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This course focuses on a range of remote sensing and geospatial science applications in the Arctic domain. Based on a brief introduction of fundamental remote sensing principles, this course will discuss general change detection applications, will introduce methods for the monitoring of snow and water; and teach remote sensing methods for wildfire analysis. In the final module, the course will discuss increasing landslide hazards in the Arctic and reveal how shallow and deep-seated landslides can be mapped using optical and radar remote sensing. All these applications are actors of change in the Arctic and impact geospatial intelligence applications such as the assessment of Arctic domain trafficability.
This course enables students to solve real-world problems using Geographical Information Systems (GIS) and remote sensing. Students will acquire skills in data management, vector, and raster analysis. They will work with elevation data and point coordinates in a GIS environment and learn how to assess data accuracy in GIS.
Remote sensing observations from airborne and spaceborne platforms have become an essential tool for monitoring environmental change. This is especially true for the Arctic, where accelerated climate warming has caused exceptional changes of landscape and ecosystems, and where the vastness and remoteness of the landscape has made remote sensing an indispensable observational tool.
In light of this need for remote sensing, this course focuses on a range of geospatial science applications in the Arctic domain. Example applications include general change detection, the monitoring of snow and water; the analysis of wildfires, and the mapping and assessment of landslides. All these applications are actors of change in the Arctic and impact geospatial intelligence applications such as the assessment of Arctic domain trafficability.
This course includes the following modules:
Module 0: Introduction to the Course
Module 1: Monitoring Environmental Change From Imagery
Module 2: Mapping Snow Cover with the Normalized Difference Snow Index
Module 3: Wildfire Mapping Concepts
Module 4: Landslide Mapping using Remote Sensing
Learners on the Verified Track will put their learned knowledge into action in data analysis exercises related to all four course modules. In these exercises, learners who select the verified track will have access to online computational labs using ArcGIS pro and Jupyter notebooks. These will facilitate a deeper immersion into the subject matter.
Specific knowledge learners must have to be successful in the course.
General proficiency in GIS (similar to what is being taught here)
Basic proficiency in the concepts of Remote Sensing
For verified track: Basic knowledge in Python programming
Participants in this course will develop the following skills:
Intuitive understanding of SAR image and phase information
Understanding of the use of remote sensing data for snow and water mapping
Experience in mapping active wildfires from thermal remote sensing data
Understanding of how to map burn scars using multispectral remote sensing data
Expertise in calculating landslides susceptibility from remotely sensed data and in mapping landslide areas and impacts
Understanding how to measure the movement of deep-seated landslides using interferometric SAR techniques
Week 1: Introduction to the Course and Environmental Change Detection Techniques
Week 1 will introduce you to the main content and structure of this course. In this first week, you will also learn about methods to detect and map environmental changes using remote sensing data. The following items will be addressed:
Introduction to course
Presentation of course syllabus
Introduction to the concept of change detection and the sensor types used in this module
Basic principles and capabilities of Synthetic Aperture Radar (SAR) imaging
Introduction to SAR-based change detection techniques
Verified Track: Lab exercise on change detection from SAR observations
Week 2: Snow and Water Monitoring Using Remote Sensing Data
This module exposes you to remote sensing methods for the mapping of snow and water. Both are significant obstacles in the Arctic, affecting mobility and access to the landscape. We will mostly use multispectral remote sensing sensors for this task. Specifically, in Week 2 we will address:
The concepts of mapping snow, ice, and water with remote sensing
What is the Normalized Difference Snow Index (NDSI), how is it derived, and what are its applications
Methods for mapping water from remote sensing images
An application of snow and water mapping techniques to a 2015 spring flooding event in northern Alaska
Verified Track: Lab exercise exploring flood mapping techniques from optical remote sensing
Week 3: Wildfire Mapping From Remote Sensing
As temperatures have risen in the Arctic, wildfires have become an ever-present hazard in the Arctic domain. In this module, we will explore wildfire remote sensing and will discuss techniques for monitoring active fires and mapping wildfire burn scars. Specifically, week 3 will discuss the following:
What are the concepts of wildfire remote sensing
How to detect active fires using thermal remote sensing
Mapping of burned area and burn severity using the Normalized Burn Ratio (NBR)
Verified Track: In lab exercises, students on the verified track will explore active fire services and will work on hands-on exercises to map burned area for recent fire events
Week 4: Landslide Mapping using Remote Sensing
The accelerated warming of the Arctic in recent decades has led to a rapid increase of landslide activity especially in sloped terrain. This is partly because the thawing of permafrost has reduced the integrity of soils. Additionally, receding mountain glaciers have reduced buttressing of unstable soils and caused the activation of landslides in many mountain valleys.
Remote sensing is an indispensable tool for monitoring these activities across the vast reaches of the Arctic. Therefore, week 4 of this course will discuss the following:
What are landslides, what causes them, and how can they be categorized
What are shallow landslides and how can remote sensing help in calculating the susceptibility of a landslide to produce shallow landslides
How can shallow landslides risks be determined using remote sensing observations
What are deep-seated landslides and what are their properties
What is InSAR and how can it be used to detect deep-seated landslides and measure their motion
Verified Track: In lab exercise students on the verified track will explore landslide susceptibility maps and analyze landslide motion using InSAR techniques
Who can take this course?
Unfortunately, learners residing in one or more of the following countries or regions will not be able to register for this course: Iran, Cuba and the Crimea region of Ukraine. While edX has sought licenses from the U.S. Office of Foreign Assets Control (OFAC) to offer our courses to learners in these countries and regions, the licenses we have received are not broad enough to allow us to offer this course in all locations. edX truly regrets that U.S. sanctions prevent us from offering all of our courses to everyone, no matter where they live.
Who can take this course?
Unfortunately, learners residing in one or more of the following countries or regions will not be able to register for this course: Iran, Cuba and the Crimea region of Ukraine. While edX has sought licenses from the U.S. Office of Foreign Assets Control (OFAC) to offer our courses to learners in these countries and regions, the licenses we have received are not broad enough to allow us to offer this course in all locations. edX truly regrets that U.S. sanctions prevent us from offering all of our courses to everyone, no matter where they live.
