Topic outline

  • Advanced Remote Sensing 2022

    THE EXAM ON 31 MAY 2022 WILL BE ORGANIZED IN ROOM 201 (OTAKAARI 4).


    The course will be arranged     on campus (period V, spring 2022) and it involves sessions which require on site attendance (e.g., hands-on sessions with a measurement device). It will not be a remote or hybrid course. [Updated: 1 March 2022]

    Prerequisite: To attend this course, you must have completed either "Photogrammetry, laser scanning and remote sensing" (GIS-E1040) or "Earth observation" (ELEC-E4510).

    Satellite

    [Image credit: ESA / Astrium GmbH]


    Welcome to the fascinating world of Earth observation!


    Every point on the Earth is viewed from space several times per day! To make the most of this technological revolution, we must invest in know-how in handling and interpreting the massive data flow. Earth observation (EO), or the gathering of information about our planet’s physical, chemical and biological systems through the analysis electromagnetic data recorded by spaceborne and airborne instruments, is a rapidly growing discipline. In addition, most global environmental issues require global data sets which are only available through satellite instruments. The rapid expansion of the Earth observation sector urgently calls for experts who have sophisticated skills in processing and interpreting the data collected through the missions.

    Teacher-in-charge: Miina Rautiainen (miina.a.rautiainen@aalto.fi)



  • Course schedule and materials

    Course dates: April 19 - June 1, 2022

    Credits: 5 credits (~135 hours of work in six weeks)


    Theme #1: Theoretical background of optical Earth observation

    The course kick-off is on Tuesday 19 April at 10.15 am. We will go through course practicalities and assessment, and you will be divided into reading groups for an assignment (Assignment #6). During this week, you will study the theoretical basis of optical remote sensing (i.e., radiative transfer theory). You will review radiometric concepts (which should be familiar to you from your previous remote sensing studies) and apply them in calculations (Assignment #1). Next, you will learn about spectral modeling and physically-based reflectance models. You will apply a simple physically-based reflectance model to simulate multispectral satellite data for a forest area (Assignment #2).


    Theme #2: Building a professional career in Earth observation
    You will be introduced to the wealth of online resources available for Earth observation enthusiasts and experts (Assignment #3). You will also learn to use cloud computing (Google Earth Engine) in the analysis of satellite data (Assignment #4). We will also visit the European Space Agency's Business Incubation Hub in Espoo!

    Theme #3: Spectral measurements and analyses
    You will learn about analyses related to hyperspectral data, and how to measured spectral libraries as part of field surveys (Assignment #5). You will get hands-on experience in operating a spectrometer outdoors.

    Theme #4: Applications of Earth observation data
    You will learn about the role of satellite remote sensing in climate change research, with a focus on the global radiation budget and albedo. You will become acquainted with scientific literature on remote sensing, and     participate in group work related to scientific research in remote sensing (related to Assignment #6 ).


  • Assignments

    LIST OF ASSIGNMENTS

    Assignment #1
    The assignment will introduce you to basic calculations in spectral field measurements and will help you understand the relationships between different radiometric units commonly applied also in satellite and airborne remote sensing. (max 10 points)

    Assignment #2
    The assignment will introduce you to spectral modeling using a physically-based reflectance model. You will learn how to simulate multi- and/or hyperspectral satellite data, and will also get experience in implementing a simple spectral simulation model. (max 15 points)

    Assignment #3
    The assignment will introduce you to online resources and tools available for remote sensing specialists. You will respond to questions related to specific online tools and resources. (max 10 points)

    Assignment #4
    The assignment will introduce you to the use of cloud computing (Google Earth Engine) in e.g., time series analysis of global satellite products for extensive geographical areas. You will use your creativity and scientific research skills to study environmental changes based on optical satellite data. (max 20 points)

    Assignment #5
    The assignment will introduce you to field work in remote sensing and the use of a spectrometer in outdoor conditions. You will analyze a spectral library that you and your peers collect from Otaniemi! (max 15 points)

    Assignment #6
    The assignment will introduce you to applications of spectral data in scientific literature. You will read a scientific article in small groups and prepare a presentation to explain the topic to your fellow students.  (max 20 points)

    Podcast discussions: During the course, you will also listen to professional remote sensing related podcasts. When we meet, we will have discussions about the podcasts and what you thought about them! You can earn bonus points by participating in the group discussions.

