View Earth by using Landsat image services

Click on "Try it Live" link below to view the earth by using Landsat image services that are updated on a daily basis with new Landsat scenes. You can view a different combination of Landsat bands such as Natural color, Infrared, vegetation index etc. by using the tools on the left panel of the map viewer. The web application highlights some of the capabilities for accessing Landsat image services powered by ArcGIS for Server, accessing AWS Landsat Public Dataset running on the Amazon Web Services Cloud. Source: ESRI

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Processing Landsat 8 images with SAC plugin for QGIS

Here is an excellent video that explains how Landsat 8 images can be downloaded and processed by using SAC (Semi-Automatic Classification) plugin for QGIS. It is an awesome tool that allows users to search through the Landsat database and use filters such as set date, select cloud cover precentage, define area of interest etc. Learn more about SAC plugin for QGIS.

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Cost effectiveness of Landsat data

USGS states that the economic value of just one year of Landsat data far exceeds the multi-year total cost of building, launching, and managing Landsat satellites and sensors! Landsat has been there for more than 42 years. We've been using Landsat images for various analysis. The efficacy of Landsat data in terms of cost effectiveness is massive! 

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Multi-scale information extraction of land cover from Landsat Imagery and DEM data

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.

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