Remote Sensing of the Environment

Instructor: Jawairia Ahmad, Centre for Water Informatics & Technology (WIT)

Email: jawairia.ahmad@lums.edu.pk

Office: 9-213, Maxwell Wing, 2nd Floor, SBASSE Building

TA: Talha Nadeem

Email:  TBD 

Office:  TBD 

Course Description

This course will cover the fundamental principles of remote sensing of the environment. Contemporary remote sensing techniques, software, and datasets will be discussed. Geographic and hydrometeorologic datasets will be used to study the application of the electromagnetic theory to retrieve information about the Earth’s system via satellite constellations. The course is designed to help students develop a broad understanding of the importance of remote sensing in comprehending and monitoring our environment. The remote-sensing skills gained through this course could be easily applied to other fields as well. 

Course Details

Offering

  • Year: 2023
  • Semester: Spring
  • Open for Student Categories: Juniors, Seniors, Graduates
  • Credits Hours: 3
  • Lecture Timings: Tuesdays and Thursdays at 3:00-4:15pm

Prerequisites

  • Junior and Senior Students : MATH120 Calculus
  • Graduate Students: None

Co-requisites

  • Introductory programming skills (in MATLAB or Python) are preferred

Textbooks

The textbooks are not mandatory as open source material relevant to the lecture topics will also be shared. In addition, the lectures are designed to be self-sufficient.

  • (Jensen) Remote sensing of the environment: An earth resource perspective 2/e. Pearson Education.
  • (Qihao) An Introduction to Contemporary Remote Sensing, 1stEd, McGraw-Hill, U. K.
  • (Margulis) Introduction to Hydrology. Including a MATLAB-Based Modular Distributed Watershed Educational Toolbox (MOD-WET).
  • Supplementary Reading: Weekly readings will be assigned prior to each lecture

Lecture Breakdown

 

Week

Topics

Book Chapters/ Recommended Reading

Week 1

Lecture 1 - Remote sensing’s role in the 21st century

Lecture 2 - Introduction to electromagnetic radiations

Jensen Ch 1, Ch 2

video

Week 2

Lecture 3 - Principles governing electromagnetic radiations; Angular distribution of radiation

Lecture 4 - Absorption and scattering by macroscopic particles; Spectral signatures; absorption windows

Jensen Ch 4

video

video

Week 3

Lecture 5 - Multispectral remote sensing systems

  • Digital image terminology
  • Landsat multispectral scanner
  • Landsat thematic mapper

Lab Tutorial 1: Accessing geospatial data

Jensen Ch 6

reading

Week 4

Lecture 6 - Thermal infrared (TIR) remote sensing  

  • Thermal infrared atmospheric windows
  • Thermal radiation laws

Lecture 7 - Thermal infrared (TIR) remote sensing  

  • Thermal infrared data collection
  • Environmental considerations

Jensen Ch 7

video

Week 5

Lecture 8 - Active microwave (AM) remote sensing

  • AM system components
  • Radar backscatter

Lecture 9- Active microwave (AM) remote sensing

  • Radar backscatter sample data analysis
  • Synthetic Aperture Radar (SAR)
 Jensen Ch 8

video

Week 6

Lecture 10 - Passive microwave (PW) remote sensing 

  • Radiometer components  
  • Brightness temperature
  • Emissivity of surfaces

Lab Tutorial 2: Using QGIS

 Jensen Ch 8

video

Week 7

Lecture 11 - LIDAR remote sensing

  • LIDAR laser and scanning system
  • Post-processing multiple returns
  • Digital Surface Model (DSM)
  • Digital Terrain Model (DTM)

Field visit

  • Multispectral camera
  • LIDAR

Jensen Ch 9

video

Week 8

Guest lecture on remote sensing applications

 

Lecture 12 - Gravimetry-based remote sensing

  • Gravimetric principles of remote sensing  
  • Gravity Recovery and Climate Experiment (GRACE)
 video

 

                                            Midterm Examination 

 

Week 10

Lecture 13 - Remote sensing of vegetation  

  • Spectral characteristics of vegetation
  • Bidirectional Reflectance Distribution Function (BRDF)

Lecture 14 -  Remote sensing of vegetation

  • Digital number conversion to radiation
  • Vegetation indices
  • Land cover classification and LandSat data analysis
 Jensen Ch 10

reading

Week 11

Lecture 15 - Remote sensing of water

  • Cloud formation
  • Precipitation development

Lecture 16 - Remote sensing of water

  • Spectral characteristics of precipitation
  • RADAR reflectivity
  • Precipitation data analysis
 Jensen Ch 11

video

Week 12

Lab Tutorial 3

Lecture 17 - Remote sensing of water

  • Spectral properties of snow 
  • Snow cover and snow depth
 Jensen Ch 11

video

Week 13

Lecture 18 - Remote sensing of water

  • Dielectric constant- real and imaginary components  
  • Fresnel equations  
  • Biophysical characteristics of surface water
  • El Nino and La Nina

Lab tutorial 4 

 Jensen Ch 11

video

Week 14

Lecture 19 - Remote sensing of landscape

  • Topography mapping
  • Urban vs. rural landscape
  • NASA Shuttle Radar Topography Mission (SRTM) 

Guest lecture on remote sensing applications

 Jensen Ch 13

video

Week 15

 Project Presentations  

Week 16

 Final Examination