GE 110: Remote Sensing Lecture Notes PDF

GE 110: REMOTE SENSING Lecture 1: Concepts and Fundamentals of Remote Sensing ENGR. ARTURO G. CAUBA JR. Instructor I College of Engineering and Geosciences Caraga State University GE 110: Remote Sensing Lecture 1 Outline  Remo...

GE 110: REMOTE SENSING Lecture 1: Concepts and Fundamentals of Remote Sensing ENGR. ARTURO G. CAUBA JR. Instructor I College of Engineering and Geosciences Caraga State University GE 110: Remote Sensing Lecture 1 Outline  Remote Sensing Definitions Broad/informal definitions Formal Definitions Similarities and Differences of Remote Sensing with other fields  The Remote Sensing Process Key concepts and principles What are the processes? What are the elements involved? GE 110: Remote Sensing Lecture 1 Expected Outcomes The students would be able to: Understand and define on their own what ‘Remote Sensing’ is: Informally and formally/technically; Differentiate Remote Sensing from other fields of Geodetic Engineering; Identify the key concepts and principles of Remote Sensing; and Identify and describe the processes and elements involved in Remote Sensing. GE 110: Remote Sensing Lecture 1 REMOTE SENSING DEFINITIONS GE 110: Remote Sensing Lecture 1 What is Remote Sensing (RS)? Key words: “Remote” -> from afar/at a distance “Sensing” -> being aware of / detecting / acquiring information Some Broad/General/Informal Definitions: “knowing by looking/hearing/feeling from afar” “feeling without touching” “acquiring of data about an object without touching it” “acquiring information at a distance” GE 110: Remote Sensing Lecture 1 Formal / Technical Definitions of RS (1) Remote Sensing is the measurement or acquisition of information of some property of an object or phenomenon, by a recording device that is not in physical or intimate contact with the object or phenomenon under study. (American Society of Photogrammetry and Remote Sensing) GE 110: Remote Sensing Lecture 1 Formal / Technical Definitions of RS (2) Remote Sensing is the science and art of obtaining information about an object, area or phenomenon through the analysis of data acquired by a device that is not in contact with the object, area, or phenomenon under investigation. (Lillesand, Kiefer & Chipman, 2008) GE 110: Remote Sensing Lecture 1 Question: Of our five senses (sight, hearing, taste, smell, touch), three may be considered forms of "remote sensing", where the source of information is at some distance. The other two rely on direct contact with the source of information - which are they? GE 110: Remote Sensing Lecture 1 Remote Sensing as a Reading Process (1) Why is reading the texts in this slide considered a good example of Remote Sensing? GE 110: Remote Sensing Lecture 1 Remote Sensing as a Reading Process (2) Eyes -> acting as a sensor It responds to light reflected from this slide. The “data” your eyes acquire are impulses/signals corresponding to the amount of light reflected from the dark and light areas displayed on the slide. These data are analyzed, or interpreted, in your mental computer to enable you to explain the dark areas on the slide as a collection of letters forming words. Beyond this, you recognize that the words form a sentence, and you interpret the information that the sentences convey. And that information is: You are being asked why reading is a good example of Remote Sensing.  GE 110: Remote Sensing Lecture 1 Similarities and Differences of Remote Sensing with other fields Remote Sensing is much like surveying It can provide fundamental spatial information including z elevation, or depth Unlike much of surveying, Remote Sensing can obtain data over very large geographical areas rather than single-point observations. GIS and Cartography They are not used to obtain fundamental information They can be used to show/display/process fundamental information They rely on data obtained by others (one of which is Remote Sensing) GE 110: Remote Sensing Lecture 1 THE REMOTE SENSING PROCESS GE 110: Remote Sensing Lecture 1 Interaction of/with light energy The process can be summed up as the interaction between incident electromagnetic radiation (light energy) and the targets of interest, and how the results of the interaction are: captured by a remote sensor analyzed to extract useful information about the targets of interest for a specific application or purpose. GE 110: Remote Sensing Lecture 1 Seven Elements of the RS Process (1) GE 110: Remote Sensing Lecture 1 Seven Elements of the RS Process (2) A. Energy Source or Illumination B. Radiation and its Interaction with the Atmosphere C. The Interaction of the Radiation with the Target of Interest D. Recording of the Reflected/Emitted Energy by the Sensor E. Transmission, Reception and Processing F. Interpretation and Analysis G. Application GE 110: Remote Sensing Lecture 1 A. Energy Source or Illumination The first requirement for remote sensing is to have an energy source Illuminates or provides electromagnetic energy to the target of interest Common energy sources: The Sun The Sensor itself (releases its own energy) GE 110: Remote Sensing Lecture 1 B. RADIATION AND ITS INTERACTION WITH THE ATMOSPHERE As the energy travels from its source to the target, it will come in contact with, and interact with the atmosphere it passes through. This interaction may take place a second time as the energy travels from the target to the sensor Note that not all energy emitted by the source goes into the Earth’s surface GE 110: Remote Sensing Lecture 1 C. THE INTERACTION OF THE RADIATION WITH THE TARGET OF INTEREST Once the energy makes its way to the target through the atmosphere, it interacts with the target The interaction is dependent on the properties of both the target and the radiation. GE 110: Remote Sensing Lecture 1 D. RECORDING OF THE REFLECTED/EMITTED ENERGY BY THE SENSOR After the energy has been scattered by, or emitted from the target, we require a sensor (remote – not in contact with the target) to collect and record the reflected or emitted electromagnetic radiation. GE 110: Remote Sensing Lecture 1 E. TRANSMISSION, RECEPTION AND PROCESSING The energy recorded by the sensor has to be transmitted often in electronic form, to a receiving and processing station where the data are processed into an image. GE 110: Remote Sensing Lecture 1 F. INTERPRETATION AND ANALYSIS The processed image is interpreted, visually and/or digitally or electronically, to extract information about the target which was illuminated. GE 110: Remote Sensing Lecture 1 G. Application The final element of the remote sensing process is achieved when we apply the information that we have been able to extract from the imagery about the target in order to better understand it, reveal some new information, or assist in solving a particular problem. Some common applications Weather and climate monitoring Land-use/Land-cover mapping and change analysis Watershed management Disaster Management Natural Resource Mapping GE 110: Remote Sensing Lecture 1 Some examples of RS Application GE 110: Remote Sensing Lecture 1 Thank you for listening!   GE 110: REMOTE SENSING Lecture 2: Electromagnetic Radiation Principles ENGR. ARTURO G. CAUBA JR. Instructor I College of Engineering and Geosciences Caraga State University GE 110: Remote Sensing Lecture 1 Outline  Basics of Electromagnetic Radiation  Electromagnetic Radiation Interactions in the Atmosphere  Electromagnetic Radiation Interactions with Earth Surface Features GE 110: Remote Sensing Lecture 1 Expected Outcomes The students would be able to: Identify the role of electromagnetic radiation in the remote sensing process; Describe how electromagnetic energy interacts in the atmosphere; Describe how electromagnetic energy interacts with earth surface features; Identify the different responses of earth surface features to electromagnetic energy; and Relate how spectral signatures derived from recorded reflected EMR can aid in identifying objects from a remotely-sensed data. GE 110: Remote Sensing Lecture 1 BASICS OF ELECTROMAGNETIC RADIATION (EMR) GE 110: Remote Sensing Lecture 1 Review: 7 Elements of the Remote Sensing Process A. Energy Source or Illumination B. Radiation and its Interaction with the Atmosphere C. The Interaction of the Radiation with the Target of Interest D. Recording of the Reflected/Emitted Energy by the Sensor E. Transmission, Reception and Processing F. Interpretation and Analysis G. Application © CCRS/CCT GE 110: Remote Sensing Lecture 1 Why we need to study EMR as an energy source in the Remote Sensing process: Energy recorded by a Remote Sensing system undergoes fundamental interactions that should be understood to properly interpret remotely sensed data (e.g. images) Example: Sun as an energy source: Energy is radiated by atomic particles at the source It travels through the vacuum of space at the speed of light (3 x 108 m/s) It interacts with the atmosphere It interacts with the Earth’s surface It interacts with the Earth’s atmosphere once again, and It finally reaches the remote sensor It is helpful to examine each of these fundamental interactions that electromagnetic energy as it progresses from its source to the remote sensing system  GE 110: Remote Sensing Lecture 1 Review of Basic Energy Concepts Energy = the ability to do work In the process, Energy is often transferred: – from one body to another – from one place to another Three (3) basic ways in which energy can be transferred: Conduction: occurs when one body transfers its kinetic energy to another by colliding with it Convection: occurs when kinetic energy of bodies is transferred from one place to another by physically moving the bodies Radiation: occurs when kinetic energy of a body is emitted or transmitted (i.e., transferred) to another body in the form of waves or particles through space or through a material medium In Remote Sensing, transfer of energy by electromagnetic radiation is of primary interest GE 110: Remote Sensing Lecture 1 Electromagnetic Radiation (1) The radiant energy released by certain electromagnetic processes. Radiant = “glowing”, “beaming” Direct transfer of energy by electromagnetic waves A kind of radiation in which electric and magnetic fields vary simultaneously. Includes: visible light, radio waves, gamma rays, and X-rays GE 110: Remote Sensing Lecture 1 Electromagnetic Radiation (2) Based on wave theory, EMR travels in a harmonic, sinusoidal fashion at the “speed of light,” c. 