Remote Sensing

Below you will find lessons that cover how to find, download, work with, visualize and analyze remote sensing data in R or Python.

Work with MODIS remote sensing data in in R.

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

last updated: 15 Jun 2017

Clean remote sensing data in R - Clouds, shadows & cloud masks

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

last updated: 10 Jul 2017

Calculate a remote sensing derived vegetation index in R

A vegetation index is a single value that quantifies vegetation health or structure. In this lesson, we will review the basic principles associated with calculating a vegetation index from raster formated, landsat remote sensing data in R. We will then export the calculated index raster as a geotiff using the writeRaster() function.

last updated: 15 Jun 2017

Landsat remote sensing tif files in R

In this lesson we will cover the basics of using LAndsat 7 and 8 in R. We 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 we will plot the data using various 3 band combinations including RGB and color-infrared.

last updated: 15 Jun 2017

Introduction to spectral remote sensing data

This lesson overviews the key components of spectral remote sensing. We briefly overview: active vs passive sensors, the electromagnetic spectrum and space-borne vs airborne sensors.

last updated: 15 Jun 2017

Extract raster values using vector boundaries in R

This lesson reviews how to extract pixels from a raster dataset using a vector boundary. We can use the extracted pixels to calculate mean and max tree height for a study area (in this case a field site where we measured tree heights on the ground. Finally we will compare tree heights derived from lidar data compared to tree height measured by humans on the ground.

last updated: 15 Jun 2017

Classify a raster in R.

This lesson presents how to classify a raster dataset and export it as a new raster in R.

last updated: 15 Jun 2017

Plot histograms of raster values in R

This lesson introduces the raster geotiff file format - which is often used to store lidar raster data. We cover the 3 key spatial attributes of a raster dataset including Coordinate reference system, spatial extent and resolution.

last updated: 15 Jun 2017

Introduction to lidar raster data products

This lesson introduces the raster geotiff file format - which is often used to store lidar raster data. We cover the 3 key spatial attributes of a raster dataset including Coordinate reference system, spatial extent and resolution.

last updated: 26 Jul 2017