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NRMT 2270, Photogrammetry/Remote Sensing Lecture 2 Electromagnetic radiation principles. Units, image resolutions. Tomislav Sapic GIS Technologist Faculty of Natural Resources Management Lakehead University
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Transcript of Lecture 2 Electromagnetic radiation...

• NRMT 2270,Photogrammetry/Remote Sensing

Lecture 2

Electromagnetic radiation principles. Units, image resolutions.

Tomislav SapicGIS Technologist

Faculty of Natural Resources ManagementLakehead University

• Units Refresher

1 ha = 10,000 m2

1 inch = 2.54 cm

1 foot = 0.3048 m

1 yard = 3 ft (‘)

1 ft = 12 inch (‘’)

1 m = 1,000,000 μm = 1,000,000,000 nm

1TB = 1000 GB

1 GB = 1,000 MB = 1,000,000 bytes

1 byte = 8 bits = 255

16 bits = 65535

• Energy Transfer

The three basic ways in which energy can be transferred:• Conduction• Convection • Radiation

Source: Jensen (2007).

• Electromagnetic radiation exhibits wave-like behaviour as it travels through space.

• An electromagnetic wave is composed of electric and magnetic vectors (fields) that are perpendicular to one another.

• Wavelength is defined as the mean distance between consecutive maximums.

• Frequency is the number of wavelengths that pass through a point per second, measured in hertz (Hz).

• The photon is the basic unit of electromagnetic radiation; it’s a piece of energy and it can transfer the energy to another object (e.g., electron).

• Photons move at the speed of light (299,792 km/s)

Source: Jensen (2007).

• Electromagnetic Spectrum

• The range of all possible frequencies of electromagnetic radiation is called electromagnetic spectrum.• Organisms use only a portion of the electromagnetic spectrum for their functions – humans see and plants use for the photosynthesis the visible portion of the spectrum.

Source: Jensen (2007).

• Light Intensity

Photon at a certain wavelength

• Light intensity is the power (amount of energy consumed per unit time) transferred per unit area, or in other words, when it comes to photons, the light intensity for a certain wavelength can be also looked at as the number of photons at that wavelength hitting a unit area per unit time.

• The energy of electromagnetic waves, i.e., radiant energy, can be reflected, absorbed by, or transmitted through an object.• The absorbed energy gets turned into other forms of energy and is used in different processes, e.g. photosynthesis.• Objects reflect, absorb and transmit the radiant energy from different segments of the EM spectrum and at various intensities.

Reflectance

Absorption

Transmittance

• Blue Green Red

Absorption, Reflectance, and Transmittance in Plants

Near Infrared

Source: Jensen (2007).

Source: Jensen (2007).

Reflectance – radiation bounces off the object on the surface of the Earth.

Radiance – radiant flux (the photons energy per unit of time - power) per unit of projected source area per unit solid angle.

Photo sensors record radiance but the term reflectance is often used in place of radiance.

• • The earth atmosphere transmits to various degrees or completely blocks different portions of the EM spectrum.

Surface of the Earth

Source: Jensen (2007).

• Atmospheric Windows from 0.1 – 30 μm

• Photographic films can be made sensitive to reflective energy from 0.7- 1.3 μm, in addition to the visible spectrum.

• Electro-optical sensing systems can, in addition, record infrared energy from 0.7 – 14 μm.

Source: Jensen (2007).

• Source: Jensen (2007).

• • The dominant factors controlling leaf reflectance within the EM spectrum used in aerial photography are the various leaf pigments in the palisade mesophyll (e.g., chlorophyll a and b, and β-carotene) and the scattering of near-infrared energy in the spongy mesophyll.

Source: Jensen (2007).

• • Chlorophyll is stored in chloroplast bodies located within the palisade and spongy parenchyma cells.

• While the spectral properties of chlorophyll cause the green colour of the leaves, morphology of the spongy parenchyma (intercellular air space) contributes to the high reflectance in the near-infrared.

• High reflectance - high transmittance property of the leaves in the near-infrared region means enhanced reflectance for the whole canopy in this region.

Source: Jensen (2007).

• Absorption Spectra of Chlorophyll a and b Pigments

Source: Jensen (2007).

• Resolutions in Photogrammetry/Remote Sensing

• Spectral

• Spatial

• Temporal

• Black

White

8 bit

0

255

16 bit

0

65535

Source: Jensen (2007).

• • Image (raster) files are defined as square cells (pixels) of the same size, aligned in a defined number of horizontal rows and vertical columns.

• Cell values in image (raster) files represent spectral reflectance (radiance) measurements.

row

colu

mn

Content of one band a typical image (raster) file:

Image Files

• • Reflected energy gets recorded on the film or an electronic sensor, in its detection units (e.g., silver halide crystals, pixels), as brightness intensity for the sensed segment of the electromagnetic spectrum.