𝒄 = 3 x 108 m/s It consists of an electrical field (E) which varies in magnitude in a direction perpendicular to the direction in which the radiation is traveling, and a magnetic field (M) oriented at right angles to the electrical field. 𝐸 = Electric vector 𝑀 = Magnetic vector 𝑐 = speed of light  GE 110: Remote Sensing Lecture 1 Characteristics of EMR Two characteristics of electromagnetic radiation are particularly important for understanding remote sensing. wavelength (λ) frequency (f) Wavelength = The length of one wave cycle, which can be measured as the distance between successive wave crests. Usually measured in micrometers (μm)or nanometers (nm) Frequency = frequency refers to the number of cycles of a wave passing a fixed point per unit of time. A wave that sends one crest by every second (completing one cycle) is said to have a frequency of one cycle per second or one hertz (1 Hz) GE 110: Remote Sensing Lecture 1 Relationship of Wavelength and Frequency Frequency is inversely proportional to wavelength The longer the wavelength, the lower the frequency The shorter the wavelength, the higher the frequency The speed of light and wavelength change while the frequency remains the same when electromagnetic radiation passes from one substance to another GE 110: Remote Sensing Lecture 1 Standard Units of Measurement: Wavelengths Wavelengths are usually expressed in the metric or SI system, since having multiples of 10 are more convenient. Wavelengths can range from many kilometers to extremely short lengths or fractions of a meter. GE 110: Remote Sensing Lecture 1 Standard Units of Measurement: Frequencies Frequencies are measured in hertz (Hz), which means cycles or wave crests per second. You can write the frequency with the symbol versions, as a large number or as an exponent. GE 110: Remote Sensing Lecture 1 Practice Problem (1) A sensor detected an incoming electromagnetic radiation (EMR) having a wavelength of 710 nanometer (nm). What is the equivalent wavelength of this EMR in: a. Micrometer (µm)? b. Millimeter (mm)? c. Meter (m)? GE 110: Remote Sensing Lecture 1 Practice Problem (2) An electromagnetic radiation (EMR) was found to have a frequency of 0.8 GHz as it passes through a vacuum. What is the equivalent frequency of this EMR in: a. Hertz (Hz)? b. KHz? c. MHz? GE 110: Remote Sensing Lecture 1 Practice Problem (3) An electromagnetic radiation (EMR) was found to have a frequency of 50 GHz as it passes through a vacuum. What would be its speed? GE 110: Remote Sensing Lecture 1 Practice Problem (4) An electromagnetic radiation (EMR) was found to have a frequency of 50 GHz as it passes through a vacuum. What would be its wavelength, in µm? GE 110: Remote Sensing Lecture 1 Practice Problem (5) Calculate the time needed for light to travel the distance of 1 m. GE 110: Remote Sensing Lecture 1 Electromagnetic Spectrum (1) Used to categorize electromagnetic radiation by their wavelength location Source: www.mpoweruk.com GE 110: Remote Sensing Lecture 1 Electromagnetic Spectrum (2) Source: http://1.bp.blogspot.com GE 110: Remote Sensing Lecture 1 Regions of the EMR Spectrum Useful for RS (1) Ultraviolet or UV portion of the spectrum has the shortest wavelengths which are practical for remote sensing. This radiation is just beyond the violet portion of the visible wavelengths, hence its name. Some Earth surface materials, primarily rocks and minerals, fluoresce or emit visible light when illuminated by UV radiation. GE 110: Remote Sensing Lecture 1 Regions of the EMR Spectrum Useful for RS (2) Visible Spectrum The light which our eyes - our "remote sensors" - can detect The visible wavelengths cover a range from approximately 0.4 to 0.7 μm. The longest visible wavelength is red and the shortest is violet. It is important to recognize how small the visible portion is relative to the rest of the spectrum. There is a lot of radiation around us which is "invisible" to our eyes, but can be detected by other remote sensing instruments and used to our advantage. GE 110: Remote Sensing Lecture 1 More on the Visible Spectrum Common wavelengths of what we perceive as Blue, green, and red are the primary colors or particular colors from the visible portion of the wavelengths of the visible spectrum. spectrum are: They are defined as such because no single Violet:0.4 -0.446 μm primary color can be created from the Blue:0.446 -0.500 μ m other two, but all other colors can be Green:0.500 -0.578 μ m formed by combining blue, green, and red Yellow:0.578 -0.592 μm in various proportions. Orange:0.592 -0.620 μm Red:0.620 -0.7 μm It is important to note that this is the only portion of the spectrum we can associate with the concept of colors. GE 110: Remote Sensing Lecture 1 More on the Visible Spectrum Although we see sunlight as a uniform or homogeneous color, it is actually composed of various wavelengths of radiation in primarily the ultraviolet, visible and infrared portions of the spectrum. The visible portion of this radiation can be shown in its component colors when sunlight is passed through a prism, which bends the light in differing amounts according to wavelength.  GE 110: Remote Sensing Lecture 1 Regions of the EMR Spectrum Useful for RS (3) The Infrared (IR) Region Covers the wavelength range from approximately 0.7 μm to 1000 μm (or 1 mm) The region useful for RS is approximately from 0.7μm to 14 μm can be divided into two categories based on their radiation properties: the reflected IR the emitted or thermal IR GE 110: Remote Sensing Lecture 1 More on the Infrared Region Reflected IR Region Radiation in the reflected IR region is used for remote sensing purposes in ways very similar to radiation in the visible portion. covers wavelengths from approximately 0.7 μm to 3.0 μm. Thermal IR Region the radiation that is emitted from the Earth's surface in the form of heat. covers wavelengths from approximately 3.0 um to 14 μm. GE 110: Remote Sensing Lecture 1 Regions of the EMR Spectrum Useful for RS (4) The Microwave Region Covers the wavelength range from approximately 1 mm to 1 m. Longer wavelength microwave radiation can penetrate through cloud cover, haze, dust, and all but the heaviest rainfall as the longer wavelengths are not susceptible to atmospheric scattering which affects shorter optical wavelengths. This property allows detection of microwave energy under almost all weather and environmental conditions so that data can be collected at any time. GE 110: Remote Sensing Lecture 1 Relationship between Energy and Frequency Based on particle theory, EMR is composed of many discrete units called photons or quanta The energy (Q) of a quantum is given as: Q = hf Q is in Joules (J) h = Planck’s constant = 6.63 x 10-34 J seconds f = frequency Since c = λf, then Q = hc/λ The energy of a quantum is inversely proportional to its wavelength The longer the wavelength, the lower its energy content This suggests that it is more difficult to detect longer wavelength energy being emitted at thermal infrared wavelengths than those at shorter visible wavelengths GE 110: Remote Sensing Lecture 1 Practice Problem (6) Given λ = 3.53 m, c = 3 x 108 m/s and h = 6.63 x 10-34 J s, Plank’s constant, Calculate the frequency and the energy of the photon Q. GE 110: Remote Sensing Lecture 1 Practice Problem (7) A very large round object in outer space was found to emit energy in the form of electromagnetic radiation amounting to 1.45 x 10-20 Joules (J) based on a measurement by a remote sensor orbiting the Earth. It was also found that the energy was being emitted at the speed of light. The time it took for the emitted radiation to reach the sensor was 5 minutes. Given that the Planck’s constant is 6.63 x 10-34 Joules seconds (J s), determine the following: 1. Frequency of the radiation, in KHz. 2. Wavelength of the radiation, in µm 3. Distance (in km) of the object from the remote sensor 4. In what region of the EMR is the radiation’s wavelength located? GE 110: Remote Sensing Lecture 1 Further Reading Fundamentals of Remote Sensing (Online Tutorial). Available at https://natural-resources.canada.ca/maps-tools-and- publications/satellite-imagery-and-air-photos/tutorial-fundamentals- remote-sensing/9309 Focus on Chapter 1 GE 110: Remote Sensing Lecture 1 Thank you for listening!  