Spectral Signatures and Their Interpretation PDF

# Spectral Signatures and Their Interpretation ## 1. EMR and earth materials interaction * When EMR from the sun reaches the earth surface, it is: * transmitted - transmittance * absorbed - absorbance * reflected - reflectance * The way that earth materials transmit, absorb or reflect...

# Spectral Signatures and Their Interpretation ## 1. EMR and earth materials interaction * When EMR from the sun reaches the earth surface, it is: * transmitted - transmittance * absorbed - absorbance * reflected - reflectance * The way that earth materials transmit, absorb or reflect the solar EMR is called the spectral signature of an object. ## 2. Spectra of earth materials * Vegetation * Soil and rocks * Water, ice and snow * Cloud, fire and smoke ## 3. Vegetation * Contains water, cellulose (tissues and fibres), lignin (non-carbohydrate constituent of wood), nitrogen, chlorophyll ("green" pigments) and anthocyanin (water-soluble pigments). * Depending on how 'active' (i.e. kinds of chlorophyll) a green vegetation is, the combination of transmittance, absorbance and reflectance vary in different bands of the spectrum. ### 3.1 Physiological Factors * Leaf structure * Reflectance, transmittance, and absorptance spectra * Leaf maturation * Mesophyll arrangements (internal structural differences) ### 3.2 Leaf structure **A leaf's structure and its reflectance characteristics at visible and near IR wavelengths** * **Image Description:** The image shows a cross-section of a leaf with labels indicating the different parts of the leaf, such as upper epidermis, chloroplasts, palisade cells, spongy mesophyll, stoma, air space, mesophyll cells, and lower epidermis. Arrows indicate the direction of how light might interact with each part of the leaf. ### 3.3 Transmittance, absorbance and reflectance * **Image Description:** The image shows a graph depicting the transmittance, absorbance, and reflectance of a mature orange leaf with respect to wavelength. Transmittance increases with wavelength and reaches almost 100% at approximately 1 µm before decreasing to 0% between 1.4 to 2 µm. Absorbance is highest between 1.4 to 2 µm and decreases significantly as wavelength increases. Reflectance is low at lower wavelengths and increases to approximately 60% between 0.8 to 1 µm before decreasing to 10% between 1.4 to 2 µm. The wavelength is measured in µm. ### 3.4 Absorption spectra * **Image Description:** The image shows a graph of the absorption spectra of chlorophyll a (blue-green) and chlorophyll b (yellow-green) with respect to wavelength (nm). Both chlorophyll a and b have two peaks, but at different wavelengths, the peak for chlorophyll a is higher. ### 3.5 Spectral reflectance * **Image Description:** The image shows a graph of the spectral reflectance of various materials: fresh snow, vegetation, silty water, sandy loam soil, asphalt, and clear water with respect to wavelength. The wavelength is measured in µm. * **Average spectral-response curves for six materials** * **Average spectral-response curves for four types of vegetation** * Deciduous * Grass * Aquatic * Coniferous * **Average spectral-response curves for a plant leaf as it progresses from a healthy state through different stages of damage** * Normal leaf * Incipient damage * Chronic damage * Dead leaf ### 3.6 Other factors * Leaf damage * Sun and shaded leaves * Leaf water content * Leaf air spaces * Salinity and nutrient levels ### 3.7 Vegetation canopy * Transmittance of leaves * Amount and arrangement of leaves * Characteristics, e.g., stalks, trunks, limbs, etc. * Background (soil, leaf litter, etc.) * Solar zenith angle * Look angle * Azimuth angle ## 4. Soil and Rocks * The reflectance from soil and rocks is influenced by: * colour * mineral contents (chemical composition or crystalline structure) * structure * and others * We use soil for discussion ### 4.1 Field reflectance spectra * **Image Description:** The image shows a graph comparing the field reflectance spectra of various materials: dry grass, green grass, bare soil, packed, bare soil, plowed with cobbles, Virginia pine, Scarlet oak, and plowed soil with cobbles. The most significant differences occur between 0.8 and 1.2 µm, and differences in packed vs. plowed soil become clearer at higher values of wavelength ### 4.2 Factors influencing interpretation of soils * Soil colour * Mineral content - depends upon the intermolecular vibration of the molecules * Organic matter - influences soil colour and moisture * Particle size - reflectance and thermal diffusivity, and moisture. ### 4.3 Factors influencing interpretation of soils (cont.) * **Soil texture** - mainly indirect effects on, e.g., soil moisture * **Structure and surface roughness** (soil aggregation) -"smoothness" of soil - have significant effects on RADAR response. * **Soil emissivity** - thermal emissivity: ratio of energy radiated at the surface / black body * **Soil temperature** - influences the interpretation of thermal imagery and time of sensing. ### 4.4 Reflectance from soils * O2 and CO2 and water vapour absorption * Sun illumination varies with atmospheric conditions and solar radiation * Effects of soil structure, surface roughness, etc. * The intensity of the sun peaks at about 0.5µm falling off rapidly at shorter and longer wavelengths. ### 4.5 Reflectance of Minerals * **Image Description:** The image shows two graphs of directional hemispherical reflectance spectra of two clay minerals, kaolinite, and montmorillonite, with respect to wavelength in µm. The top graph shows the spectra between 0.4 and 2.5µm. Kaolinite shows a small peak around 1.4µm, montmorillonite shows a peak around 2.2µm. The bottom graph shows the spectra between 2 and 25µm. The biggest difference between the two