - Final Projects due | ||
| - May 8 | ||
| - May 5 | ||
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| # Geospatial Analysis with R <img src="https://s28151.pcdn.co/offices/marketing-and-communications/wp-content/blogs.dir/3/files/sites/106/2019/08/CU_Seal_Red_SM_60_75_v4-768x768.png" align="right" width="120" /> | ||
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| ## Spring 2023 | ||
| ## Spring 2024 | ||
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| Updated on: 2023-04-17 | ||
| Updated on: 2024-01-17 | ||
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| <center> | ||
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| | | | | ||
| |:-------------------|:------------------------------------| | ||
| | Instructor | Michael Cecil (<[email protected]>) | | ||
| | Teaching assistant | Arman Bajracharya | | ||
| | | | | ||
| |:-------------------|:-------------| | ||
| | Instructor | Lyndon Estes | | ||
| | Teaching assistant | Vanchy Li | | ||
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| </center> | ||
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| ## Resources | ||
|
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||
| - [Syllabus](syllabus.html) | ||
| - [Assessment Criteria](assessment.html) | ||
| - [Software installation](software-installation.html) | ||
| - [Git/GitHub](git-github.html) | ||
| - [Known bugs and fixes](bugs-fixes.html) | ||
| - [Syllabus](syllabus.html) | ||
| - [Assessment Criteria](assessment.html) | ||
| - [Software installation](software-installation.html) | ||
| - [Git/GitHub](git-github.html) | ||
| - [Known bugs and fixes](bugs-fixes.html) | ||
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| ## Links | ||
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| - [Helpful functions](helpful_functions.html) | ||
| - [Cheatsheets](cheatsheets.html) | ||
| - [Helpful functions](helpful_functions.html) | ||
| - [Cheatsheets](cheatsheets.html) | ||
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| ## Course materials | ||
|
|
||
| The class materials were designed by Lyndon Estes and Lei Song. | ||
|
|
||
| - [Unit 1](unit1.html) - Overview | ||
| - [Module 1](unit1-module1.html) - Reproducibility and related R | ||
| skills | ||
| - [Module 2](unit1-module2.html) - R and R fundamentals | ||
| - [Module 3](unit1-module3.html) - Data preparation and operation | ||
| - [Module 4](unit1-module4.html) - Data manipulation and | ||
| visualization | ||
| - [Unit1 practice answers](unit1-practice-answers.html) - Answers | ||
| and code for Unit1 practice | ||
| - [Unit 2](unit2.html) - Overview | ||
| - [Module 1](unit2-module1.html) - Vector data | ||
| - [Module 2a](unit2-module2a.html) - Raster data, part 1 | ||
| - [Module 2b](unit2-module2b.html) - Raster data, part 2 | ||
| - [Unit2 practice answers](unit2-practice-answers.html) - Answers | ||
| and code for Unit2 practice | ||
| - [Potential Projects](projects.html) | ||
| - [Unit 1](unit1.html) - Overview | ||
| - [Module 1](unit1-module1.html) - Reproducibility and related R | ||
| skills | ||
| - [Module 2](unit1-module2.html) - R and R fundamentals | ||
| - [Module 3](unit1-module3.html) - Data preparation and operation | ||
| - [Module 4](unit1-module4.html) - Data manipulation and visualization | ||
| - [Unit 2](unit2.html) - Overview | ||
| - [Module 1](unit2-module1.html) - Vector data | ||
| - [Module 2a](unit2-module2a.html) - Raster data, part 1 | ||
