Remote Sensing of Vegetation, Soil and Water Systems

Professor: Laurent Tits, Ben Somers, seminars by PhD students

Examenvorm: Written

Examentaal: English

2020

1) What are RTM? Why are they used in remote sensing? What are their advantages and distadvantages? Explain in detail PROSPECT and SAIL.

2) What is RUE? Illustrate with a figure. What are its assumptions? Give 2 situations where these assumptions don't apply.

3) Explain both the passive and active microwave characteristics from an agricultural field using illustrations. What are the main components? How is SM deduced from this and what are the components that have a large influence hereon?

4) Set up a plant species diversity monitoring program for 't Zwin (nature reserve) which inhibits different ecosystems with a limited budget.

5) Set up a monitoring program for all individual street trees in Leuven to know the chlorophyll content, leaf area index and water content of each tree. The city is rich so has unlimited budget.

2015-2016

In total: 65 marks on the exam

1) Fluorescence: what methodology can you use to derive fluorescence? (10)

2) What is compositing? Why and how is it done? Give examples of methodologies. (10)

3) What are plant optical types? How can they be applied to investigate plant characteristics? (5)

4a) What effect have the following factors on the spectral signatures of vegetation in the VIS, NIR and SWIR part of the spectrum. Explain with some graphs. (15)

- Beetle attack on Eucalyptus

- Iron deficiency on pear orchards, resulting in chlorosis

- Long period of drought

4b) Describe the 3 different methodologies seen in class to extract a biophysical parameter of interest from a hyperspectral data set. What are their pro's and con's? Which one of them requires external data? What kind of data? (15)

4c) One of the methods in 4a requires an extra data processing step. Explain (= spectral unmixing/masking). (5)

5) INBO wants to map and monitor all plant species in "Het Zwin" (forests, dunes, ...). What methodology would you apply to classify these? What sort of data, validation, ... would you need? (5)

2014 - 2015

40 marks are on the 3 reports, 60 marks on the exam. The exam consisted of 6 questions. First 3 theoretical questions, each on 5 points. Then a there was a more practical part on 45 points where you have to apply different methodologies seen in class.

1) What are the advantages and limitations of terrestrial and airborne LiDAR data collection? (5)

2) Explain the Fraunhofer Line Depth method. (5)

3) What are plant optical types? How can they be applied to investigate plant characteristics?

4a) What effect have the following factors on the spectral signatures of vegetation in the VIS, NIR and SWIR part of the spectrum. Explain with some graphs. (15)

- Iron deficiency, resulting in chlorosis

- Long period of drought

- Young vs. old leafs

4b) Describe the 3 different methodologies seen in class to extract a biophysical parameter of interest from a hyperspectral data set. What are their limitations? Which one of them requires external data? How should this external data be applied? (15)

4c) One of the methods in 4b requires an extra data processing step. Explain (= compositing). (5)

5) Something about invasive species detection. (5)

6) You have 2 different landcovers: forestry and grassland. What methodology would you apply to classify these? What sort of data would you need? (5)

2013 - 2014

There is about one question form each chapter of the exam.

1) A graph with a modelled LAI and estimated LAI using remote sensing.

a) What kind of function is this? Name or equation?

b) Why are there growth delays near the end of the season?

c) The LAI is dervided from remote sensing data and then used to calibrate the model. Which strategy is employed here? Explain.

2) What effect have the following factors on the spectral signature of leaves between 350-2500 nm (sketch) and give the biophysical causes

a) Shade vs sunlit

b) Monocots vs dicots

c) Succulent vs Non-Succulent plants

d) very young leaves vs young leaves vs mature leaves vs senescented leaves

3) Explain the difference between hyper- and multispectral remote sensing. What are advantages and disadvantages?

4) What type of ground-based LiDAR is most comparable with airborne LiDAR? Argumentation? Hardware components?

5) Is the radiospectrometer shown in the practicals capable of registering fluorescence, with a spectral resolution of 1 nm? What do you need to measure fluorescence?

6) Multi Angle Viewing

a) What are the advantages of MVA?

b) How does multi angle viewing help vegetation studies?

c) Why is multi angle viewing very good for albedo research?

d) Apply the MVA to MODIS

7) What is compositing? Why and how is it done? Give an example of criterons

8) What is the major challenge for change detection? Which pre-processing steps?

9) Ray tracing models need scenes to work. Explain why and how the scenes are created?

10) Explain spectral mixture analysis. Use simple equations.

11) Is space-born fluorescence measuring possible? Given the challenges and possibilities.

12) Certain assumptions need to be made for remote sensing, list these.

13) Describe the specific methods for studying hyperspectral data.

14) What are the spectral and spatial trade-off for hypertemporal sensors?

2013 - 2014

1) Spectral signature between 350-2500 nm of + biophysical causes

a) shade vs sunlit leaves

b) monocots vs dicots.

c) succulent vs non-succelent leaves

d) very young vs young vs mature vs senescented leaves

e) healthy vs attacked by insects

2) Explain the difference between hyper- and multispectral remote sensing. What are advantages and disadvantages?

3) What type of ground-based LiDAR is most comparable with airborne LiDAR? Argumentation? Hardware components?

4) Dynamic terrestrial LiDaR, this is lidar placed upon a moving platform, the continuous geo-referencing of the moving platform is similar

5) Explain the fraunhofer Line Depth method + sketch

6) What is compositing? What is the purpose? Explain and give an example of 1 criteria and 2 criteria algorithms.

7) How does terrestrial laser scanning provide data for multi-angle purposes?

8) Describe ARVI, NDVI, TSAVI and PVI and their geometric relationship

9) What is the major challenge for change detection? Which pre-processing steps?

10) Basic assumption for the Beer-Lambert and Kubelka-Mulk models? Give example where this assumption is not met.

11) Explain the re-initialization and assimilation strategy, add a sketch

12) Explain the assumption linkage