minerals in the bottom graph can be found around 10µm. ## 5. Water, Ice and Snow * Water * visible transmittance is high * high absorptance in NIR * influenced by the cleanness * Snow * high reflectance in < 1.5µm * low at 1.5 and 2µm * very low in the thermal IR ### 5.1 Reflectance of ocean water * **Image Description:** The image shows a graph showing the calculated change in bulk reflectance of ocean water with increasing concentration of phytoplankton. Reflectance increases, especially at lower wavelengths, as the concentration of phytoplankton increases. ### 5.2 Reflectance of Snow * **Image Description:** The image shows two graphs of computed reflectance spectra of three different textures of snow (coarse, fine, and frost) for 0.3-3.0µm and 3-14µm wavelength. ## 6. Cloud, fire and smoke * Cloud * strong reflectance in visible and NIR * associated with shadow * can be penetrated by radar * Fire * high temperature * Wien's displacement law * $λ_{max}=\frac{W}{T}$, where W = 2,897 µm K, λ is the wavelength, and T is the temperature. * Smoke * highly visible (black or white) in visible * can be penetrated by TM5 and TM7 as their wavelength is larger than the most smoke particles. ### 6.1 Detecting smoke and fires * **Image Description:** The image shows a set of images of the same area with the same spatial resolution, but each image was taken with a different sensor band of a TM satellite. The sensors used were TM band 1-5 and 7. The first three images show smoke plume in the same location in each band. Bands 1-4 are grayscale images, the smoke plume is readily visible, and the fire is hard to discern. Bands 5 and 7 are grayscale images that have been processed to appear almost black, the smoke plume is still visible, and the fire is noticeably brighter than the surrounding environment. ## 7. Multispectral images and their interpretation * **Single image band interpretation** * similar to airphoto interpretation * beware of the spectral wavelength of the band and the spectral signatures of the objects * Colour composites * Multispectral band statistics * Multispectral classifications ### 7.1 Panchromatic and infrared photographs * **Image Description:** The image shows a panchromatic (left) and an infrared (bottom) photograph of the Goldach region, Switzerland. The panchromatic photo appears as light gray to black, the infrared photo appears almost entirely white except for the stream and several small areas that appear dark. ### 7.2 Infrared and panchromatic photographs * **Image Description:** The image shows an infrared (left) and a panchromatic (right) photograph of the same area. The lighter areas in the infrared image correspond to the darker areas in the panchromatic image, and vice versa. The lighter areas in the infrared image are more recent sediment deposits that are usually moist and have not been vegetated. ### 7.3 Single band interpretation * **Image Description:** The image shows 6 individual images taken by a TM satellite sensor. One image for each of the TM bands 1, 2, 3, 4, 5, and 7. The images appear grayscale. The images are of the same area and with the same spatial resolution. ### 7.4 Colour composites * **Number of composites** * $N = \frac{n!}{3!(n-3)!}$ * **Example: TM 6 non-thermal bands** * $N = \frac{6!}{3!(6-3)!} = 20$ ### 7.5 Colour Infrared photos * **Image Description:** The image shows a colour infrared photo of an area with different types of vegetation. Red areas are vegetation covered areas, a stream is in the middle of the photo (dark red/brown), and lighter areas are fields of various other materials. ### 7.6 Colour composites (cont.) | | RED | GREEN | BLUE | |-------|----------|----------|----------| | Nature | TM3 | TM2 | TM1 | | Colour | TM4 | TM3 | TM2 | | IR | MSS7 | MSS5 | MSS4 | | | HRV3 | HRV2 | HRV1 | | | AVHRR4 | AVHRR3 | AVHRR1 | | | TM7 | TM2 | TM1 | | | CZCS6 | CZCS2 | CZCS1 | ### 7.7 Colour composites (cont.) * **Image Description:** The image shows three false colour composites of the same area. The first composite is TM bands 1, 2, 3, the second composite is TM bands 2, 3, 4, and the third composite is TM bands 1, 4, 5. ### 7.8 Object signatures on panchromatic and infrared photographs | Object | Panchromatic | Infrared | |------------------------------------|----------------|------------| | Snow | White | White | | Clouds | White | White | | Sky (high oblique) | Medium grey | Black | | Clear water | Dark grey | Black | | Silty water | Light grey | Medium grey| | Deciduous foliage | Dark grey | White | | Coniferous foliage | Dark grey | Medium grey| | Autumn foliage (yellow) | Light grey | Light grey | | White sand (dry) | Light grey | Light grey | | White sand (moist) | Medium grey | Dark grey | | Red sandstone (dry) | Medium grey | Light grey | | Red sandstone (moist) | Medium grey | Dark grey | | Swamp | Dark grey | Black | | Asphalt | Dark grey | Black | | Concrete | Light grey | Medium grey| * a: Acquired with a Kodak Wratten 12 filter. * b: Acquired with Kodak Wratten 88A or 89B filters. ### 7.9 Multispectral band statistics * **Image Description:** The left image of the page shows the input histogram of a generic multispectral band. The right image shows the output of a linear stretch applied to the multispectral band. ### 7.10 Multispectral band statistics (cont.) * **Image Description:** The image shows a scattergram for one multispectral image band. ## 8. Summary * Different earth's materials have various characteristics in reflecting solar EMR. * The reflectance pattern of an object is called its spectral signature. * Understanding spectral signatures of earth's materials is essential for remote sensing image interpretation. * The ultimate goal is to guide spectral band selection and create human colour vision for proper image interpretation.