Remote Sensing - Lidar

Crop Spatial Raster Data With a Shapefile in Python

Sometimes a raster dataset covers a larger spatial extent than is needed for a particular purpose. In these cases, you can crop a raster file to a smaller extent. Learn how to crop raster data using a shapefile and export it as a new raster in open source Python

last updated: 14 Feb 2020

Classify and Plot Raster Data in Python

Reclassifying raster data allows you to use a set of defined values to organize pixel values into new bins or categories. Learn how to classify a raster dataset and export it as a new raster in Python.

last updated: 06 Mar 2020

Open, Plot and Explore Raster Data with Python

Rasters are gridded data composed of pixels that store values, such as an image or elevation data file. Learn how to open, plot, and explore raster files in Python.

last updated: 06 Mar 2020

What is Raster Data

Rasters are gridded data composed of pixels that store values. Learn more about the structure of raster data and how to use them to store data, such as imagery or elevation values.

last updated: 14 Feb 2020

Extract Raster Values Using Vector Boundaries in R

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

last updated: 03 Sep 2019

Clip Raster in R

You can clip a raster to a polygon extent to save processing time and make image sizes smaller. Learn how to crop a raster dataset in R.

last updated: 13 Mar 2020

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: 13 Mar 2020

Create a Canopy Height Model With Lidar Data

A canopy height model contains height values trees and can be used to understand landscape change over time. Learn how to use LIDAR elevation data to calculate canopy height and change in terrain over time.

last updated: 03 Sep 2019

Plot Histograms of Raster Values in R

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

last updated: 03 Sep 2019

Introduction to Lidar Raster Data Products

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

last updated: 13 Mar 2020

What is Lidar Data

This lesson reviews what lidar remote sensing is, what the lidar instrument measures and discusses the core components of a lidar remote sensing system.

last updated: 03 Sep 2019

Compare Lidar to Measured Tree Height

To explore uncertainty in remote sensing data, it is helpful to compare ground-based measurements and data that are collected via airborne instruments or satellites. Learn how to create scatter plots that compare values across two datasets.

last updated: 06 Mar 2020

Extract Raster Values at Point Locations in Python

For many scientific analyses, it is helpful to be able to select raster pixels based on their relationship to a vector dataset (e.g. locations, boundaries). Learn how to extract data from a raster dataset using a vector dataset.

last updated: 13 Mar 2020

Compare Lidar With Human Measured Tree Heights - Remote Sensing Uncertainty

Uncertainty quantifies the range of values within which the value of the measurement falls - within a specified level of confidence. Learn about the types of uncertainty that you can expect when working with tree height data both derived from lidar remote sensing and human measurements and learn about sources of error including systematic vs. random error.

last updated: 06 Mar 2020