Environmental Remote Sensing GEOG 2021

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Della McCormick
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1 Environmental Remote Sensing GEOG 2021 Lecture 3 Spectral information in remote sensing

2 Spectral Information 2

3 Outline Mechanisms of variations in reflectance Optical Microwave Visualisation/analysis Enhancements/transforms Getting info. from multispectral data 3

4 Reflectance Reflectance = output / input (radiance) measurement of surface complicated by atmosphere input solar radiation for passive optical input from spacecraft for active systems RADAR Strictly NOT reflectance - use related term backscatter 4

5 RADAR Mechanisms RADAR = RAdio Detection and Ranging Backscatter Transmit Receive See: 5

6 RADAR Mechanisms Rule-of-thumb: higher backscatter (brighter) means rougher 6

7 RADAR Mechanisms 7

8 Passive RS Mechanisms 8

9 Mechanisms Atmospheric windows transmission high so can see through atmosphere Particularly microwave 9

10 Reflectance Causes of spectral (with wavelength) variation in reflectance? (bio)chemical & structural properties chlorophyll concentration in vegetation soil - minerals/ water/ organic matter 10

11 Optical Mechanisms: vegetation 11

12 Optical Mechanisms: soil 12

13 consider Vegetation amount change in canopy cover over time (dynamics) varying proportions of soil / vegetation (canopy cover) A=Bare soil B=Full cover C=Senescence 13

14 Vegetation amount & dynamics Change detection Rondonia 1975 Rondonia 1986 Rondonia 1992 fishbone pattern? Landsat Multispectral Scanner :

15 Vegetation amount & dynamics Change detection 15

16 Uses of (spectral) information consider properties as continuous e.g. mapping leaf area index (LAI) or canopy cover or discrete variable e.g. spectrum representative of cover type (classification) Vegetation reflectance LOW in visible, HIGH in nearinfrared (NIR) 16

17 Leaf Area Index (LAI) The total one-sided green leaf area per unit ground surface area. 17

18 Leaf Area Index (LAI) 18

19 Leaf Area Index (LAI) Multi-year average MODIS LAI: 19

20 20

Leaf Area Index (LAI) MODIS LAI over Africa: September 2000 (left), December 2000 (right) See: http://svs.

21 Leaf Area Index (LAI) MODIS LAI over Africa: September 2000 (left), December 2000 (right) See: & 21

22 See: Forest cover

23 Forest cover

24 visualisation/analysis spectral curves spectral features, e.g., 'red edge scatter plot two (/three) channels of information colour composites three channels of information enhancements e.g. NDVI 24

25 visualisation/analysis spectral curves reflectance (absorptance) features information on type and concentration of absorbing materials (minerals, pigments) e.g., 'red edge': increase Chlorophyll concentration leads to increase in spectral location of 'feature' e.g., tracking of red edge through model fitting or differentiation 25

26 visualisation/analysis Colour Composites choose three channels of information not limited to RGB use standard composites e.g. false colour composite (FCC) learn interpretation Vegetation refl. high in NIR, display on red channel, so more veg == more red, soil blue 26

27 visualisation/analysis Std FCC - Rondonia 27

28 Enhancements Vegetation Indices reexamine red/nir space features NDVI =? 28

29 Enhancements Vegetation Index (VI) approach define function of the two channels to enhance response to vegetation & minimise response to extraneous factors (soil) maintain (linear?) relationship with desired quantity (e.g., canopy coverage, LAI) Main categories: ratio indices (angular measure) perpendicular indices (parallel lines) 29

30 RATIO Enhancements INDICES Vegetation Indices 30

31 RATIO Enhancements INDICES Vegetation Indices Ratio Vegetation Index RVI = NIR/Red Normalised Difference Vegetation Index NDVI = (NIR-Red)/(NIR+Red) 31

32 Enhancements Vegetation Indices RATIO INDICES FCC (veg is red) NDVI (veg is bright) 32

33 Global NDVI from MODIS in 2000 RATIO INDICES See: 33

34 Enhancements Vegetation Indices PERPENDICULAR INDICES 34

35 Enhancements Vegetation Indices PERPENDICULAR INDICES Perpendicular Vegetation Index PVI Soil Adjusted Vegetation Index SAVI 35

36 PERPENDICULAR INDICES And others... SARVI2, now called EVI (Enhanced Vegetation Index) 36

37 Summary Scattering/reflectance mechanisms monitoring vegetation amount visualisation/analysis spectral plots, scatter plots enhancement Vis 37

38 Readings Jensen s Chapter on Veg. Indexes Verstraete and Pinty (1996) Designing Optimal Spectral Indexes for Remote Sensing Applications Both available as pdfs on Moodle 38

INTRODUCTION TO MICROWAVE REMOTE SENSING. Dr. A. Bhattacharya

1 INTRODUCTION TO MICROWAVE REMOTE SENSING Dr. A. Bhattacharya Why Microwaves? More difficult than with optical imaging because the technology is more complicated and the image data recorded is more varied.