| - [Module 2b](unit2-module2b.html) - Raster data, part 2 | ||
| - [Potential Projects](projects.html) | ||
|
|
||
| ## Course content | ||
|
|
||
| - Week 1 (Jan 18) | ||
| - Setup | ||
| - [Class 1 slides](class1.html) | ||
| - Week 2 (Jan 23, 25) | ||
| - Using git and Github; R packages; | ||
| - [Class 2 slides](class2.html) | ||
| - [Class 3 slides](class3.html) | ||
| - Assignment 1 due (Unit 1 Module 1) | ||
| - Week 3 (Jan 30, Feb 1) | ||
| - Continued setup work, RMarkdown, R ecosystem | ||
| - [Class 4 slides](class4.html) | ||
| - [Class 5 slides](class5.html) | ||
| - Week 4 (Feb 6, 8) | ||
| - R data structures, OOP, Environments, Control flow | ||
| - [Class 6 slides](class6.html) | ||
| - [Class 7 slides](class7.html) | ||
| - Assignment 2 due (Unit 1 Modules 2-3) | ||
| - Week 5 (Feb 13, 15) | ||
| - tidyr universe, working with data | ||
| - [Class 8 slides](class8.html) | ||
| - [Class 9 slides](class9.html) | ||
| - Week 6 (Feb 20, 22) | ||
| - regression, plotting | ||
| - [Class 10 slides](class10.html) | ||
| - [Class 11 slides](class11.html) | ||
| - Assignment 3 due (Unit 1 Module 4) | ||
| - Week 7 (Feb 27, Mar 1) | ||
| - more ggplot, intro to vector | ||
| - [Class 12 slides](class12.html) | ||
| - [Class 13 slides](class13.html) | ||
| - Spring Break | ||
| - Week 8 (Mar 13, 15) | ||
| - Vector operations | ||
| - [Class 14 slides](class14.html) | ||
| - [Class 15 slides](class15.html) | ||
| - Assignment 4 due (Unit 2 Module 1) | ||
| - Week 9 (Mar 20, 22) | ||
| - Raster basics | ||
| - [Class 16 slides](class16.html) | ||
| - Mar 22 online (AAG) | ||
| - Week 11 (Mar 27, 29) | ||
| - Raster analysis, neighborhoods | ||
| - Mar 27 project prep (AAG) | ||
| - [Class 17 slides](class17.html) | ||
| - Week 12 (Apr 3, 5) | ||
| - Raster algebra, terrain, modeling | ||
| - [Class 18 slides](class18.html) | ||
| - [Class 19 slides](class19.html) | ||
| - Assignment 5 (Unit 2 Module 2) | ||
| - Week 13-15 (Apr 10, 12, 17, 19, 24, 26, May 1) | ||
| - Project Overview due (Apr 16) | ||
| - [Class 20 slides (leaflet, plotly)](class20.html) | ||
| - [Random Forest - raster classification](wur_rf_demo.html) | ||
| - [Random Forest - ground sensors](sensor_rf_demo.html) | ||
| - Final Projects due | ||
| - May 8 | ||
| - Week 1 (Jan 17) | ||
| - Setup | ||
| - [Class 1 slides](class1.html) | ||
| - Week 2 (Jan 22, 24) | ||
| - Using git and Github; R packages; | ||
| - Assignment 1 due (Unit 1 Module 1) | ||
| - Week 3 (Jan 29, Jan 31) | ||
| - Continued setup work, RMarkdown, R ecosystem | ||
| - Week 4 (Feb 5, 7) | ||
| - R data structures, OOP, Environments, Control flow | ||
| - Assignment 2 due (Unit 1 Modules 2-3) | ||
| - Week 5 (Feb 12, 14) | ||
| - tidyr universe, working with data | ||
| - Week 6 (Feb 19, 21) | ||
| - regression, plotting | ||
| - Assignment 3 due (Unit 1 Module 4) | ||
| - Week 7 (Feb 19, 21) | ||
| - more ggplot, intro to vector | ||
| - Spring Break | ||
| - Week 8 (Feb 26, 28) | ||
| - Vector operations | ||
| - Assignment 4 due (Unit 2 Module 1) | ||
| - Week 9 (Mar 11, 13) | ||
| - Raster basics | ||
| - Week 11 (Mar 18, 20) | ||
| - Raster analysis, neighborhoods | ||
| - Mar 27 project prep (AAG) | ||
| - Week 12 (Mar 25, 27) | ||
| - Raster algebra, terrain, modeling | ||
| - Assignment 5 (Unit 2 Module 2) | ||
| - Week 13-15 (April) | ||
| - Project Overview due | ||
| - Final Projects due | ||
| - May 5 |
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