zahid khalil contact: zahidkhalil.rao@gmail · 2019. 10. 5. · as snow ages, the reflectivity of...

INTERACTION OF EMR WITH EARTH'S SURFACES

Course: Introduction to RS & DIPUCC: 620124

Zahid KhalilContact: [email protected]

Introduction

When electromagnetic energy reaches the Earth's surface there are three possible energy interactions with the surface feature:

Reflection: occurs when radiation "bounces" off the target and is redirected

Absorption: occurs when radiation (energy) is absorbedinto the target

Transmission: occurs when radiation passes through a target

Introduction

As we know from the principle of energy conservation, energy can neither be created nor destroyed, but it can be transferred:

EI(λ) = ER(λ) + EA(λ) + ET(λ)Where:EI(λ) = Incident energy (from sun)ER(λ) = Reflected energyEA(λ) = Absorbed energyET(λ) = Transmitted energy

Introduction

The proportion of energy reflected, absorbed and transmitted will vary depending on the surface material, condition and wavelength of the energy.

For example: Vegetation and soils can reflect approximately 30-50% of the incident energy

While water on the other hand reflects only 10% of incident energy.

Water reflects most of this in the visible range, minimal in the NIR and beyond 1.2 μm (mid-infrared) water absorbs nearly all energy.

Radiance vs. Reflectance

The total quantity of incoming energy (light) from the sun is known as irradiance.

Satellites measure radiance (brightness), or the amount of light.

Objects on the ground are often characterized by their reflectance, or the percentage of incident energy that is reflected.

Radiance vs. Reflectance

Reflectance is the portion of incoming incident energy that is reflected.

This is always measured as a function of wavelength and is given as a percent.

Spectral Reflectance

ρλ = ER(λ) / EI(λ)or

% Reflectance =100 x Reflected/Incoming

Reflectance Dependency

The remote sensing measurement not only depends on the basic optical properties of the surface, but also on external conditions:

State of the atmosphere

Sun-surface-sensor geometry of the observation

Location and topography


The atmosphere affects the radiance received by the sensor in two ways:

It can reduce (or attenuates) the energy

Atmosphere itself is a reflector, adding energy or “path radiance” to the signal detected by the sensor

Diffuse radiation also occurs due to the multiple atmospheric scatters

As a result, the irradiance at the surface consists of both a direct and diffuse component


The reflectance reaching a sensor is also dependent on the geometric conditions of the observation: The orientation of the Sun

The height of the Sun in the sky (solar elevation angle)

Direction in which the sensor is pointing relative to nadir (the look angle)

These geometric relationships along with the surface properties (primarily roughness) determine how the incoming radiation is scattered and the strength of outgoing radiation.


There are three types of surface scattering that may occur:

Specular Reflection

Diffuse or Lambertian reflection

Anisotropic reflection

Specular reflectors are flat surfaces that produce mirror like reflections.

On an ideal specular reflector the angle of incidence is equal to the angle of reflection.


Specular Reflection

In this case, the sensor can measure only the ground reflected energy at particular viewing angle and will not receive any energy at any other viewing directions


Diffuse or Lambertian Reflection The incident energy is reflected diffusely

and more or less equally, or isotropically in all direction.

Independent of viewing angle to the surface normal

Most surfaces exhibit the third type of scattering behavior known as anisotropic reflectance, i.e. neither perfectly specular or diffuse reflector but their characteristics are somewhere in between.


In general, the type of scattering depends on the size of the surface elements and the wavelength involved.

In conclusion, the observed reflectance signature of a surface is a product of its own inherent physical, biological, and chemical makeup, as well as various external factors that modify the spectral behavior of surface constituents.


Despite all of these factors, the spectral reflectance signatures are still very useful in extracting information about the land surface.

Spectral Reflectance Curve of Vegetation

Vegetation Spectral Characteristics

❑ Vegetation has a unique spectral signaturewhich enables it to be distinguished readily fromother types of land cover in an optical/near-infrared image.

❑ It has generally low reflectance in the visiblespectrum, high in the NIR, and low reflectance inSWIR portion of the spectrum.


The amount of energy reflected for a particular wavelength depends on:

Leaf pigmentation

Leaf thickness

Composition (cell structure)

Amount of water in the leaf tissue

Structure of Leaf


In the visible portion, the reflection of blue and red spectrum is low, because these portions are absorbed by the plant (mainly by chlorophyll) for photosynthesis; The vegetation reflects relatively more green light

In NIR range, the reflectance depends on leafdevelopment and cell structure.

In SWIR, it is mainly determined by the free water in the leaf tissue; More free water, less reflectance Wavelength ranges around 1.45, 1.95 and 2.50 m are

therefore called water absorption bands.


Reflectance is much higher in the near infrared (NIR) region due to the cellular structure of the leaves, specifically the spongy mesophyll.

Leaf reflectance increases for more heterogeneous cell shapes and contents as well as with increase in the number of cell layers, intercellular spaces and variation in cell size.

Leaf Structure

Mesophyll vs NIR Reflectance

Lots of palisade mesophyll = low NIR reflectance

Lots of spongy mesophyll = higher NIR reflectance

Leaf Water Content

Variation in the spectral reflectance characteristics of vegetation according to leaf

moisture content.