GE 110: Remote Sensing Lecture 2 GE 110: REMOTE SENSING Lecture 2: Electromagnetic Radiation Principles (Continuation) ENGR. ARTURO G. CAUBA JR. Instructor I College of Engineering and Geosciences Caraga State University GE 110: Remote Sensing Lecture 2 Review Question (1) In remote sensing, it is used to record energy reflected or emitted from the earth’s surface a. Satellite b. Radiator c. Device d. Sensor e. All of the above  GE 110: Remote Sensing Lecture 2 Review Question (2) The visible portion of the electromagnetic spectrum refers to: a. The region whose wavelength ranges from 400 to 700 nm b. The only portion of the spectrum we can associate with the concept of color c. The portion where the longest wavelength is red and the shortest is violet d. All of the above e. None of the above GE 110: Remote Sensing Lecture 2 ELECTROMAGNETIC RADIATION (EMR) INTERACTIONS IN THE ATMOSPHERE GE 110: Remote Sensing Lecture 2 Review: 7 Elements of the Remote Sensing Process A. Energy Source or Illumination B. Radiation and its Interaction with the Atmosphere C. The Interaction of the Radiation with the Target of Interest D. Recording of the Reflected/Emitted Energy by the Sensor E. Transmission, Reception and Processing F. Interpretation and Analysis G. Application © CCRS/CCT GE 110: Remote Sensing Lecture 2 Review of Basic EMR concepts (1) EMR: travels in a harmonic, sinusoidal fashion at the “speed of light,” c consists of an electrical field (E) which varies in magnitude in a direction perpendicular to the direction in which the radiation is Wavelength = The length of one wave cycle, traveling, and a magnetic field (M) oriented at right angles to the which can be measured as the distance electrical field. between successive wave crests. Usually measured in micrometers (μm)or Wavelength (λ), Frequency (f) and Energy (Q) nanometers (nm) Frequency is inversely proportional to wavelength Frequency = frequency refers to the number The longer the wavelength, the lower the frequency of cycles of a wave passing a fixed point per unit of time. The shorter the wavelength, the higher the frequency A wave that sends one crest by every second When electromagnetic radiation passes from one substance to (completing one cycle) is said to have a another, the speed of light and wavelength change while the frequency of one cycle per second or one frequency remains the same hertz (1 Hz) The energy of a quantum/photon (light particle) is inversely proportional to its wavelength c = λf Q = hf The longer the wavelength, the lower its energy content Q = hc/λ GE 110: Remote Sensing Lecture 2 Review of Basic EMR concepts (2) The EMR Spectrum Regions/Portions of EMR Spectrum useful for RS –Ultraviolet (UV) Region: 10 nm to 10 times) Water droplets and large dust particles can cause this type of scattering. Non-selective scattering gets its name from the fact that all wavelengths are scattered about equally. This type of scattering causes fog and clouds to appear white to our eyes because blue, green, and red light are all scattered in approximately equal quantities: blue + green + red light = white light GE 110: Remote Sensing Lecture 2 Why Are Rain Clouds Gray Or Dark? Because of their thickness, or height. That is, a cloud gets thicker and denser as it gathers more water droplets and ice crystals —the thicker it gets, the more light it scatters, resulting in less light penetrating all the way through it. This effect becomes more pronounced the The particles on the underside of the rain larger the water droplets get —such as right cloud don't have a lot of light to scatter to before they're large enough to fall from the sky as rain —because they become more efficient your eyes, so the base appears gray as you at absorbing light, rather than scattering it. look on from the ground below. GE 110: Remote Sensing Lecture 2 Atmospheric Scattering Effects On Remote Sensing Images It severely reduce the information content of remotely sensed data The imagery loses contrast It becomes difficult to differentiate one object from another. Image blurring The EMR scattered by the atmosphere towards the sensor without first reaching the ground produces a hazy appearance of the image. This effect is particularly severe in the blue end of the visible spectrum due to the stronger Rayleigh Scattering for shorter wavelength radiation. GE 110: Remote Sensing Lecture 2 Atmospheric Absorption (1) In contrast to scattering, this phenomenon causes molecules in the atmosphere to absorb energy at various wavelengths. Absorption is the process by which incident EMR is absorbed and converted into other forms of energy Reduces the amount of EMR reaching the Earth’s surface GE 110: Remote Sensing Lecture 2 Atmospheric Absorption (2) Main atmospheric constituents which absorb radiation: Water vapour Carbon dioxide Oxygen Ozone Nitrous oxide The cumulative effect of the absorption by the various constituents can cause the atmosphere to “close down” completely in certain regions of the spectrum. Portions of the spectrum where absorption is minimal and transmit EMR effectively are called atmospheric windows. These portions are being taken advantage by Remote Sensing GE 110: Remote Sensing Lecture 2 Atmospheric Windows The visible portion of the spectrum, to which our eyes are most sensitive, corresponds to both an atmospheric window and the peak energy level of the sun. Heat energy emitted by the Earth corresponds to a window around 10 μm in the thermal IR portion of the spectrum, while the large window at wavelengths beyond 1 mm is associated with the microwave region. GE 110: Remote Sensing Lecture 2 ELECTROMAGNETIC RADIATION (EMR) INTERACTIONS WITH EARTH SURFACE FEATURES GE 110: Remote Sensing Lecture 2 Review: 7 Elements of the Remote Sensing Process A. Energy Source or Illumination B. Radiation and its Interaction with the Atmosphere C. The Interaction of the Radiation with the Target of Interest D. Recording of the Reflected/Emitted Energy by the Sensor E. Transmission, Reception and Processing F. Interpretation and Analysis G. Application © CCRS/CCT GE 110: Remote Sensing Lecture 2 EMR Interaction with a Target Radiation that is not absorbed or scattered in the atmosphere can reach and interact with the Earth's surface. The interaction is dependent on the properties of both the target and the radiation Three (3) forms of interactions: Absorption Transmission Reflection The total incident energy will interact with the surface in one or more of these three ways. GE 110: Remote Sensing Lecture 2 Absorption Vs. Transmission Vs. Reflection Absorption (A) occurs when radiation (energy) is absorbed into the target Transmission(T) occurs when radiation passes through a target. Reflection (R) occurs when radiation "bounces" off the target and is redirected. In Remote Sensing, we are most interested in measuring the radiation reflected from targets. GE 110: Remote Sensing Lecture 2 GE 110: Remote Sensing Lecture 2 Types of Reflection Specular Reflection “mirror-like” reflection occur when incident EMR interacts with a smooth surface and all (or almost all) of the energy is directed away from the surface in a single direction. Diffuse Reflection occurs when incident EMR interacts with a rough surface and the energy is reflected almost uniformly in all directions. The ideal form of diffuse reflection is called Lambertian reflectance GE 110: Remote Sensing Lecture 2 Specular Reflection Illustrations GE 110: Remote Sensing Lecture 2 Diffuse Reflection Illustrations GE 110: Remote Sensing Lecture 2 Specular vs Diffuse: Which one will dominate?(1) Most earth surface features lie somewhere between perfectly specular or perfectly diffuse reflectors. Whether a particular target reflects specularly or diffusely, or somewhere in between, depends on the surface roughness of the feature in comparison to the wavelength of the incoming radiation. GE 110: Remote Sensing Lecture 2 Specular vs Diffuse: Which one will dominate?(2) Diffuse reflection – if the wavelengths are much shorter than the surface variations or the particle sizes that make up the surface. Example: fine-grained sand would appear quite rough to the visible wavelengths but would appear fairly smooth to long wavelength microwaves. GE 110: Remote Sensing Lecture 2 Role of Reflection, Absorption &Transmission In Remote Sensing Of Earth Features (1) Various fractions of the energy incident (I) on the surface features are reflected (R), absorbed (A), and/or transmitted (T) 𝑬I(𝝀)= 𝑬R(𝝀) + 𝑬A(𝝀 )+ 𝑬T(𝝀) all energy components are a function of wavelength (λ) The proportions of energy reflected, absorbed, and transmitted vary for different earth features, depending on their material type and condition. These differences permit us to distinguish different features on an image GE 110: Remote Sensing Lecture 2 Role of Reflection, Absorption &Transmission In Remote Sensing Of Earth Features (2) The wavelength dependency means that, even within a given feature type, the proportion of reflected, absorbed, and transmitted energy will vary at different wavelengths. This important property makes it possible to identify different features and separate them by their spectral signatures.  