Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
4 Hour(s) 21 Minute(s)
Language
English
Taught by
Minerva Singh
Rating
Course Overview
Pre-process and Analyze Satellite Remote Sensing Data With Free Software
ENROLL IN MY LATEST COURSE ON HOW TO LEARN ALL ABOUT BASIC SATELLITE REMOTE SENSING.
Are you currently enrolled in either of my Core or Intermediate Spatial Data Analysis Courses?
Or perhaps you have prior experience in GIS or tools like R and QGIS?
You don't want to spend 100s and 1000s of dollars on buying commercial software for imagery analysis?
The next step for you is to gain profIciency in satellite remote sensing data analysis.
MY COURSE IS A HANDS ON TRAINING WITH REAL REMOTE SENSING DATA WITH OPEN SOURCE TOOLS!
My course provides a foundation to carry out PRACTICAL, real-life remote sensing analysis tasks in popular and FREE software frameworks with REAL spatial data. By taking this course, you are taking an important step forward in your GIS journey to become an expert in geospatial analysis.
Why Should You Take My Course?
I am an Oxford University MPhil (Geography and Environment) graduate. I also completed a PhD at Cambridge University (Tropical Ecology and Conservation).
I have several years of experience in analyzing real life spatial remote sensing data from different sources and producing publications for international peer reviewed journals.
In this course, actual satellite remote sensing data such as Landsat from USGS and radar data from JAXA will be used to give a practical hands-on experience of working with remote sensing and understanding what kind of questions remote sensing can help us answer.
This course will ensure you learn & put remote sensing data analysis into practice today and increase your proficiency in geospatial analysis.
Remote sensing software tools are very expensive and their cost can run into thousands of dollars. Instead of shelling out so much money or procuring pirated copies (which puts you at a risk of prosecution), you will learn to carry out some of the most important and common remote sensing analysis tasks using a number of popular, open source GIS tools such as R, QGIS, GRASS and ESA-SNAP. All of which are in great demand in the geospatial sector and improving your skills in these is a plus for you.
This is an introductory course, i.e. we will focus on learning the most important and widely encountered remote sensing data processing and analyzing tasks in R, QGIS, GRASS and ESA-SNAP
You will also learn about the different sources of remote sensing data there are and how to obtain these FREE OF CHARGE and process them using FREE SOFTWARE.
In addition to all the above, you’ll have MY CONTINUOUS SUPPORT to make sure you get the most value out of your investment!
ENROLL NOW :)
Course Content
- 7 section(s)
- 55 lecture(s)
- Section 1 Introduction to Satellite Remote Sensing Data Analysis
- Section 2 Introduction to Optical Remote Sensing Data
- Section 3 Pre-Processing Optical Data
- Section 4 The Many Uses of Optical Data
- Section 5 Classification of Remote Sensing Satellite Data
- Section 6 Introduction to Active Remote Sensing Data: Synthetic Aperture Radar
- Section 7 BONUSES SECTION
What You’ll Learn
- Download different types of satellite remote sesning data for free, Have thorough knowledge of remote sensing- theoretical concepts and applications, Implement pre-processing techniques using R and QGIS, Carry out unsupervised classification of satellite remote sesning data, Carry out supervised classification of satellite remote sesning data, Implement machine learning algorithms on satellite remote sensing data in R, Carry out habitat suitability mapping using remote sensing and machine learning, Use other freely avaliable software tools such as Google Earth Engine and SNAP for RS data analysis
Skills covered in this course
Reviews
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LLisa D.
I had problem with having a blank (black) screen in some sessions, starting in 5. Then it turns out a very important R package (RStoolbox) is no longer supported. Then it turns out that Landsat no longer provides the Collection 1 data, as it is all now available with the pre-processing completed. So, while I was glad to learn some of the background theory of what is going on in the "black box" it really is a huge waste of time to try to follow along and install packages that no longer even remotely current for today's researchers.
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DDr. Surendra Singh Choudhary
This course briefly covered all remote sensing and related software to extract and classify different classes of features using satellites data
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PPedro chacon
Solid course. I feel like there are tons of programs to use for remote sensing. This course does a good job of introduce some and how to use them.
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SSeann Day
The delivery of the lecture is a little stilted. Previous courses seem to have a more practiced feel. It is good to see the pitfalls of some of the methods (like the download of LandSat directly into QGIS) but I do not think that it was worth the time. Maybe just a statement at the end of lecture 11 or 12 stating the problems that may occur. There seems to be a disconnect between data sets used in demonstrations within lectures and data sets that are available in the drop box.
