Introduction
The main purpose of this study is to perform a multi-scale information extraction of land cover and vegetation structure from Landsat TM imagery and DEM data, using classification and statistical modeling methods. This study also aims to evaluate the results of the analysis through accuracy statistics and meaningful map productions. The data available for this study is a TM Landsat image of the Hinton and Jasper, Alberta area with channels, 1 to 5 and 7. A channel containing a DEM of the area and three additional channels with tasseled cap (TCA) outputs are also provided.
Additionally, three shape files containing land cover, leaf area index (LAI) and Crown closure are also available. These shape files are in the form of points and are basically used to create training sites and assess the accuracy of the results. The land cover shape file is a file containing 437 land cover calls made by field personnel observing a 90 x 90 meter area roughly equivalent to nine TM pixels. The leaf area index shape file is a file containing 37 estimates of LAI obtained by field personnel using an Accupar Ceptometer over a 30 x 30 meter ground plot roughly equivalent to one TM pixel. The crown closure shape file contains 73 estimates of crown closure measured by field personnel using spherical densiometers over a 30 x 30 meter ground plot roughly equivalent to one TM pixel.
The land cover shape file is used to create a classified image. The LAI and crown closure shape files are used to predict the LAI and Crown closure values for the entire Landsat scene. With the help of these datasets, it is possible to produce multiple maps that can be used to explore the relations hips between LAI, crown closure and the process that are taking place on the ground. The main objective of this study is to produce two maps that can demonstrate how these different sets of data can be used to generate meaningful information at different scales.
Read entire article (It is password protected. Please contact me for liable access to this article.)