GE 110: Remote Sensing Lecture 2 Spectral Signature And Spectral Reflectance Spectral signature – the Spectral reflectance has different values at difference in the reflectance different wavelengths for a given feature. characteristics with respect to wavelengths Spectral reflectance (ρ): the ratio of reflected radiation to incident radiation as a function of wavelength. ρ(λ)= (𝑬R(𝝀) / 𝑬I(𝝀)) x 100 GE 110: Remote Sensing Lecture 2 Spectral Reflectance of Vegetation (1) The spectral characteristics of vegetation vary with wavelength. Plant pigment in leaves called chlorophyll strongly absorbs radiation in the red and blue wavelengths but reflects green wavelength. The internal structure of healthy leaves acts as diffuse reflector of near infrared wavelengths. Measuring and monitoring the near infrared reflectance is one way that scientists determine how healthy a particular vegetation may be.  GE 110: Remote Sensing Lecture 2 Spectral Reflectance of Vegetation (2) Plant reflectance in the 0.7 to 1.3 μm range results primarily from the internal structure of plant leaves. Because this structure is highly variable between plant species, reflectance measurements in this range often permit us to discriminate between species, even if they look the same in visible wavelengths. Beyond 1.3 μm, energy incident upon vegetation is essentially absorbed or reflected, with little to no Dips in reflectance occur at transmittance of energy 1.4, 1.9, and 2.7 μm because Throughout the range beyond 1.3 μm, leaf reflectance is water in the leaf absorbs approximately inversely related to the total water strongly at these present in a leaf. wavelengths This total is a function of both the moisture content and the - wavelengths in these thickness of a leaf. spectral regions are referred to as water absorption bands GE 110: Remote Sensing Lecture 2 Spectral Reflectance of Water Majority of the radiation incident upon water is not reflected but is either absorbed or transmitted. Longer visible wavelengths and near infrared radiation is absorbed more by water than by the visible wavelengths. water looks blue or blue green due to stronger reflectance at these shorter wavelengths and darker if viewed at red or near infrared wavelengths. Factors that affect the variability in reflectance of a water body are depth of water, materials within water and surface roughness of water. GE 110: Remote Sensing Lecture 2 Spectral Reflectance of Soil The majority of radiation incident on a soil surface is either reflected or absorbed and little is transmitted. The soil reflectance curve shows less peak and valley variations. The presence of moisture in soil decreases its reflectance. The characteristics of soil that determine its reflectance properties are: moisture content organic matter content Texture structure iron oxide content. GE 110: Remote Sensing Lecture 2 Important Notes: Spectral response can be quite variable, even for the same target type, and can also vary with time (e.g. "green-ness" of leaves) and location. Knowing where to "look" spectrally and understanding the factors which influence the spectral response of the features of interest are critical to correctly interpreting the interaction of electromagnetic radiation with the surface. By measuring the energy that is reflected by targets on earth’s surface over a variety of different wavelengths, we can build up a spectral signature for that object. And by comparing the response pattern of different features, we may be able to distinguish between them, which we may not be able to do if we only compare them at one wavelength. GE 110: Remote Sensing Lecture 2 References: Jensen, J.R. (2007). Remote Sensing of the Environment: An Earth Resource Perspective, 2nd Edition. New Jersey: Pearson Education/Prentice Hall. Campbell, J. B., & Wynne, R. H. (2011). Introduction to Remote Sensing 5th Edition. New York: The Guilford Press. Lillesand, T. M., Kiefer, R. W., & Chipman, J. W. (2008). Remote Sensing and Image Interpretation 6th Edition. United States of America: John Wiley & Sons, Inc. Fundamentals of Remote Sensing (Online Tutorial). Available at http://www.nrcan.gc.ca/node/9309 GE 110: Remote Sensing Lecture 2 Thank you for listening!   GE 110: REMOTE SENSING Lecture 3: Remote Sensing Data Collection ENGR. ARTURO G. CAUBA JR. Instructor I College of Engineering and Geosciences Caraga State University GE 110: Remote Sensing Lecture 3 Outline  Basic Concept of Reflected EMR measured by Sensors  Detection and Recording of Reflected EMR  Transmission, Reception and Processing of Remotely-sensed Data  Example Satellite Remote Sensing Systems and their Characteristics GE 110: Remote Sensing Lecture 3 Expected Outcomes The students would be able to: Understand the concepts behind the recording of reflected EMR by the sensor; Identify the different types of sensors, instruments and platforms used in collecting remote sensing data; Identify the different sensor characteristics and resolution properties; Understand how data is transmitted, received and processed from the remote sensing platforms; and Differentiate different satellite remote sensing systems according to their characteristics and resolution properties. GE 110: Remote Sensing Lecture 3 Review: 7 Elements of the Remote Sensing Process A. Energy Source or Illumination B. Radiation and its Interaction with the Atmosphere C. The Interaction of the Radiation with the Target of Interest D. Recording of the Reflected/Emitted Energy by the Sensor E. Transmission, Reception and Processing F. Interpretation and Analysis G. Application © CCRS/CCT GE 110: Remote Sensing Lecture 3 PART 1. BASIC CONCEPT OF REFLECTED/ EMITTED EMR MEASURED BY SENSORS  GE 110: Remote Sensing Lecture 3 What is measured by the sensor? The energy budget equation can be re- Recall that: written in terms of radiant flux (Φ): Various fractions of the Φ I(𝝀)= Φ R(𝝀) + Φ A(𝝀 )+ Φ T(𝝀) energy incident (I) on the The total amount of radiant flux in surface features are specific wavelengths incident to the reflected (R), absorbed (A), surface must be accounted for by and/or transmitted (T) evaluating the amount of radiant flux 𝑬I(𝝀)= 𝑬R(𝝀) + 𝑬A(𝝀 )+ 𝑬T(𝝀) reflected from the surface, the all energy components are a amount of radiant flux absorbed by function of wavelength (λ) the surface, and the amount of radiant flux transmitted through the surface. GE 110: Remote Sensing Lecture 3 Radiant Flux Also known as radiant power It refers to the total amount of electromagnetic energy (usually in the form of light or electromagnetic radiation) that is emitted, transmitted, or received per unit of time (Energy per unit time). It represents the rate at which radiant energy is flowing through a given area. Measured in “Watts” (W) 1 Watt = 1 Joules/s GE 110: Remote Sensing Lecture 3 Radiant Flux Density Most remote sensing systems are in space, and they usually look only at a relatively small portion of the Earth at a single instant. Consider a flat area (e.g., 1x1m in dimension) being bath in radiant flux (Φ) in specific wavelength (λ) from the Sun: The amount of radiant flux intercepted divided by the area of the plane surface is the average radiant flux density (W per unit area) GE 110: Remote Sensing Lecture 3 Types of Radiant Flux Density, usually measured in Watts per m 2. Irradiance (E) The amount of radiant flux incident upon a surface per unit area of the surface Incoming energy per unit time and area Exitance (M) or Reflected Radiance The amount of radiant flux leaving (“reflected” from) a surface per unit area of the surface Leaving energy per unit time and area GE 110: Remote Sensing Lecture 3 Radiance (1) The most precise remote sensing radiometric measurement A form of exitance but the direction of the leaving radiant flux is specified Formally defined as the “radiant intensity per unit of projected source area in a specified direction” Measured in Watts per square meter per steradian W m-2 sr-1 Radiance is the physical quantity being measured by a remote sensor GE 110: Remote Sensing Lecture 3 Radiance (2) The radiant flux leaves the projected source area in a specific direction toward the remote sensor Note: we are not concerned with any other radiant flux that might be leaving the source area in any other direction We are interested only in radiant flux in certain wavelengths (λ) leaving the projected source area (A) within a certain direction (cos θ ) and solid angle Ω GE 110: Remote Sensing Lecture 3 The Solid Angle symbol: Ω a three-dimensional angle that an object subtends at a point. In general, it is a measure of how large the object appears to an observer looking from that point An object's solid angle in steradians is equal to the area of the segment of a unit sphere, centered at the angle’s vertex, that the object covers. The