Remote Sensing - MODIS

Introduction to the CMIP and MACA v2 Climate Data

In this lesson you will learn the basics of what CMIP5 and MACA v 2 data are and how global climate data are downscaled to higher resolutions to support regional analysis.

last updated: 12 Nov 2020

Introduction to the NetCDF4 Hierarchical Data Format

In this lesson you will learn about that netcdf 4 data format which is a format, commonly used to store climate data. In later lessons you will learn how to open climate data using open source Python tools.

last updated: 12 Nov 2020

Introduction to the HDF4 Data Format

MODIS is remote sensing data that is stored in the HDF4 file format. Learn how to view and explore HDF4 files (and their metadata) using the free HDF viewer provided by the HDF group.

last updated: 12 Nov 2020

Calculate Vegetation Indices in Python

A vegetation index is a value that quantifies vegetation health or structure. Learn how to calculate the NDVI and NBR vegetation indices to study vegetation health and wildfire impacts in Python.

last updated: 11 Sep 2020

Introduction to Multispectral Remote Sensing Data in Python

Multispectral remote sensing data can be in different resolutions and formats and often has different bands. Learn about the differences between NAIP, Landsat and MODIS remote sensing data as it is used in Python.

last updated: 11 Sep 2020

Work with MODIS Remote Sensing Data in R.

In this lesson you will explore how to import and work with MODIS remote sensing data in raster geotiff format in R. You will cover importing many files using regular expressions and cleaning raster stack layer names for nice plotting.

last updated: 03 Sep 2019

Clean Remote Sensing Data in R - Clouds, Shadows & Cloud Masks

In this lesson, you will learn how to deal with clouds when working with spectral remote sensing data. You will learn how to mask clouds from landsat and MODIS remote sensing data in R using the mask() function. You will also discuss issues associated with cloud cover - particular as they relate to a research topic.

last updated: 30 Mar 2020

Work with MODIS Remote Sensing Data in Python

MODIS is a satellite remote sensing instrument that collects data daily across the globe at 250-500 m resolution. Learn how to import, clean up and plot MODIS data in Python.

last updated: 13 Mar 2020

Calculate NDVI in R: Remote Sensing Vegetation Index

NDVI is calculated using near infrared and red wavelengths or types of light and is used to measure vegetation greenness or health. Learn how to calculate remote sensing NDVI using multispectral imagery in R.

last updated: 03 Sep 2019