Lab: Computing Index Rasters

Introduction

There is an ever increasing availability of remotely sensed (RS) data for spatial analysis. Most recently, UAVs are being used to collect data at lower cost than ever before. However, to effectively use RS data, we need to know to georeference it, correct for sensor and atmospheric effects, and convert it into numerical values we can use.

Preparation

To save time, I've provided the following data sets for this lab. Make sure to download them ASAP.

• LandSat 7 Scene

Creating Index Rasters

Creating index rasters is done using the "Raster Math" tool. The tutorial below will walk you through how to create an NDVI raster from LandSat. The tutorial also describes how to create other indices's which you may complete if desired for extra credit.

Note that this tutorial was written for LandSat 5 data and the format of the metadata has changed a bit (i.e. you may need to look around for some of the values but they are there!). Also, not all the bands are required for NDVI which may save you a little time. Also note that the use of "CON()" has changed and you'll need to check the help information on how to use this function (don't use Reclassify as it will turn your pixels into integers).

Calculating Vegetation Indices's from Landsat 5 TM and Landsat 7 ETM+ Data

Then, create a point shapefile with at least 10 points within Humboldt County. For each of the following, extract the values at the points and compare them in a table.

• The values from your NDVI layer
• The land cover type from a National Land Cover Data (NLCD) data set
• The land use value from the Humboldt County Parcels shapefile
• A description of what GoogleMaps shows in satellite view

Finally, visit at least 2 of the sites and record what you see within 15 meters (radius) of the point.

Homework Turn-In

See Canvas for the Turn-in instructions.