solid angle of an object that is very far away is roughly proportional to the ratio of area to squared distance. Here "area" means the area of the object when projected along the viewing direction. GE 110: Remote Sensing Lecture 3 Recording of Radiance by the Sensor (1) Ideally, the radiance (L) recorded by the sensor is a true function of the amount of radiance leaving the target surface/feature within the sensor’s instantaneous field of view (IFOV) at a specific solid angle. These other radiant energy entering the IFOV is called “Path Radiance” Path radiance is usually removed during the processing of remotely-sensed data through various methods. GE 110: Remote Sensing Lecture 3 Recording of Radiance by the Sensor (2) Unfortunately, other radiant energy may enter the IFOV from various other paths and introduce confounding noise into the remote sensing process such as: Spectral solar irradiance that was attenuated before illuminating the target surface within the IFOV Diffuse sky irradiance that never even reaches the earth because of atmospheric scattering Energy from the sun that has undergone atmospheric scattering and absorption before illuminating the target surface Radiation that was also reflected from neighboring area into the atmosphere, but then scattered or reflected onto the target surface. Radiation that was reflected or scattered from a neighboring area  GE 110: Remote Sensing Lecture 3 Radiance versus Reflectance Radiance Reflectance Basically, you can think of radiance as how Reflectance is the ratio of the amount of much light the instrument "sees" from the light leaving a target to the amount of light object being observed. striking the target. Unit: W m-2 sr-1 It has no units. Radiance depends on the illumination Reflectance is a property of the material (both its intensity and direction), the being observed. orientation and position of the target and Reflectance is calculated from the reflected the path of the light through the radiance over the irradiance at a certain atmosphere. horizontal plane. Radiance is the variable directly measured ρ(λ)= (M(𝝀) / 𝑬(𝝀)) by remote sensing instruments. GE 110: Remote Sensing Lecture 3 Spectral Radiance Spectral radiance = is the radiance per wavelength interval, measured in Watts per square meter per steradian per micrometer (Wm-2sr-1µm-1) GE 110: Remote Sensing Lecture 3 How does a Remote Sensor capture or record Radiance? One way of visualizing this process is to consider what you would see if you were in an airplane looking at the ground through a telescope (“the sensor”). Only the energy that exited the terrain and came up to and through the telescope in a specific solid angle would be intercepted by the telescope and viewed by your eye More explanation later. GE 110: Remote Sensing Lecture 3 PART 2. DETECTION AND RECORDING OF REFLECTED / EMITTED EMR GE 110: Remote Sensing Lecture 3 Classification of Remote Sensors (1) PASSIVE SENSORS – Sensors which sense natural radiation, either emitted or reflected from the earth Passive sensors can only be used to detect energy when the naturally occurring energy source is available. – E.g., the SUN – For all reflected energy, this can only take place during the time when the sun is illuminating the Earth. Energy that is naturally emitted (such as thermal infrared) can be detected Passive sensors depend on day or night, as long as the amount of the Sun as the source of energy is large enough to be recorded. illumination. Also called as”Optical” sensors because they record reflected EMR in the visible Basic example: “Camera to thermal infrared regions. without flash”  GE 110: Remote Sensing Lecture 3 Classification of Remote Sensors (2) ACTIVE SENSORS emit radiation which is directed toward the target to be investigated. – The radiation reflected from that target is detected and measured by the sensor. Advantages for active sensors include the ability to obtain measurements anytime, regardless of the time of day or season. Active sensors can be used for examining wavelengths that are not sufficiently provided by the sun, such as microwaves, or to better control the way a target is illuminated. Active sensors provide their own energy source Active systems require the generation of a fairly for illumination. large amount of energy to adequately illuminate targets. Basic example: “Camera with flash activated to take a picture in a dark room” GE 110: Remote Sensing Lecture 3 Remote Sensing Platforms Platforms for remote sensors may be For a sensor to collect and record situated: energy reflected or emitted from a on the ground, on an aircraft (or some other target or surface, it must reside platform within the Earth's on a platform away from the atmosphere), target or surface being observed. or on a spacecraft or satellite outside of the Earth's atmosphere.  GE 110: Remote Sensing Lecture 3 Example of Ground-based Remote Sensor Ground-based sensors are often used to record detailed information about the surface which is compared with information collected from aircraft or satellite sensors. Common example: – Spectroradiometer – an instrument that is used to determine spectral response of various features GE 110: Remote Sensing Lecture 3 Examples of Aircraft-based Remote Sensors Aerial Camera installed in a plane LiDAR (Light Detection and Ranging) Camera installed in an unmanned aerial vehicle (UAV) GE 110: Remote Sensing Lecture 3 Examples of Space-based Remote Sensors Remote sensing satellites like: – MODIS – Landsat 5, 7, 8 – Quickbird – Worldview 1, 2, 3 – ASTER VNIR – etc GE 110: Remote Sensing Lecture 3 How does a Remote Sensor capture or record Radiance? 25 GE 110: Remote Sensing Lecture 3 Illustration of how a sensor records radiance (across-track scanner/whiskbroom sensor) Reflected energy detectors Emitted energy detectors The electromagnetic energy/radiance entering the sensor is split into multiple spectral bands, with each wavelength range being directed toward a specific detector (one detector per band)  The radiance detected by each detector now has a wavelength component which is now what we call as “Spectral Radiance” GE 110: Remote Sensing Lecture 3 Detection and Recording of Radiance (1) The sensor (e.g., some type of detector) on- board a moving platform captures radiances and records it into an image consisting of the radiance spatial distribution At any instant in time, the sensor “sees” the reflected or emitted energy within the system’s instantaneous field of view (IFOV) IFOV: normally expressed as the cone angle (solid angle) within which incident energy is focused on the detector All energy propagating toward the sensor within the IFOV contributes to the detector response at any instant.  GE 110: Remote Sensing Lecture 3 Detection and Recording of Radiance (2) More than 1 land-cover maybe included in the IFOV at any given instant and the composite signal response will be recorded. – An image typically contain a combination of “pure” and “mixed” pixels, depending upon the IFOV and the spatial complexity of the ground features. GE 110: Remote Sensing Lecture 3 Detection and Recording of Radiance (3) Converting from radiance to electrical signal to image data: – The electrical response from each detector is a continuous analog signal – Digital images are created by quantizing an analog electrical signal, through a process known as analog-to-digital (A-to-D) conversion 29 GE 110: Remote Sensing Lecture 3 Analog-to-Digital Conversion GE 110: Remote Sensing Lecture 3 Detection and Recording of Radiance (4) Analog-to-digital (A-to-D) conversion: – The electrical response from each detector is usually in terms of an electrical voltage – During acquisition, the continuous signal is sampled at a set time interval (∆T) and recorded numerically at each sample point – For each value of electrical voltage, there is a corresponding Digital Number (DN)  GE 110: Remote Sensing Lecture 3 Detection and Recording of Radiance (5) Analog-to-digital (A-to-D) conversion (continuation): Each sampled value of an analog signal is converted to a DN, and then recorded and stored into its equivalent “binary number” (i.e., series of 0s and 1s) E.g., if the DN is 10, then it will be converted into its binary form (which is 1010 --> “1010” will be the one stored not “10”) – The recorded “binary numbers” are decoded (e.g., by a computer) to get the corresponding “DN” values to form an image GE 110: Remote Sensing Lecture 3 More about DNs Typically, the DNs recorded and stored by the sensor in binary forms have defined numerical ranges such as: o 0 - 255 o 0 – 511 o 0 – 1023 o Or higher These ranges represent the set of integers that can be recorded using 8-, 9-, and 10-bit binary computer coding scales – i.e.,: 28 = 256 29 = 512 210 = 1024 – In general: DN range: [0 to (2n-1)] where n = the number of bits which corresponds to what we will call as the sensor’s “radiometric resolution” GE 110: Remote Sensing Lecture 3 Detection and Recording of Radiance (6) Analog-to-digital (A-to-D) conversion (continuation): Each DN value is correlated with Spectral Radiance e.g., we can compute for Spectral Radiance given a DN value using a sensor-specific formula relating DN with radiance) The conversion of DN values to Spectral Radiance is an important part of “Radiometric Calibration”. 