This is the main communication site for the course. Here you will find the lectures, readings, and assignments. This is a place to visit regularly.
The purpose of this course is to strengthen the theoretical foundations of remote sensing and to develop the student's skills for digital image processing and analysis. This course focuses on developing critical thinking to conduct research using earth observation data.
The course syllabus is available at this link
Week 1 – Remote sensing and digital image processing – Cap. 1 from Jensen (2015)
Topics:
- ¿What is remote sensing?
- ¿What is a remote sensing system?
- ¿What are advantages and limitations of remote sensing?
- ¿What is the remote sensing process?
- ¿What are the key characteristics of digital images?
In-class exercises:
- Search and download satellite images
- Visualize multispectral images
Independent work:
Week 2 - Electromagnetic radiation – Cap. 2 from Campbell (2022)
- The Electromagnetic Spectrum
- Major Divisions of the Electromagnetic Spectrum
- Radiation Laws
- Interactions with the Atmosphere
- Interactions with Surfaces
In-class exercises:
- TBW
Independent work:
Week 3 – Remote sensing of vegetation - Cap. 11 from Jensen (2014)
- Leaves
- Plants
- Canopies
In-class exercises:
- Start Module 3 below
Independent work:
- Replicate these tutorials with data for your study area:
- Module 3: Raster interpretation and visualization
- Module 4: Moving Data In and Out of Google Earth Engine
- Download IDEAM landcover data from here
REFERENCIA
Week 4 – The real potential of remote sensing to map aboveground biomass in tropical forests (Nidhi, 2022)
Topics:
- Presentation of Nidhi's article
- Discussion D
In-class exercises:
- Start module 5 below
Independent work:
- Replicate these tutorials with data for your study area:
Week 5 – Image interpretation – Cap. 6 from Campbell (2022)
- What is image interpretation?
- Why image interpretation is useful?
- Image Interpretation Tasks
- Elements of Image Interpretation
- Classification schemas
In-class exercises:
- Start module 6 below
Independent work:
- Replicate this tutorial with data for your study area:
- Create "fichas técnicas" for the land cover classes you are interested in:
In-class exercises:
- Follow these tutorials with data for your study area:
Independent work:
- Replicate this tutorial with data for your study area:
In-class exercises:
- Follow this tutorial with data for your study area:
Students will submit the first report before 22th March at 12:00 midnight (25% of the final grade)
Independent work:
- Do the second iteration of your random forest (RF) land cover classification in GEE
- Make sure you document each iteration
Topics:
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Essential reference:
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Additional references:
Students enrolled in the course will write the first examination on 29th March (25% of the final grade)
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Make sure you register in the canvas platform before coming to the classroom
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Independent work:
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Topics
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Reference
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Independent work:
- TBD
See the recording of this week lecture here
Topics:
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- What is ML?
- What are decision trees (DT)?
- What are random forests (RF)?
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In-class exercise:
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Independent work
- Adapt the sampling generation exercise to your image analysis problem
Topics:
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In-class exercise:
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Independent work
- In case it is useful, adapt the GEE RF code to analyze your own images
Topics:
Reference:
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In-class exercise:
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Independent work
- Continue iterating & writing your Informe No. 2
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Topics:
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In-class exercise:
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Readings:
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Independent work:
- Include textural metrics in your covariables dataset and examines its effects
- Continue iterating & writing your Informe No. 2
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Topics:
- There is no face-to-face class.
- Instead, make sure you attend the following virtual sessions from NASA (and take notes):
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Independent work:
- Complete & revise your Informe No. 2
- Plazo para entrega de Informe No. 2
- 24 de Mayo - 2:00 pm -
- Impresión a color
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Topics:
- There is no face-to-face class.
- Instead, make sure you attend the following virtual session from NASA (and take notes):
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Independent work:
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Complete & revise your Informe No. 2
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Nuevo plazo para entrega de Informe No. 2
- 26 de Mayo - dejarlo en Oficina 333 antes de las 11:59 am -
- Impresión a color
- Sobre sellado marcado con su nombre
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Study for Examen No. 2 (to be written on 31 May at 2:00 pm)
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