• The brightness intensity recorded in pixel is a resultant of the sum of reflectances (photons) coming from the area the individual pixel captures and hitting the sensor detector that produces the pixel.

• In an image raster (band) the brightness is displayed on a scale from black for the lowest to white for the highest.

• Digital (electrical) sensors are pre-calibrated to the max (white) and min (black) level of possible reflectance.

• Radiometric resolution in image (raster) files is the binary depth (scale of discrete, integer, numbers) available to store reflectance values per each pixel.

• In a digital photo (image) file, reflectance (black to white range) is captured along the scale designed for the sensor and the digital file.

o The most common scale, in digital photo files used by average users is 0 – 255. This range represents 1 byte, i.e. 8 bits.o However, digital photo files can also be, e.g., 11 bit (0 – 2047), 16 bit (0 – 65535), and so on.

• Radiometric resolution measures the number of discriminable signal levels. 0 – 255 is a lower radiometric resolution than 0 – 65535.

• In digital images radiometric resolution is referred as data depth.

• Each cell (pixel) in a raster (image, photo) file has assigned to it the data depth defined for the file. The number of cells times the data depth gives the size of the image file. The size of the image file remains the same irrespective of the values stored in its cells.

• Spectral Resolution

• Spectral resolution defines the wavelength range segment(s) the specific sensor records.

• Image sensors outside of aerial photography record a much broader and varied selection of the EM spectrum.

• Aerial photography primarily deals with four segments, blue, green, red, and near infrared (NIR), or with the range encompassing the blue, green, red, and sometimes, a portion of NIR neighbouring red.

• Image files that have blue, green, red and sometimes NIR reflectance recordings stored into their separate, respective bands, are referred to as multispectral image files; the other image files, encompassing in their spectral range several segments, are referred to as panchromatic image files.

• For example ADAR 5500 digital frame camera records the blue (450 – 515 nm), green (525 – 605 nm), red (640 – 690 nm), and NIR (750 – 900 nm) segments in 4 separate channels.

• The spectral resolution of campus_pan is 400 –700 nm and of campus_rgb 400 –500/500 – 600/600 –700 nm.

Campus_rgb has a higher spectral resolution than campus_pan.

• The campus_rgb raster (image) file has 5062 columns and 3645 rows, three bands (blue, green and red), and its data depth is 16 bit.

The total byte size of the campus_rgb raster is (5062*3645*16*3)/8 = 110705940 bytes = 110.71 MB

• Spatial Resolution• Expresses the size of the earth surface

represented by one (square) cell in a digital photo (raster file) or one silver halide crystal in a chemical photo.

• A 10 m raster is a raster whose each cell represents 10 x 10 meters of the earth surface.

• Spatial resolution is also sometimes referred as ground sampling distance as well as instantaneous field of view (IFOV).

• Because of the nature of rasters and their easy computational resampling, raster spatial resolution does not necessarily represent the spatial variability on the ground.

• For example, the 80 m raster in the example on the right can be taken and resampled into a 40 m raster, but in that case all four new 40 m cells within each original 80 m cell area would have the same cell value – the spatial resolution would become 40 m, but the Ground Sampling Distance would stay 80 m.

• • Example (simplified): 8 bit (0 – 255), 1m raster, red band (~600 – ~700 nm).

Ground

Raster, red band

~0.23 (sand) *255*0.5 + ~0.01 (water) *255*0.5 = 30.6

31

Sand (~50% of the cell area)

Water (~50% of the cell area)

Cell (pixel) value

1 m

Only, the derivation of cell values in digital sensors is a bit more complicated …

• • Primary colours filters are applied to separate detectors in the same array and separate bands, each representing one of the three primary colours, are constructed by using the values of the pixels filtered by a given colour and interpolating the values of the pixels surrounding them. Most of digital sensors use a Bayer mosaic for the interpolation.

Source: https://en.wikipedia.org/wiki/Bayer_filter#Modifications

• Instantaneous Field of View (IFOV) and Field of View (FOV)

Source: W. Takeuchi, http://stlab.iis.u-tokyo.ac.jp/~wataru/lecture/rsgis/rsnote/cp6/6-2-1.gif

Source: Federation of American Scientists, http://www.fas.org/man/dod-101/navy/docs/es310/EO_image/EO_Image.htm

)ƒ2

(tan2 1d

IFOV

)H2

(tan2 1D

IFOV

d – pixel widthƒ – focal lengthD – ground widthH – flying height

• Temporal Resolution

• Temporal resolution defines the average time between two takes of a photo of the same area.

• Temporal resolution has greater relevance when describing satellite images, because remote sensing satellites continuously orbit the Earth but their orbit heights can differ so that they revisit the same area at different time frequencese.g., once a day, once a month, etc.).

• Aerial photos are usually tasked through specific projects and not on a regular basis over time.

• References:

J. R. Jensen. 2007. Remote Sensing of the Environment: An Earth Resource Perspective. Pearson Prentice Hall.