    Deadlines for assignments:
    Assignment #1: Monday 25 April
    Assignment #2: Friday 6 May
    Assignment #3: Monday 9 May
    Assignment #4: Monday 16 May
    Assignment #5: Friday 20 May
    Assignment #6: Wednesday 25 May (seminar presentations)


  • Podcasts

    We will discuss Big Themes related to EO during our contact sessions. You can get bonus points for active participation in the group discussions! Please listen to the podcast(s) before attending our session -- the podcasts will serve as the basis/inspiration for our discussions. Here is the schedule:

    Tue 26.4. This week's theme is EO & entrepreneurship. As a preparation for our ESA BIC visit, we will discuss "Being self-employed in the Earth observation sector".

    Wed 4.5. This week's theme is EO & cloud computing. As a preparation for the Google Earth Engine (GEE) assignment, we will discuss the significance that cloud computing in EO can have in monitoring the global environment. We will listen to "Target Zero Hunger 08: Agriculture - the view from space" and "Satellites and cloud computing".

    Wed 11.5. This week's discussion theme is EO & global solidarity. Access to open Earth observation data can have a great societal impact in lower income countries. We will discuss this after listening to podcasts about the use of satellite data in Ghana and insuring West Africa's crops.

    Tue 17.5. This week's discussion theme is EO & climate change. For example, in our northern latitudes, insect outbreaks and wildfires are expected to increase as a result of the changing climate. We will discuss the overall role of EO in climate change monitoring after listening to podcasts about bark beetle outbreaks and wildfires.

  • Course assessment

    The course assessment is based on six mandatory assignments and a voluntary exam.  This means that you need to dedicate a considerable amount of time to assignments during the course -- the expected workload of the course is 135 hours. The assignments have been designed so that they develop different skills Earth observation experts need: writing skills, data analysis skills, modeling skills, critical thinking skills, professional discussion skills, presentation skills, group work skills, … A minimum of 50 points (and all assignment reports handed in) is required to pass the course. There is a possibility to earn bonus points from small extra assignments and podcast discussions. If you hand in an assignment late, five points per day will be deducted from the points you would have obtained had you handed in the assignment on time.

  • Extracurricular materials

    Tools

    Hyperspectral Data Analysis in R (the new hsdar package by Meyer & Lehnert, 2022)

    "An R software package which focuses on the processing, analysis and simulation of hyperspectral (remote sensing) data. The package provides a new class (Speclib) to handle large hyperspectral datasets and the respective functions to create Speclibs from various types of datasets such as e.g., raster data or point measurements taken with a field spectrometer. "


    Useful reading materials

    "Computer processing of remotely-sensed images". 2011. By Mather & Koch. Wiley & Blackwell publication. 434 p. (Available as e-book in Aalto. A good basic text book.)

    "Remote sensing of the environment". 2014 (or older editions). By Jensen. Pearson publications. (A good basic text book.)

    "Remote sensing of vegetation: principles, techniques, and applications". 2010. By Jones & Vaughan. Oxford University Press. 353 p. (An excellent book for those interested in vegetation!)

    "Hyperspectral remote sensing: principles and applications". 2008. By Borengasser, Hungate & Watkins. 119 p. (A basic text book for beginners.)

    "Quantitative Remote Sensing of Land Surfaces". 2004. By Liang. Wiley & Sons, Inc. Publication. 533 p. (A more advanced text book.)

    "Advances in Land Remote Sensing: System, Modeling, Inversion and Application". 2008. By Liang (ed.). Springer Science+Business Media. 497 p. (A more advanced book / collection of review articles by scientists.)


    Scientific journals in remote sensing

    If you are interested in the most recent developments in remote sensing data & methods, you need to start following scientific journals. The five most highly ranked scientific journals (according to ISI Thomson Reuters, latest listing) in this field are
    1)     Remote Sensing of Environment
    2)     ISPRS Journal of Photogrammetry and Remote Sensing
    3)     International Journal of Applied Earth Observation and Geoinformation
    4)     IEEE Transactions on Geoscience and Remote Sensing
    5)     Remote Sensing


    Earth observation and sustainability

    If you are interested in learning more about EO and sustainability, you can check out, for example, this article!


    Podcasts

    The Mapscaping podcast
    Eyes on Earth
    Scene from above


    Free webinars & other self study materials

    LearnEO! Online lessons in Earth observation (by European Space Agency)
    MOOCs offered by the European Space Agency
    Google Earth Engine self study materials

    Misc. links

    The European Association of Remote Sensing Companies
    A report of societal impact of space activities in Finland, published in March 2022 (in Finnish only)