Background

Learning goals

  • Recap the basic principles of optical remote sensing
  • From radiance to reflectance
  • Learn how to measure with the ASD FieldSpec
  • Analyze lab spectroscopy measurements

Optical remote sensing

Optical remote sensing makes use of the radiation reflected by a surface in the visible (~400-700 nm), the near infrared (700-1300 nm) and shortwave infrared (1300-~3000 nm) parts of the electromagnetic spectrum. Spaceborne-/airborne-based remote sensing and field spectroscopy utilize the solar radiation as an illumination source. Lab spectroscopy utilize a lamp as an artificial illumination source.

Optical remote sensing via spaceborne sensors (left), field spectroscopy (middle) and laboratory spectroscopy (right).

The proportion of the radiation reflected by a surface depends on the surface’s spectral reflection, absorption and transmission properties and varies with wavelength. These spectral properties in turn depend on the surface’s physical and chemical constituents. Measuring the reflected radiation hence allows use to draw conclusions on a surface’s characteristic, which is the basic principle behind optical remote sensing.

Reflection, absorption and transmission by a surface (left). Spectral reflectance profile of vegetation with major factors determining the reflectance (right).

Radiance & reflectance

Optical sensors/spectrometers measure the radiation reflected by a surface to a certain solid angle in the physical quantity radiance. The unit of radiance is watts per square meter per steradian (W • m-2 • sr-1). A general problem related to the use of radiance as unit of measurement is the variation of radiance values with illumination. For example, the absolute incoming solar radiation varies over the course of the day as a function of the relative position between sun and surface and so does the absolute amount of radiance measured.

The quotient between measured reflected radiance and measured incoming radiance (Radiancereflected / Radianceincoming) is called reflectance. Reflectance provides a stable unit of measurement which is independent from illumination and is the percentage of the total measurable radiation, which has not been absorbed or transmitted.

A white reference is a surface with a reflectance property of nearly 100% across the visible, near infrared and shortwave infrared part of the electromagnetic spectrum. Accordingly, a radiance measurement of a white reference is the same as the measurment of incoming radiance. White reference measurments therefore serve for calculating the reflectence of a target surface. A typical material used as a white reference is spectralon. Spectralon is well suited due to its Lambertian reflectance characteristics, i.e., radiation is reflected from any incident illumination into all viewing directions equally.

White reference (left), measured reflected radiance of a white reference and target surface (middle) and calculated reflectance of the target surface (right).

Lab spectroscopy

Lab spectroscopy carried out with a non-imaging spectrometer allows us to exactly characterize the spectral properties of a surface. General advantages of lab spectroscopy are measurements under controlled conditions, e.g. a constant illumination source, flexible determination of distance and angle to the surface, instrument calibration to eliminate the noise from the signal, no atmospheric influence.

Schematic laboratory measurement setup with a non-imaging spectrometer.

The Analytical Spectral Devices (ASD) FieldSpec is a portable non-imaging spectrometer widely used in remote sensing research. The ASD FieldSpec allows both radiance and reflectance measurements in narrow contiguous spectral bands covering the visible, near infrared and shortwave infrared regions of the electromagnetic spectrum. The ASD FieldSpec is specifically designed for field surveys, however, can be also used in the laboratory.

This seminar session utilizes the ASD FieldSpec 3. This device has separate detectors for the VNIR (350-1000nm), the SWIR1 (1000-1800nm) and the SWIR2 (1800-2500nm) to measure the reflected radiance in 2151 bands. The measurement of each band can be described with a Gaussian response function, where the spectral resolution is the Full-Width-Half-Maximum (FWHM) and the spectral sampling interval is the distance between neighboring bands. The spectral resolution of the ASD FieldSpec 3 is 3 nm in the shorter and 10 nm in the longer wavelengths. Spectral sampling interval is 1.4 nm at 350 to 1000 nm and 2 nm at 100 to 2000 nm.

The ASD FieldSpec 3 as used in the laboratory and field, and its specifications.

Spectral resolution and spectral sampling interval of a Gaussian response function. (Source: Schaepman, 1998)

Session materials

Download the session materials from our shared repository.

Exercise

Calculate ground area

  • What is the ground area spotted by a spectrometer with an angular field-of-view of 25° when measuring with a distance of 0.5 m between the fiber optics and the surface?

Calculate reflectance

  • Calculate the reflectance spectra of a vegetation surface based on laboratory measurements with the ASD FieldSpec. Measurments of a white reference and the vegetation surface are provided in radiances in a comma-separated text file (‘asd_excercise.txt’).
  • Plot the reflectance spectrum in a diagram. Style the plot adequately, i.e, title, formatted axes, axis title including units, legend, etc.
  • Calculations and plotting can be carried out either with a spreadsheet or in the programming language R.

Example: Calculation and plotting with a Excel spreadsheet (you may use other software solutions like LibreOffice Calc)

Example: Reflectance calculation and plotting with R

# Introduction to Remote Sensing Winter 2020/2021
# Humboldt-Universität zu Berlin

# R script to convert measured radiance into reflectance

# Read measurements from online resource. Alternatively provide full file path to asd_exercise.txt
msr <- read.table('https://box.hu-berlin.de/f/f37686ea85ec4bc99ef9/?dl=1', sep=',', dec='.', header=T)

# Calculate reflectance 
msr$vegetation.reflectance <- msr$vegetation.radiance / msr$whitereference.radiance

# Create line plot of wavelength (x-axis) and reflectance (y-axis)
plot(x=msr$wavelength.nm, y=msr$vegetation.reflectance, 
     type='l', ylab='Reflectance', xlab='Wavelength (nm)')

Assignment

The aim of this assignment is to conduct several spectral measurements of different surfaces under laboratory conditions and to process and visualize the recorded spectra.

Lab measurments

Joint lab measurements with the ASD FieldSpec are unfortunately not be possible in this semester. Please watch this short video (includes sound), which illustrates how the measurements of your assignment were recorded.

Assignment data

Proceed with the laboratory data (‘asd_radiance_tile.txt’,‘asd_reflectance_leaf.txt’). As described in the lab measurment videos, the data sets contain multiple radiance measurements of a red tile and a white reference, and reflectance measurements of tree leaves of different vitality.

BaseName Description
meas.000 First radiance measurement of the white reference
meas.001-003 Radiance measurement of the red roof tile (horizontal position)
meas.004-006 Radiance measurement of the red roof tile (vertical position)
meas.007 Second radiance measurement of the white reference
meas.008-010 Reflectance measurements of green leaves
meas.011-013 Reflectance measurements of yellow leaves
meas.014-016 Reflectance measurements of dry leaves

Process & plot data

Process the laboratory data set to provide the following diagrams:

  • Diagram 1: Illustrates the 8 radiance measurements (meas.000-007).
  • Diagram 2: Illustrates the 6 radiance measurements (001-006) processed into reflectance. Use the mean of the two white reference measurements to calculate reflectance.
  • Diagram 3: Illustrates the 9 reflectance measurements (008-016).
  • Diagram 4: Illustrates 3 reflectance spectra of different vitality states of the leaves. To do so, calculate the mean reflectance spectra for each vitality state.

Note: Style each diagram properly, i.e. add a plot title, format axes, add axis title including units, add legend, etc.

Submission

  • Upload the diagrams as a PDF file on Moodle.

  • General submission notes: Submission deadline for the weekly assignment is always the following Monday at 10am. Please use the naming convention indicating session number and family name of all students in the respective team, e.g. ‘s01_surname1_surname2_surname3_surname4.pdf’. Each team member has to upload the assignment individually. Provide single file submissions, in case you have to submit multiple files, create a *.zip archive.


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