The Red Edge

The Red Edge

Healthy, Stressed & Severely Stressed Vegetation

Spectral Reflectance Curve of Snow

Spectral Properties of Snow

It depends upon the following snow parameters ;

◼Grain Size and Shape

◼Impurity Contents

◼Near Surface Liquid Water Content

◼Depth And Surface Roughness

◼Solar elevation

◼ Fresh fallen snow has a very high reflectance in thevisible wavelengths.

◼ As snow ages, the reflectivity of snow decreases in thevisible and specially in the NIR wavelengths.

◼ This decrease in reflection is due to melting andrefreezing with in the surface layers and to the naturaladdition of impurities.

◼ Melting of snow increase the mean grain size anddensity.

Spectral Properties of Snow

Continued…

◼ In the wavelength region between approximately (0.65 -1.4micro m); the difference in snow crystal radius leads to thegreater difference in the reflection.

◼ The greater the size of grain the greater will be thedecrease in the reflection.

◼ The reflection of glacier ice is quite low.

◼ But the glacier ice covered with snow increases thereflection.

◼ Presence of melt water decreases the reflection.

Spectral Signature of Snow & Ice

Distinguishing Snow and Cloud

❑ Snow and cloud has same reflectance in visible portion of the spectrum.

❑ So how can we discriminate between these two features …???

❑

❑ Snow can be distinguished From Cloud in middleinfrared band

At the wavelength of 1.6 m, snow has very lowreflectance, while the reflectance of cloudsremains high.

Continued…

Spectral Reflectance Curve of Soil

Spectral Properties of Soil

Bare soil generally has an increasing reflectance, with greater reflectance in near-infrared and shortwave infrared.

It is dependent on so many factors that it is difficult to give one typical soil reflectance curve

Some of the factors affecting soil reflectance are: Moisture content

Soil texture (proportion of silt, clay and sand)

Surface roughness (particle size distribution)

Presence of iron oxide

Organic matter content

Of these variables, moisture content is the most important due to its dynamic nature and

large overall impact on soil reflectance.


Variation in the spectral reflectance characteristics of soil according to moisture

content.


Variation in the spectral reflectance characteristics of soil according to particle size.


Variation in the spectral reflectance characteristics of soil according to particle size.

What about Clayey soil…..?

Spectral Properties of Soil

Soils are mixtures of a number of inorganic and organic constituents, so it is not straightforward to evaluate the composition of soils from their spectral signatures.

For example: Soil with a high quartz content often reflect a large portion of energy

across the electromagnetic spectrum

Wet soils absorb most of the NIR and SWIR light

Soils high in organic matter tend to absorb much of the visible light that fall upon them


Spectral reflectance for different soil types: Mollisol (gray silt), Vertisol (brown

clay) and Entisol (White gypsum)

Spectral Reflectance Curve of Water

Spectral Properties of Water

Compared to Vegetation and soils, water has a lower reflectance.

Water reflects EM energy in the visible range and a little in NIR.

In general the longer the wavelength, the greater the absorption

It is generally straightforward to spectrally recognize water bodies on remotely sensed images


Variation in water optical properties depends upon: Differences in water depth

Chlorophyll content

Dissolved particles

Surface roughness

Reflectance increases with increasing sediment content

It also increases with increasing algal concentrations

What happens when chlorophyll content increases in water…?


Variation in water optical properties depends upon: Differences in water depth

Chlorophyll content

Dissolved particles

Surface roughness

Reflectance increases with increasing sediment content

It also increases with increasing algal concentrations

What happens when chlorophyll content increases in water…?

What if there is calm water?

Influence of depth on water reflectance

The depth of water directly influences the reflectance contribution from materials on the bottom of the water

In shallow water, due to the stronger contribution from the bottom layer, reflectance will generally increased

The greater the water depth, the greater the absorptance

Bathymetric mapping in coastal zones is based on these relationships.

From studies, the maximum water depth that could be determined was 6.4m in

the blue band, 3m in the green band, and 2.1m in the red band. (Ji et al. 1992)

Spectral Behaviour of Urban Land

In urban areas the spectral reflectance of an individual pixel will generally not resemble the reflectance of a single land cover class but rather a mixture of the reflectances of two or more classes.

Because they are combinations of spectrally distinct land cover types, mixed pixels in urban areas are frequently misclassified as other classes.

But…

The level of detail of the reflectance curve depends on the spectral resolution of the sensor.

Laboratory and field spectrometers typically collect hundreds of data points, measuring the percent reflectance of a material at hundreds of wavelengths.

The Landsat 8 only measures reflectance at nine different bands (or specific wavelengths) between 400 to 2500 nanometers,

While hyperspectral sensors like Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) measure 224 bands in the same range.

But…

The level of detail of the reflectance curve depends on the spectral resolution of the sensor.

Laboratory and field spectrometers typically collect hundreds of data points, measuring the percent reflectance of a material at hundreds of wavelengths.

The Landsat 8 only measures reflectance at nine different bands (or specific wavelengths) between 400 to 2500 nanometers, which isn't sufficient resolution to detect any absorptions typical in minerals.

While hyperspectral sensors like Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) measure 224 bands in the same range which has sufficient spectral range to resolve many common absorption bands found in a wide variety of minerals and other compounds

Comparison of spectral reflectance curves for alunite from four sensors (Landsat

TM, MODIS, AVIRIS and laboratory sensor) with different spectral resolutions.

Image Credit: USGS

Questions & Discussion

zahid khalil contact: zahidkhalil.rao@gmail · 2019. 10. 5. · as snow ages, the reflectivity of...

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