Earth Science - Fire

Remote Sensing to Study Wildfire

Learn about how scientists use remote sensing methods to study the impacts of wildfire through calculations of vegetation indices before and after wildfire.

last updated: 23 Oct 2018

Field Methods to Study Wildfire

Learn about how scientists use field survey methods to study the impacts of wildfire through measurements of biomass and soil.

last updated: 16 Oct 2018

An Overview of the Cold Springs Wildfire

The Cold Springs wildfire burned a total of 528 acres of land between July 9, 2016 and July 14, 2016. Learn more about this wildfire and how scientists study wildfire using both field and remote sensing methods.

last updated: 23 Oct 2018

Learn to Use NAIP Multiband Remote Sensing Images in Python

Learn how to open up a multi-band raster layer or image stored in .tiff format in Python using Rasterio. Learn how to plot histograms of raster values and how to plot 3 band RGB and color infrared or false color images.

last updated: 30 Oct 2018

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: 10 Jan 2018

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: 10 Jan 2018

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: 23 Oct 2018

Clean Remote Sensing Data in Python - 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: 06 Nov 2018

Landsat Remote Sensing tif Files in R

In this lesson you will cover the basics of using Landsat 7 and 8 in R. You will learn how to import Landsat data stored in .tif format - where each .tif file represents a single band rather than a stack of bands. Finally you will plot the data using various 3 band combinations including RGB and color-infrared.

last updated: 30 Jul 2018

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: 30 Jul 2018

How Multispectral Imagery is Drawn on Computers - Additive Color Models

In this lesson you will learn the basics of using Landsat 7 and 8 in R. You will learn how to import Landsat data stored in .tif format - where each .tif file represents a single band rather than a stack of bands. Finally you will plot the data using various 3 band combinations including RGB and color-infrared.

last updated: 08 Dec 2017