34 GE 110: Remote Sensing Lecture 3 Example sensor-specific formula relating DN with Spectral Radiance GE 110: Remote Sensing Lecture 3 Some questions: Why record and store the radiance as “DNs in binary form” instead of the spectral radiance value itself? – Why not directly record the actual value of spectral radiance? Answer: – Storing using the binary system can save a lot in storage space: A binary file is usually very much smaller than a text file that contains an equivalent amount of data Small files save storage space, can be transmitted faster, and are processed faster. – This is very important when Remote Sensing data is transmitted from the satellites to the ground receiving station for processing to form images GE 110: Remote Sensing Lecture 3 Characteristics of Digital Image Data (1) Image = a matrix of DN values Each DN is located at a specific row and column in the matrix Pixel: - the smallest unit of an image. - image pixels are normally square and represent a certain area on an image (e.g., the ground segment within the sensor’s IFOV) - Each pixel has DN value associated with it. GE 110: Remote Sensing Lecture 3 Characteristics of Digital Image Data (2) Typically, the DNs constituting a digital image are recorded over such numerical ranges as: o 0 - 255 o 0 – 511 o 0 – 1023 o Or higher These ranges represent the set of integers that can be recorded using 8-, 9-, and 10- bit binary computer coding scales – i.e.,: 28 = 256 29 = 512 210 = 1024 – In general: DN range: [0 to (2n-1)] where n = the number of bits (radiometric resolution)  GE 110: Remote Sensing Lecture 3 Characteristics of Digital Image Data (3) DNs describe the information content in an image. The DNs represent the strength of signal that was detected and recorded by the sensor Also called “brightness values” – The maximum number of brightness levels available depends on the number of bits used in representing the energy recorded. The higher the range of the DN values in an image, the more sensitive the sensor is to differences in signal strength This property is called “Radiometric Resolution” GE 110: Remote Sensing Lecture 3 Sensor Radiometric Resolution Radiometric resolution – defined as the sensitivity of a remote sensor to differences in signal strength as it records radiance from the earth’s surface. A sensor capable of recording DN values ranging from 0- 1023 (10- bit) is said to have a higher radiometric resolution than a sensor that can record DN values ranging from 0-255 (8-bit). Important of higher radiometric resolution: – the more sensitive it is to detecting small differences in reflected or emitted energy. – The more precise we may be able to measure the amount of radiance recorded by the sensor GE 110: Remote Sensing Lecture 3 Sensor Radiometric Resolution (2) 2-bit image 8-bit image By comparing a 2-bit image with an 8-bit image, we can see that there is a large difference in the level of detail discernible depending on their radiometric resolutions. GE 110: Remote Sensing Lecture 3 Sensor’s Spatial Resolution (1) The ground segment sensed at any instant is called the ground resolution element or ground resolution cell. The size of the ground area sensed at any instant in time is loosely referred to as the system’s spatial resolution. In a digital image, the spatial resolution corresponds to the pixel size GE 110: Remote Sensing Lecture 3 Sensor’s Spatial Resolution (2) Spatial resolution refers to the size of the smallest possible feature that can be detected. Spatial resolution is dependent on IFOV. – A small IFOV is desirable to record fine spatial detail – A larger IFOV means a greater quantity of total energy is focused on a detector as it scans the ground resolution cell Larger IFOV = higher signal-to-noise ratio This permits more sensitive scene radiance measurements due to higher signal levels The result is an improvement in Radiometric Resolution. What is sacrificed is spatial resolution. GE 110: Remote Sensing Lecture 3 Sensor’s Spatial Resolution (3) GE 110: Remote Sensing Lecture 3 Comparison of different spatial resolutions High resolution Medium resolution Low resolution © GISGeography GE 110: Remote Sensing Lecture 3 Spatial Resolution Effects on Image Quality Pixel size = 17 km 9 km 1 km 46 GE 110: Remote Sensing Lecture 3 Sensor Spectral Resolution Spectral resolution is the ability of a sensor to resolve features within specific wavelengths of the optical spectrum and slice wavelengths into smaller increments. It specifies the number of spectral bands in which the sensor can collect reflected radiance. The finer the spectral resolution, the narrower the wavelength range for a particular channel or band. GE 110: Remote Sensing Lecture 3 Sensor Spectral Resolution (2) GE 110: Remote Sensing Lecture 3 Sensor’s Temporal Resolution The ability of a sensor to image the exact same area at the same viewing angle a second time around. The higher the temporal resolution, the shorter the length of time between the acquisitions of images. GE 110: Remote Sensing Lecture 3 Classification of Sensors based on Scanning Modes/Methods (or “Sensor Technology”) ACROSS-TRACK ALONG-TRACK SCANNER SCANNER “Whisk broom sensor” “Push broom sensor” GE 110: Remote Sensing Lecture 3 Across-track scanner Characteristics Scans the Earth in a series of lines. – The lines are oriented perpendicular to the direction of motion of the sensor platform (i.e. across the swath). – Each line is scanned from one side of the sensor to the other, using a rotating mirror. – As the platform moves forward over the Earth, successive scans build up a two- dimensional image of the Earth´s surface. The IFOV (C) of the sensor and the altitude of the platform determine the ground resolution cell viewed (D), and thus the spatial resolution. Because the distance from the sensor to the target increases The length of time the IFOV "sees" a towards the edges of the swath, the ground resolution cell as the rotating ground resolution cells also become mirror scans (called the dwell time), is larger and introduce geometric generally quite short and influences the distortions to the images. design of the spatial, spectral, and radiometric resolution of the sensor.  GE 110: Remote Sensing Lecture 3 Recording of Reflected/Emitted Radiation by an Across-track Scanner: The incoming reflected or emitted radiation is separated into several spectral components that are detected independently. The UV, visible, near-infrared, and thermal radiation are dispersed into their constituent wavelengths. A bank of internal detectors, each sensitive to a specific range of wavelengths, detects and measures the energy for each spectral band and then, as an electrical signal, they are converted to digital data and recorded for subsequent computer processing.  GE 110: Remote Sensing Lecture 3 Along-track scanner Characteristics also uses the forward motion of the platform to record successive scan lines and build up a two- dimensional image, perpendicular to the flight direction. instead of a scanning mirror, they use a linear array of detectors located at the focal plane of the image formed by lens systems, which are "pushed" along in the flight track direction (i.e. along track). These systems are also referred to as pushbroom scanners, as the motion of the detector array is analogous to the bristles of a broom being pushed along a floor.  GE 110: Remote Sensing Lecture 3 Recording of Reflected/Emitted Radiation by an Along-track Scanner: Each individual detector measures the energy for a single ground resolution cell (D) and thus the size and IFOV of the detectors determines the spatial resolution of the system. A separate linear array is required to measure each spectral band or channel. For each scan line, the energy detected by each detector of each linear array is sampled electronically and digitally recorded. GE 110: Remote Sensing Lecture 3 Advantages of Along-track Scanners/Pushbroom Sensors The array of detectors combined with the pushbroom motion allows each detector to "see" and measure the energy from each ground resolution cell for a longer period of time (dwell time). This allows more energy to be detected and improves the radiometric resolution. The increased dwell time also facilitates smaller IFOVs and narrower bandwidths for each detector. Thus, finer spatial and spectral resolution can be achieved without impacting radiometric resolution. 