Remote Sensing of the Land Surface

May 2, 1996North of Denver, CO

August 16, 1995Central Brazil

What colors do we need to observe?

Ocean Plants Soils

Urban

Visible and Near Infrared Remote Sensing

Red: 610 - 700 nm Orange: 590 - 610 nm Yellow: 570 - 590 nm Green: 500 - 570 nm Blue: 450 - 500 nm Indigo: 430 - 450 nm Violet: 400 - 430 nm

Visible and Near IR Systems• Panchromatic imaging system: single channel detector sensitive to radiation within a broad

wavelength range; if visible range, then the resulting image resembles a "black-and-white" photograph taken from space. The physical quantity being measured is the apparent brightness of the targets. The spectral information or "color" of the targets is lost.

– IKONOS PAN ,SPOT ,HRV-PAN

• Multispectral imaging system: multichannel detector with a few spectral bands. Each channel is sensitive to radiation within a narrow wavelength band. The resulting image is a multilayer image which contains both the brightness and spectral (color) information of the targets being observed.

– LANDSAT MSS, LANDSAT TM , SPOT HRV-XS , IKONOS MS

• Superspectral Imaging Systems: many more spectral channels (typically >10) than a multispectral sensor. The bands have narrower bandwidths, enabling the finer spectral characteristics of the targets to be captured by the sensor.

– MODIS , MERIS

• Hyperspectral Imaging Systems: "imaging spectrometer". it acquires images in about a hundred or more contiguous spectral bands.

– Hyperion on EO1 satellite

Bands used for Land Surface Remote SensingBand Designation Wavelength (nm) Application*Visible Blue 450-520 Because water increasingly absorbs at longer

wavelengths, this band the best data for mapping depth-detail of water-covered areas. It is also used for soil-vegetation discrimination, forest mapping, and distinguishing cultural features.

Visible Green 500-600 The blue-green region of the spectrum corresponds to the chlorophyll absorption of healthy vegetation and is useful for mapping detail such as depth or sediment in water bodies. Cultural features such as roads and buildings also show up well in this band.

Visible Red 600-700 Chlorophyll absorbs these wavelengths in healthy vegetation. Hence, this band is useful for distinguishing plant species, as well as soil and geologic boundaries.

Near- IR 700-8000.70-0.80 μm

This band is especially sensitive to varying vegetation biomass. It also emphasizes soil-crop and land-water boundaries in images.

Near-IR 800-1100 0.80-1.10 μm

This band is used for vegetation discrimination, penetrating haze, and water-land boundaries.

Mid-IR 1550-17401.55-1.74 μm

This band is sensitive to plant water content, which is a useful measure in studies of vegetation health. It is also used to distinguish clouds, snow, and ice.

Mid-IR 2080-23502.08-2.35 μm

This band is used for mapping geologic formations and soil boundaries. It is also responsive to plant and soil moisture content.

Table 1. Visible and IR bands used for Land Surface Studies

*Application synthesis adapted from Yale University Remote Sensing and GIS Research Group

PAR Action Spectrum

Photosynthetically Active Radiation

violet - blue - green-yellow-orange - red - near IR

Measuring Vegetation

Strong Reflection

StrongDifferential Absorption

Attenuation in the Visible Wavelengths(molecular/no aerosol)

Grant Petty, 2004

Blue

and

ligh

t blu

eSc

atte

red

by m

olec

ules

ozone

765 nm

865 nm

Blue and Light BlueDirect Beam

Diffuse

PAR Action Spectrum

Photosynthetically Active Radiation

violet - blue - green-yellow-orange - red - near IR

Blue Line: depiction of molecular scattering in the visible wavelength bands

Attenuation in the Visible Wavelengths

Grant Petty, 2004

Aerosols scatter downwelling and upwelling visible radiation Haze

Bloom?

Daytime Visibility

Distant Dark ObjectsAppear Brighter

“Clear” Day

Hazy Day

Daytime Visibility

White Sunlight

Top of Atmosphere

Color and Intensity

Distance to the Dark Object

consider scattering by aerosols

Daytime Visibility

White Sunlight

Top of Atmosphere

Increased contribution ofwhite light

Object appears lighterwith distance

Longer Distance to the Dark Object

Daytime Visibility

Distant Dark ObjectsAppear Brighter

“Clear” Day

Hazy Day

What the satellite sees

White Sunlight

Top of Atmosphere

molecular and aerosol scattering 400→ 500 nm

ocean water 450-480 nmplants 500-600 nm and near-IR

atmosphere:windows in near IR

MAG NIR

Atmospheric Aerosol Correction Procedure

Blue Green Red Near-IR

Ln (Optical Thickness)

Cloudy

Cloudless-Polluted

Molecular Scattering

Aerosols

Satellite Channels

Aerosol

Molecules

Surface

NDVI• NDVI is calculated from the visible and

near-infrared light reflected by vegetation. • Healthy vegetation

– absorbs visible light and reflects a large portion of the near-IR light

• Unhealthy or sparse vegetation – reflects more visible light and less near-IR light

• Real vegetation is highly variable

NDVI

NASA Earth Observatory (Illustration by Robert Simmon)

NOAA 11AVHRR

1980 200019901985 201020051995

NOAA 7AVHRR

NOAA 9AVHRR

NOAA 14AVHRR

SeaWiFS

SPOT

MODISNOAA-16

NPP

NOAA 9 NOAA-17

Satellite Satellite NDVI NDVI data data

sourcessources

NOAA-18

C. Tucker

Terra Satellite• December 1999: Terra spacecraft• Moderate-resolution Imaging

Spectroradiometer, or MODIS, that greatly improves scientists’ ability to measure plant growth on a global scale.

