Landsat 8 波段组合「建议收藏」

Landsat 8 波段组合「建议收藏」Landsat8hasbeenonlineforacoupleofmonthsnow,andtheimageslookincredible.WhileallofthebandsfrompreviousLandsatmissionsarestillincorporated,thereareacoupleofnewones,su…

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Landsat 8 has been online for a couple of months now, and the images look incredible. While all of the bands from previous Landsat missions are still incorporated, there are a couple of new ones, such as the coastal blue band water penetration/aerosol detection and the cirrus cloud band for cloud masking and other applications. Here’s a rundown of some common band combinations applied to Landsat 8, displayed as a red, green, blue (RGB):

Natural Color 4 3 2
False Color (urban) 7 6 4
Color Infrared (vegetation) 5 4 3
Agriculture 6 5 2
Atmospheric Penetration 7 6 5
Healthy Vegetation 5 6 2
Land/Water 5 6 4
Natural With Atmospheric Removal 7 5 3
Shortwave Infrared 7 5 4
Vegetation Analysis 6 5 4

Here’s how the new bands from Landsat 8 line up with Landsat 7:

Landsat 7

Landsat 8

Band Name Bandwidth (µm) Resolution (m) Band Name Bandwidth (µm) Resolution (m)
Band 1 Coastal

0.43 – 0.45

30

Band 1 Blue

0.45 – 0.52

30

Band 2 Blue

0.45 – 0.51

30

Band 2 Green

0.52 – 0.60

30

Band 3 Green

0.53 – 0.59

30

Band 3 Red

0.63 – 0.69

30

Band 4 Red

0.64 – 0.67

30

Band 4 NIR

0.77 – 0.90

30

Band 5 NIR

0.85 – 0.88

30

Band 5 SWIR 1

1.55 – 1.75

30

Band 6 SWIR 1

1.57 – 1.65

30

Band 7 SWIR 2

2.09 – 2.35

30

Band 7 SWIR 2

2.11 – 2.29

30

Band 8 Pan

0.52 – 0.90

15

Band 8 Pan

0.50 – 0.68

15

Band 9 Cirrus

1.36 – 1.38

30

Band 6 TIR

10.40 – 12.50

30/60

Band 10 TIRS 1

10.6 – 11.19

100

Band 11 TIRS 2

11.5 – 12.51

100

For the most part, the bands line up with what we’re used to, with some minor tweaking of the spectral ranges. The thermal infrared band from Landsat 7 is now split into two bands for Landsat 8. Whereas before you had one thermal band that was acquired at 60 m resolution (and resampled to 30 m) now you have increased spectral resolution at the cost of spatial resolution. It wouldn’t be remote sensing without tradeoffs, right?

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