55 GE 110: Remote Sensing Lecture 3 GE 110: REMOTE SENSING Lecture 3: Remote Sensing Data Collection (Continuation) ENGR. ARTURO G. CAUBA JR. Instructor I College of Engineering and Geosciences Caraga State University GE 110: Remote Sensing Lecture 3 Question (1): If the spectral range of the 288 channels of the CASI (Compact Airborne Spectrographic Imager) is exactly 0.40 µm to 0.90 µm and each band covers a wavelength of 1.8 nm (nanometres, 10-9 m), will there be any overlap between the bands? GE 110: Remote Sensing Lecture 3 Question (2): Suppose you have a digital image which has a radiometric resolution of 6 bits. What is the maximum value of the digital number which could be represented in that image? GE 110: Remote Sensing Lecture 3 Question (3): How would thermal imagery be useful in an urban environment? GE 110: Remote Sensing Lecture 3 PART 3. TRANSMISSION, RECEPTION AND PROCESSING OF REMOTELY SENSED DATA GE 110: Remote Sensing Lecture 3 Review: 7 Elements of the Remote Sensing Process A. Energy Source or Illumination B. Radiation and its Interaction with the Atmosphere C. The Interaction of the Radiation with the Target of Interest D. Recording of the Reflected/Emitted Energy by the Sensor E. Transmission, Reception and Processing F. Interpretation and Analysis G. Application © CCRS/CCT  GE 110: Remote Sensing Lecture 3 Data Reception, Transmission, and Processing: Airborne Remote Sensing Data obtained during airborne remote sensing missions can be retrieved once the aircraft lands http://english.ceode.cas.cn/rs/Facilities/AirborneRS/ It can then be processed and delivered to the end user. GE 110: Remote Sensing Lecture 3 Data Reception, Transmission, and Processing: Spaceborne Remote Sensing Data acquired from satellite platforms © niitp.ru need to be electronically transmitted to Earth – Why?  Because the satellite continues to stay in orbit during its operational lifetime. (We cannot let it land on the earth’s surface and The technologies designed to accomplish this retrieve the data!) can also be used by an aerial platform if the data are urgently needed on the surface. GE 110: Remote Sensing Lecture 3 Three (3) Options for Transmitting Data from Satellites 64 GE 110: Remote Sensing Lecture 3 Three (3) Options for Transmitting Data from Satellites 1. The data can be directly transmitted to Earth if a Ground Receiving Station (GRS) is in the line of sight of the satellite (A). GE 110: Remote Sensing Lecture 3 Three (3) Options for Transmitting Data from Satellites 2. If option 1 is not possible, the data can be recorded on board the satellite (B) for transmission to a Ground Receiving Station (GRS) at a later time. GE 110: Remote Sensing Lecture 3 Three (3) Options for Transmitting Data from Satellites 3. Data can also be relayed to the GRS through the Tracking and Data Relay Satellite System (TDRSS) (C) The TDRSS consists of a series of communications satellites in geosynchronous orbit. The data are transmitted from one satellite to another until they reach the appropriate GRS. GE 110: Remote Sensing Lecture 3 How does a GRS look like? http://www.csrsr.ncu.edu.tw/csrsr_new_site/Website/about/intro.php National Central University – Center for Remote Sensing and Space Research Ground Receiving Station/Facility (in Taiwan) GE 110: Remote Sensing Lecture 3 INSIDE THE CSRSR GRS GE 110: Remote Sensing Lecture 3 Data received by GRS are in raw digital format. In binary format: – DN values are stored in series of 1’s and 0’s The GRS will then decode the binary data to produce an image consisting of DNs The image may then, if required, be processed to correct systematic, geometric and atmospheric distortions to the imagery, and be translated into a standardized format. The data are written to some form of storage medium such as tape, disk or CD. The data are typically archived at most receiving and processing stations, and full libraries of data are managed by government agencies as well as commercial companies responsible for each sensor's archives. GE 110: Remote Sensing Lecture 3 PART 4. SATELLITE REMOTE SENSING SYSTEMS AND THEIR CHARACTERISTICS  GE 110: Remote Sensing Lecture 3 Remote Sensing Satellite Characteristics: Orbits The path followed by a satellite is referred to as its orbit. Orbit selection can vary in terms of altitude (their height above the Earth's surface) and their orientation and rotation relative to the Earth.  GE 110: Remote Sensing Lecture 3 Classification of Remote Sensing Satellites According to Type of Orbit Geostationary/Geosynchronous Satellites: – Satellites at very high altitudes, which view the same portion of the Earth's surface at all times – Orbiting the Earth at altitudes of approximately 36,000 km – revolve at speeds which match the rotation of the Earth so they seem stationary, relative to the Earth's surface. – Orbital period: 24 hours – This allows the satellites to observe and collect information continuously over specific areas. – Weather satellites are common examples – Due to their high altitude, some geostationary weather satellites can monitor weather and cloud patterns covering an entire hemisphere of the Earth. GE 110: Remote Sensing Lecture 3 Classification of Remote Sensing Satellites According to Type of Orbit Polar-orbiting Satellites – follow an orbit (basically north- south) which, in conjunction with the Earth's rotation (west- east), allows them to cover most of the Earth's surface over a certain period of time. – Orbiting at altitudes ranging from 200-1000 km GE 110: Remote Sensing Lecture 3 Classification of Remote Sensing Satellites According to Type of Orbit Sun-synchronous Satellites – Follows an orbit that are combination of orbital period and inclination such that the satellite keeps paces with the sun’s westward progress as the earth rotates – The satellite always crosses the equator at precisely the same local time – Orbiting at altitudes ranging from 200-1000 km – These satellites are also near-polar orbiting satellites GE 110: Remote Sensing Lecture 3 Sun-synchronous, near-polar orbiting RS Satellites Most RS satellites are sun-synchronous, near-polar orbiting satellites The satellite can pass over the area in an ascending or descending mode. At any given latitude, the position of the sun in the sky as the satellite passes overhead will be the same within the same season. This ensures consistent illumination conditions when acquiring images in a specific season over successive years, or over a particular area over a series of days. This is an important factor for monitoring changes between images or for mosaicking adjacent images together, as they do not have to be corrected for different illumination conditions.  GE 110: Remote Sensing Lecture 3 Other Satellite Characteristics (1) As a satellite revolves around the Earth, the sensor "sees" a certain portion of the Earth's surface. The area imaged on the surface, is referred to as the swath. Imaging swaths for spaceborne sensors generally vary between tens and hundreds of kilometres wide. GE 110: Remote Sensing Lecture 3 Other Satellite Characteristics (2) As the satellite orbits the Earth from pole to pole, its east-west position wouldn't change if the Earth didn't rotate. However, as seen from the Earth, it seems that the satellite is shifting westward because the Earth is rotating (from west to east) beneath it. This apparent movement allows the satellite swath to cover a new area with The satellite's orbit and the rotation each consecutive pass. of the Earth work together to allow complete coverage of the Earth's The interval of time required for the surface, after it has completed one satellite to complete its orbit cycle is complete cycle of orbits. not the same as the "revisit period". GE 110: Remote Sensing Lecture 3 EXAMPLES OF SATELLITE REMOTE SENSING SYSTEM AND THEIR CHARACTERISTICS GE 110: Remote Sensing Lecture 3 Landsat 8 Satellite Characteristics Launched February 11, 2013 Sensors on-board the satellite: – Operational Land Imager (OLI) – Thermal Infrared Sensor (TIRS) Sensor technology: push-broom (along-track) scanner Orbit: near-polar, sun- synchronous orbit Orbit altitude: 705 km Swath width: 185 km Revisit/temporal resolution: 16 days Radiometric resolution: 16-bit Spectral resolution: 11 spectral bands Spatial resolution: 15m (panchromatic); 30 m (others) GE 110: Remote Sensing Lecture 3 Landsat 8 Band Designations and Spatial Resolution Wavelength Spatial Resolution Bands (micrometers) (meters) Band 1 - Coastal aerosol 0.43 - 0.45 30 Band 2 - Blue 0.45 - 0.51 30 Band 3 - Green 0.53 - 0.59 30 Band 4 - Red 0.64 - 0.67 30 Band 5 - Near Infrared (NIR) 0.85 - 0.88 30 Band 6 - SWIR 1 1.57 - 1.65 30 Band 7 - SWIR 2 2.11 - 2.29 30 Band 8 - Panchromatic 0.50 - 0.68 15 Band 9 - Cirrus 1.36 - 1.38 30 Band 10 - Thermal Infrared (TIRS) 1 10.60 - 11.19 100 / (30)* Band 11 - Thermal Infrared (TIRS) 2 11.50 - 12.51 100 / (30)* *TIRS bands are acquired at 100-meter resolution but are resampled to 30 meter in delivered data product.  