• MODIS: higher spatial resolution (up to 250-meter resolution) than AVHRR

MODIS Global NDVI

Average NDVI 1981-2006

~40,000 images composited

C. TuckerGreen NDVI 1

Marked contrasts between the dry and wet seasons

Senegal

Beltsville USA winter wheat biomass

C. Tucker

Remote Sensing of Soil MoistureLecture 7

What is soil moisture?• Soil moisture water that is held in the spaces between soil

particles. – Surface soil moisture is the water that is in the upper 10 cm of

soil– Root zone soil moisture is the water that is available to plants,

which is generally considered to be in the upper 200 cm of soil.

• Ratio of liquid water content to the soil in percentage of volume or weight hysteresis: memory of previous precipitation events.

• Soil moisture is a key variable used to describe water and energy exchanges at the land surface/atmosphere interface

• Thermal infrared techniques• Microwave

– Active – Passive

• Optical (visible/near infrared)

Remote Sensing of Soil Moisture

Advantages of Microwave RS

• Transparent atmosphere• Vegetation semitransparent• Microwave measurement strongly dependent

on dielectric properties of soil water• Not dependent on solar illumination

Basis for Microwave Remote Sensing of Soil Moisture

• Basis for microwave remote sensing of soil moisture is contrast in dielectric constant of water (80) and dry soil (<5), causing emissivity contrast of 0.4 for water and 0.95 for dry land (Schmugge 2002)

• Research concludes surface layer sm can be determined to about ¼ wavelength, i.e. 0-5 cm layer using microwave λ = 21 cm

• Longer λ better for increased depth, less noise

• Soil moisture in pasture• λ = 21 cm responded

Soil moisture

λ = 21 cm

Schmugge 2002

Emissivity and Soil Moisture• Brightness temperature related to emissivity for 0 to 5 cm

surface layer

• εM is soil surface emissivity, TM is soil surface temperature• (1-εM)Tsky is ~ 2K, therefore εM ~ TB/TM

• If TM estimated independently, εM can be determined• Typical range for εM is 0.9 for dry soil to 0.6 for smooth wet

soil

TB = εMTM + (1-εM)Tsky

Schmugge 2002

Factors affecting accuracy• Vegetation cover

– Most important, dense vegetation (corn, forest) can obscure soil surface

– Greater effect at shorter λ• Soil properties

– Density and texture• Surface roughness

– Commonly 10 to 20% reduction in response range• Density and roughness relatively constant

Radar Remote Sensing— Soil Moisture

• HYDROS (http://www.skyrocket.de/space/doc_sdat/hydros.htm)– Back-up ESSP mission for global soil moisture.

• L-band radiometer.• L-band radar.

– Died mission

-98.5 -9 8.0 -97.5

35.0

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Southern G reat P la ins Hydro logy Experim ent (S G P97)Surface So il M oisture Derived From Rem otely S ensed M icrowave Da ta

June 30 July 1

July 2 July 3

S oil M oisture (% )

Latit

ude

(Deg

rees

)

Longitude (Degrees)

50

40

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10

0

35.0

35.5

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Chickasha

ElReno

Lamont

OklahomaCity

Chickasha

ElReno

Lamo nt

OklahomaCity

Chickasha

ElReno

Lam ont

Oklahom aCity

Chickasha

ElReno

Lamo nt

OklahomaCity

June 30

NA SA Land Surface Hydro logy Program

-98.5 -9 8.0 -97.5

35.0

35.5

36.0

36.5

-98.0 -97.5 -97.0

0

10

20

30

40

50

Southern G reat P la ins Hydro logy Experim ent (S G P97)Surface So il M oisture Derived From Rem otely S ensed M icrowave Da ta

June 30 July 1

July 2 July 3

S oil M oisture (% )

Latit

ude

(Deg

rees

)

Longitude (Degrees)

50

40

30

20

10

0

35.0

35.5

36.0

36.5

37.0

Chickasha

ElReno

Lamont

OklahomaCity

Chickasha

ElReno

Lamo nt

OklahomaCity

Chickasha

ElReno

Lam ont

Oklahom aCity

Chickasha

ElReno

Lamo nt

OklahomaCity

June 30

NA SA Land Surface Hydro logy Program

Courtesy: Tom Jackson, USDA

SGP’97

RadarPol: VV, HH & HV

Res – 3 and 10 km

Radiometer

Pol: H, V

Res =40 km,

dT= 0.64º K