6.1 Indices Flashcards

1
Q

Band composites

How to distinguish vegetation from soil

A
# How to distinguish vegetation from soil
False-color B5/B4/B3 (NIR/Red/Green)
# How to distinguish water from the shadow
Pseudocolor B8A/B7/B3
# How to distinguish cloud from snow
Pseudocolor B11/B7/B3
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2
Q

What is Indice?

A
Quantitative measurements of different features
–Vegetation
–Water
–Snow
–Moisture
–etc.
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3
Q

Advantages and Disadvantage of indices

A

Advantages:
–Simple to understand
–Easy to implement
–Fast (operation per scene instead of per pixel)

Disadvantage:
Empirical i.e. no physical meaning

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4
Q

Indice used for Band difference:

A

𝐷𝑉𝐼=𝑁𝐼𝑅−𝑅

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5
Q

Indice used for Band ratio:

A

𝑅𝑉𝐼=𝑁𝐼𝑅 / R

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6
Q

Indice used for Band normalized ratio:

A

NDVI = (NIR-R) / (NIR+R)

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7
Q

Difference Vegetation Index (DVI)

A
  • Simplest vegetation index
  • Distinguishes vegetation from soil

𝐷𝑉𝐼=𝑁𝐼𝑅−𝑅

–High values for vegetation
–Low values for soil
–Negative values for water

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8
Q

Difference Vegetation Index (DVI) disadvantages

A

×Large range of DVI –> difficult to compare (difficult to compare different area or images)

×Sensitive to atmosphere and shadow

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9
Q

Ratio Vegetation Index (RVI)

A

Simplest ratio based index to quantify vegetation greenness

𝑅𝑉𝐼=𝑁𝐼𝑅 / R

–Large RVI value: healthy vegetation
–Lower RVI values: water, soil, ice

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10
Q

Ratio Vegetation Index (RVI) disadvantages

A

×Impossible to calculate when R=0

×Large range of RVI –> difficult to compare

e.g. RVI = 0.5/0.08 = 6.25 -> healthy vegetation
RVI = 0.4 / 0.3 = 1.33 -> unhealthy vegetation

the image appears yellowish means lower vegetation density

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11
Q

Normalized Difference Vegetation Index (NDVI)

A

Quantify vegetation greenness

NDVI = (NIR-R) / (NIR+R)

–Ranging from -1 to 1
–Healthy vegetation: high NDVI values
–Clearwater: negative NDVI close to -1
–Sand , snow, cloud: low NDVI value close to 0

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12
Q

Normalized Difference Vegetation Index (NDVI) value and what it means

A
NDVI = (0.5-0.08) / (0.5+0.08) = 0.72 -> healthy vegetation
NDVI = (0.4-0.3) / (0.4+0.3) = 0.14 -> unhealthy vegetation 

NDVI >0.2 = sparse vegetation
NDVI >0.6 = dense vegetation

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13
Q

Normalized Difference Vegetation Index (NDVI) facts

A
  • 16 km weekly NDVI
  • Advanced Very High-Resolution Radiometer (AVHRR)
  • 1 km spatial resolution, 4 6 spectral bands
  • 2400 x 6400 spatial coverage
  • Since 1979
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14
Q

Normalized Difference Vegetation Index (NDVI) disadvantages

A

•NDVI has a limited sense to high Leaf Area Index (LAI)
–LAI quantifies the amount of leaf materials in a canopy.

  • Atmospheric condition alternates NDVI value
  • NDVI is sensitive to background noise from soil
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15
Q

Enhanced Vegetation Index (EVI)

A

EVI quantifies vegetation greenness

(complicated equation)

–Corrects for some atmospheric condition and canopy background noise
–Ranging from -1 to 1
–Healthy vegetation between 0.2 and 0.8
–Effective for analyzing areas with large amounts of chlorophyll (e.g. rainforests

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16
Q

Enhanced Vegetation Index (EVI) disadvantage

A

×Blue band is missing in several sensors

17
Q

EVI vs. NDVI

A
  • EVI is more sensitive to LAI (EVI -)

* EVI is less sensitive to aerosol (EVI +)

18
Q

Enhanced Vegetation Index 2 EVI2)

A

EVI2 quantifies vegetation greenness
–For sensors without a blue band e.g. AVHRR

(complicated equation)

19
Q

Normalized Difference Moisture Index (NDMI)

A

Measures the water content of green vegetation

NDMI = (NIR-SWIR) / (NIR+SWIR)

–Ranging from -1 to 1
–Chlorophyll has a high reflection in NIR

–High water content –> Low SWIR reflectance
–Low water content –> high SWIR reflectance

–High water content: High NDMI
–Low water content: Low NDMI

20
Q

Normalized Difference Water Index (NDWI)

A

Quantify water bodies

NDWI = (G-NIR) / (G+NIR)

–Ranging from -1 to 1
–Water bodies: NDWI values larger than 0.5
–Vegetation: Negative NDWI values

21
Q

Normalized Difference Snow Index (NDSI)

A

Quantify the amount of snow and ice

NDSI = (G-SWIR) / (G+SWIR)

–Ranging from -1 to 1
–Distinguish snow/ice from cloud

–Snow has
•Low reflectance in SWIR
•High reflectance in visible/NIR

–Cloud has high reflectance in SWIR and visible/NIR

–Snow/ice: High NDSI values
–Cloud: Low NDSI values