GE 110: Remote Sensing Lecture 3 Landsat 8 Bands and its Applications Band Wavelength Useful for mapping Band 1 – coastal aerosol 0.43 - 0.45 coastal and aerosol studies Bathymetric mapping, distinguishing soil from Band 2 – blue 0.45 - 0.51 vegetation and deciduous from coniferous vegetation Emphasizes peak vegetation, which is useful for Band 3 - green 0.53 - 0.59 assessing plant vigor Band 4 - red 0.64 - 0.67 Discriminates vegetation slopes Band 5 - Near Infrared (NIR) 0.85-0.88 Emphasizes biomass content and shorelines Band 6 - Short-wave Discriminates moisture content of soil and 1.57 - 1.65 Infrared (SWIR) 1 vegetation; penetrates thin clouds Band 7 - Short-wave Improved moisture content of soil and vegetation and Infrared (SWIR) 2 2.11 - 2.29 thin cloud penetration Band 8 - Panchromatic 0.50 - 0.68 15 meter resolution, sharper image definition Band 9 – Cirrus 1.36 - 1.38 Improved detection of cirrus cloud contamination Band 10 – TIRS 1 10.60 – 11.19 100 meter resolution, thermal mapping and estimated soil moisture 100 meter resolution, Improved thermal mapping Band 11 – TIRS 2 11.5 - 12.51 and estimated soil moisture GE 110: Remote Sensing Lecture 3 Differences of Landsat 8 from its predecessors GE 110: Remote Sensing Lecture 3 Landsat 8 Band 1 Image (Coastal aerosol)  GE 110: Remote Sensing Lecture 3 Landsat 8 Band 2 Image (Blue) GE 110: Remote Sensing Lecture 3 Landsat 8 Band 3 Image (Green) GE 110: Remote Sensing Lecture 3 Landsat 8 Band 4 Image (Red)  GE 110: Remote Sensing Lecture 3 Landsat 8 Band 5 Image (NIR) 88  GE 110: Remote Sensing Lecture 3 Landsat 8 Band 6 Image (SWIR1) 89 GE 110: Remote Sensing Lecture 3 Landsat 8 Band 7 Image (SWIR2) 90  GE 110: Remote Sensing Lecture 3 Landsat 8 Band 8 Image (Panchromatic) 91 GE 110: Remote Sensing Lecture 3 Landsat 8 True Color 92  GE 110: Remote Sensing Lecture 3 Landsat 8 False Color (NIR-Red-Green) 93  GE 110: Remote Sensing Lecture 3 Landsat 8 False Color (SWIR2-NIR-Green)  GE 110: Remote Sensing Lecture 3 Landsat 8 False Color (SWIR1-NIR-Blue) 95 GE 110: Remote Sensing Lecture 3 GE 110: Remote Sensing Lecture 3 Sentinel-2 Sentinel-2, launched as part of the European Commission’s Copernicus program on June 23, 2015, was designed specifically to deliver a wealth of data and imagery. The satellite is equipped with an opto-electronic multispectral sensor for surveying with a resolution of 10 to 60 m in the visible, near infrared (VNIR), and short-wave infrared (SWIR) spectral zones, including 13 spectral channels, which ensures the capture of differences in vegetation state, including temporal changes, and minimizes impact on the quality of atmospheric photography. The orbit has an average height of 785 km and the presence of two satellites in the mission allow repeated surveys every 5 days at the equator and every 2-3 days at middle latitudes. Free and open data policy GE 110: Remote Sensing Lecture 3 Sentinel-2A Sentinel-2B Senntinel-2 bands Central wavelength Bandwidth Central wavelength Bandwidth Spatial resolution (nm) (nm) (nm) (nm) (m) Band 1 – Coastal aerosol 442.7 21 442.2 21 60 Band 2 – Blue 492.4 66 492.1 66 10 Band 3 – Green 559.8 36 559.0 36 10 Band 4 – Red 664.6 31 664.9 31 10 Band 5 – Vegetation red 704.1 15 703.8 16 20 edge Band 6 – Vegetation red 740.5 15 739.1 15 20 edge Band 7 – Vegetation red 782.8 20 779.7 20 20 edge Band 8 – NIR 832.8 106 832.9 106 10 Band 8A – Narrow NIR 864.7 21 864.0 22 20 Band 9 – Water vapour 945.1 20 943.2 21 60 Band 10 – SWIR – Cirrus 1373.5 31 1376.9 30 60 Band 11 – SWIR 1613.7 91 1610.4 94 20 Band 12 – SWIR 2202.4 175 2185.7 185 20  GE 110: Remote Sensing Lecture 3 The Sentinel 2 Satellite (Audio/Video) View the Video on You Tube: https://www.youtube.com/watch?v=jljN8_7Tz1E GE 110: Remote Sensing Lecture 3 The Sentinel-2 Satellite (Part 2) (Audio/Video) View the video on You Tube https://www.youtube.com/watch?v=pl7WkG_T3M4 GE 110: Remote Sensing Lecture 3 Free Satellite Imagery Data Sources USGS Earth Explorer Sentinel Open Access Hub Satellite Land Cover NOAA Data Access Viewer Links are available on this website: 15 Free Satellite Imagery Data Sources - GIS Geography GE 110: Remote Sensing Lecture 3 Class Activity The main objective of this exercise is to become familiar with remote sensing satellite system to monitor ecosystem characteristics. At the end of this exercise, you will be able to: Search the most appropriate remote sensing data to be used to monitor ecosystem characteristics  GE 110: Remote Sensing Lecture 3 Class Activity Consider the following scenarios to monitor: Forest health of all tropical forests in the Philippines Aboveground biomass estimation of mangrove forest in Dinagat Island Rice crop monitoring at a local scale (crop field around 10ha) Select the most appropriate remote sensing data for each scenario and fill out the following table: Sensor Name Spatial Resolution Spectral resolution Temporal Resolution Data Quality/Limitation Justify your selection! GE 110: Remote Sensing Lecture 3 Reading Assignment: Chapter 3 (Microwave Remote Sensing), page 92-135. Fundamentals of Remote Sensing, A Canada Centre for Remote Sensing Remote Sensing Tutorial GE 110: Remote Sensing Lecture 3 References/Further Reading Jensen, J.R. (2007). Remote Sensing of the Environment: An Earth Resource Perspective, 2nd Edition. New Jersey: Pearson Education/Prentice Hall. Campbell, J. B., & Wynne, R. H. (2011). Introduction to Remote Sensing 5th Edition. New York: The Guilford Press. Lillesand, T. M., Kiefer, R. W., & Chipman, J. W. (2008). Remote Sensing and Image Interpretation 6th Edition. United States of America: John Wiley & Sons, Inc. Fundamentals of Remote Sensing (Online Tutorial). Available at http://www.nrcan.gc.ca/node/9309 GE 110: Remote Sensing Lecture 3 Thank you for listening!   GE 110: REMOTE SENSING Lecture 4: Visual Interpretation of Remote Sensing Images ENGR. ARTURO G. CAUBA JR. Instructor I College of Engineering and Geosciences Caraga State University GE 110: Remote Sensing Lecture 4 Outline: Part 1. Review of Image Concepts Part 2. Overview of Visual Image Interpretation Part 3. Elements of Visual Image Interpretation Part 4. Image Interpretation Keys GE 110: Remote Sensing Lecture 4 Expected Outcomes The students would be able to: – Identify and differentiate different image concepts – Identify the concepts and different elements of visual image interpretation – Identify features in an image using image interpretation keys GE 110: Remote Sensing Lecture 4 PART 1. IMAGE CONCEPTS GE 110: Remote Sensing Lecture 4 Review: 7 Elements of the Remote Sensing Process A. Energy Source or Illumination B. Radiation and its Interaction with the Atmosphere C. The Interaction of the Radiation with the Target of Interest D. Recording of the Reflected/Emitted Energy by the Sensor E. Transmission, Reception and Processing F. Interpretation and Analysis G. Application © CCRS/CCT GE 110: Remote Sensing Lecture 4 Remote Sensing Image Characteristics (1) Image = a matrix of DN values Each DN is located at a specific row and column in the matrix Pixel: - the smallest unit of an image. - image pixels are normally square and represent a certain area on an image (e.g., the ground segment within the sensor’s IFOV) - Each pixel has DN value associated with it. GE 110: Remote Sensing Lecture 4 Remote Sensing Image Characteristics (2) DNs describe the information content in an image. The DNs represent the strength of signal that was detected and recorded by the sensor Also called “brightness values” – The maximum number of brightness levels available depends on the number of bits used in representing the energy recorded. The higher the range of the DN values in an image, the more sensitive the sensor is to the differences in signal strength This property is called “Radiometric Resolution”  GE 110: Remote Sensing Lecture 4 Images as “Raster” Data An image is an example of Raster data In its simplest form, a raster consists of a matrix of cells (or pixels) organized into rows and columns (or a grid) where each cell contains a value representing information – For RS Images, this information are DNs http://webhelp.esri.com/arcgisdesktop/9.2/index.cfm?TopicName=What_is_ raster_data%3F GE 110: Remote Sensing Lecture 4 Raster versus Vector Data Raster – Information are stored as series of pixels or cells Vector http://webhelp.esri.com/arcgisdesktop/9.2/index.cfm?TopicName=What_is_ raster_data%3F – Information are stored as either points, lines or polygons GE 110: Remote Sensing Lecture 4 Image (Raster) Coordinate System X-axis = column number Y-axis = row number; also called “line number” A pixel’s location can be identified by its (column, row) value The (1,1) axis is on the upper leftmost part of the images Cell height and cell width = depends on the image’s spatial resolution GE 110: Remote Sensing Lecture 4 Multi-band Images (1) Recall: – Electromagnetic energy/radiance entering the sensor is split into multiple spectral bands, with each wavelength range being directed toward a specific detector (one detector per band) For each detector, an image of the same area is produced E.g., for a 3-band sensor, 3 images are produced GE 110: Remote Sensing Lecture 4 Multi-band Images Images sensed simultaneously from essentially the same geometric vantage points but in different bands of Blue Band Green Band the electromagnetic spectrum. Red Band NIR Band  GE 110: Remote Sensing Lecture 4 Organization of Multi-band Image Data (1) How are pixel values for each band of a remote sensing image Blue Band Green Band organized/ structured and stored in a file? Red Band NIR Band GE 110: Remote Sensing Lecture 4 Organization of Multi-band Image Data (2) Three (3) common methods of organizing/ structuring image data for multiband images: – Band interleaved by line (BIL) – Band interleaved by pixel (BIP) – Band sequential (BSQ) GE 110: Remote Sensing Lecture 4 Band interleaved by line (BIL) BIL stores pixel information band by band for each line, or row, of the image. Example: – Given a three-ba