Remote sensing e-course

28-29 December, 2013

Fatwa Ramdani

Geoenvironment, Earth Science, Grad. School of Science

Outline • The first day of this course will focus in vegetation cover analysis

based on remotely-sensed data, Landsat OLI 8. The methods how to analyze and exploit the multispectral information for vegetation mapping will be illustrated. This lesson also provide the concept of color composite, basic algorithm theoretical of atmospheric correction, how to using formula in open source software.

• The second day will guide the students to the next level of analysis using Thermal Infrared Sensor, compare with the vegetation indices and different land use land cover class.

• In every section will be follow with the exercise and questions to allow student expand their understanding.

Course Goal and Objectives

• Understand the concept of false composite color

• Understand the basic algorithm theoretical of atmospheric correction

• Understand formula module function in open source software

• Understand the benefit of vegetation indices

• Understand basic cartography design and classification technique

• Understand the utility of TIRS bands

Intended Audience

• University student with basic level of knowledge in Remote Sensing studies

• Course Requirements:

– Internet access

– GRASS software (http://grass.osgeo.org/grass64/binary/mswindows/native/)

– QuantumGIS software (http://www.qgis.org/en/site/forusers/download.html)

– Download data here ()

1. Using remotely-sensed image to highlighted vegetation

• This lesson will focus in vegetation cover analysis based on remotely-sensed data, Landsat 5 TM, Landsat 7 ETM+, and OLI 8. The methods how to analyze and exploit the multispectral information for vegetation mapping will be illustrated. This lesson also provide the concept of color composite.

Resources:

• http://fatwaramdani.wordpress.com/2013/05/31/landsat-8-of-west-sulawesi/

• http://landsat.usgs.gov/L8_band_combos.php

2. Radiance and Reflectance

• The section will be discuss the basic concept of radiance and reflectance

Resource • http://www.exelisvis.com/Company/PressRoom/TabId/190/ArtMID/786/ArticleID/3377/3377.aspx

To understand more about how Satellite sensors work, it helps to remember that – As sunlight strikes Earth’s surface, some of it is absorbed, and some of it is reflected back into space.

Sunlight has visible light and infrared light, as well light of other wavelengths. Sunlight interacts with the objects it hits. Some of

it is absorbed and some of it is reflected by those objects.

We see the light that’s reflected from objects.

Photo: Diptarama

In this picture, IR is Infrared light R is red light G is green light B is blue light

Red, green, blue, and infrared light from the sun hit the tree and its leaves. Infrared and green light are reflected from the tree. Red and blue light are absorbed by the tree.

Activities!

• Import file using GRASS

• Explore basic statistics

• Rescale satellite images

• Apply greyscale and RGB composite

• Apply image enhancement (IHS)

3. Generating vegetation indices and produce thematic map

• This lecture will introduce the student to basic algorithm theoretical of Digital Numbers (DNs) conversions, atmospheric correction, how to using formula in open source software, variant of vegetation indices algorithm, and will be follow with the exercise and questions to allow student expand their understanding.

ACTIVITIES

• Converting DNs into Reflectance, calculate NDVI & WDRVI, assign colour.

Resource • https://landsat.usgs.gov/Landsat8_Using_Product.php

• http://fatwaramdani.wordpress.com/2010/12/02/optimizing-spectral-information-for-sensing-vegetation-properties/

Quiz?

• Why do we assign band to certain color? • How is the spatial distribution of vegetation density in

the study area? Which area has sparse, moderate, and dense vegetation cover? Could you distinguish it from false composite color?

• What is d2 value associated with 28 Dec 2013? • Why do we need to perform TOA radiance and TOA

reflectance? • Why the histogram and transect of WDRVI image and

NDVI image are different? • What impression do you get from the scatter chart of

the WDRVI against NDVI values?

End of first day

Questions?

6. Comparing near-natural colour composite to LST (Land Surface Temperature)

• The students will guide to comparing their land surface temperature map with near-natural colour composite using GRASS. Also they will guider more to explore command console in GRASS

Resources

• http://fatwaramdani.wordpress.com/2012/04/04/comparing-near-natural-colour-composite-to-lst-land-surface-temperature-using-grass/

4. Exploring Digital Numbers (DNs) of TIRS bands

• This lecture will introduce students how to explore the DNs of TIRS band using transect and histogram

ACTIVITIES!

• Converting DNs into Radiance

Resources

http://atmcorr.gsfc.nasa.gov/

http://atmcorr.gsfc.nasa.gov/Barsi_AtmCorr_SPIE05.pdf

https://landsat.usgs.gov/calibration_notices.php

5. Deriving surface temperature from TIRS band using GRASS

• This part will guide students how to derive surface temperature from TIRS band using GRASS

ACTIVITIES!

• Converting Radiance into Absolut temperature (Kelvin)

• Converting Absolut temperature into Celsius

• Save file and produce map using QuantumGIS

Resources • http://fatwaramdani.wordpress.com/2012/04/04/how-to-derive-surface-temperature-from-thermal-

band-using-grass/

Activities& Quiz!

• Read the LST values using transect line on the different land use land cover, record the coordinates, and create the tables. Record at least for 5 different land use land cover

• Read the vegetation indices value & LST values using transect line on the different land use land cover, and create the scatterplot

• Based on the above activites, analyse the result! Which class of land use land cover related to high land surface temperature, and which class related to the lower values?

Thank you!

Questions?