Climate Data Visualization and Analysis

An introduction to importing, visualizing, and analyzing climate data in MATLAB.
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Actualizado 16 mar 2023

Climate Data Visualization and Analysis

View on File Exchange or Open in MATLAB Online

MATLAB Versions Tested

Curriculum Module

Created with R2021b. Compatible with R2021b and later releases.

Information

This curriculum module contains interactive MATLAB® live scripts that teach the basics of how to import, visualize, and analyze climate data using MATLAB.

Background

You can use these live scripts as demonstrations in lectures, class activities, or interactive assignments outside class. This module covers importing, visualizing, and analyzing data. It also includes examples of analyzing temperature anomaly data and Arctic sea ice data, as well as using multispectral imaging data to characterize drought in Northern California.

The instructions inside the live scripts will guide you through the exercises and activities. Get started with each live script by running it one section at a time. To stop running the script or a section midway (for example, when an animation is in progress), use the image_0.png Stop button in the RUN section of the Live Editor tab in the MATLAB Toolstrip.

Contact Us

Solutions are available upon instructor request. Contact the MathWorks teaching resources team if you would like to request solutions, provide feedback, or if you have a question.

Prerequisites

This module assumes you have a basic understanding of MATLAB. If you do not, consider completing MATLAB Onramp before starting this module.

Getting Started

Accessing the Module

On MATLAB Online:

Use the image_1.png link to download the module. You will be prompted to log in or create a MathWorks account. The project will be loaded, and you will see an app with several navigation options to get you started.

On Desktop:

Download or clone this repository. Open MATLAB, navigate to the folder containing these scripts and double-click on ClimateVis.prj. It will add the appropriate files to your MATLAB path and open an app that asks you where you would like to start.

Ensure you have all the required products (listed below) installed. If you need to include a product, add it using the Add-On Explorer. To install an add-on, go to the Home tab and select image_2.png Add-Ons > Get Add-Ons.

Products

MATLAB® is used throughout. Tools from Image Processing Toolbox™, Statistics and Machine Learning Toolbox™, and Curve Fitting Toolbox™ are used as well.

Scripts

If you are viewing this in a version of MATLAB prior to R2023b, you can view the learning outcomes for each script here

GlobalTemperature.mlx

image_3.png In this script, students will...
- Load time-series temperature data into MATLAB
- Compare regional temperature trends using time-series plots
- Apply array indexing to compute changes to CO2 concentration
- Discuss correlation and autocorrelation of climate time-series data

ArcticSeaIce.mlx

image_4.png In this script, students will...
- Load and display Arctic sea ice extent GeoTIFF data
- Quantify Arctic sea ice extent using logical operators
- Use a for loop to analyze changes to Arctic sea ice from 1979 to 2021
- Compute the linear trend of Arctic sea ice extent

MultispectralImaging.mlx

image_5.png In this script, students will...
- List the spectral band designations for the Landsat 8 satellite
- Load and display single band images
- Use metadata to rescale a spectral band
- Create an RGB image from spectral bands

MultispectralIndices.mlx

image_6.png In this script, students will...
- Compute multispectral indices (NDVI and NDWI) from Landsat 8 data
- Analyze the reduction of reservoir area due to drought
- Superimpose a multispectral index on an RGB image
- Quantify changes to vegetation
- Apply image processing techniques, such as creating a binary mask and registering images

License

The license for this module is available in the LICENSE.md.

Related Courseware Modules

Regression Basics

image_7.png Available on: image_8.png image_9.png GitHub

Machine Learning for Regression

image_10.png Available on: image_11.png image_12.png GitHub

Machine Learning Methods: Clustering

image_13.png Available on: image_14.png image_14.png GitHub

Or feel free to explore our other modular courseware content.

Educator Resources

Contribute

Looking for more? Find an issue? Have a suggestion? Please contact the MathWorks teaching resources team. If you want to contribute directly to this project, you can find information about how to do so in the CONTRIBUTING.md page on GitHub.

© Copyright 2024 The MathWorks™, Inc

Citar como

Ryan Weinstein (2024). Climate Data Visualization and Analysis (https://github.com/MathWorks-Teaching-Resources/Climate-Data-Visualization-and-Analysis/releases/tag/v1.0.4), GitHub. Recuperado .

Compatibilidad con la versión de MATLAB
Se creó con R2021b
Compatible con cualquier versión desde R2021b
Compatibilidad con las plataformas
Windows macOS Linux
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Versión Publicado Notas de la versión
1.0.4.0

See release notes for this release on GitHub: https://github.com/MathWorks-Teaching-Resources/Climate-Data-Visualization-and-Analysis/releases/tag/v1.0.4

1.0.3

See release notes for this release on GitHub: https://github.com/MathWorks-Teaching-Resources/Climate-Data-Visualization-and-Analysis/releases/tag/v1.0.3

1.0.2

See release notes for this release on GitHub: https://github.com/MathWorks-Teaching-Resources/Climate-Data-Visualization-and-Analysis/releases/tag/v1.0.2

1.0.1

See release notes for this release on GitHub: https://github.com/MathWorks-Teaching-Resources/Climate-Data-Visualization-and-Analysis/releases/tag/v1.0.1

1.0.0

Para consultar o notificar algún problema sobre este complemento de GitHub, visite el repositorio de GitHub.
Para consultar o notificar algún problema sobre este complemento de GitHub, visite el repositorio de GitHub.