Remote Sensing Final Exam Review

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Remote Sensing Quizzes & Trivia

Questions and Answers
  • 1. 

    Most ElectroMagnetic Radiation from the Sun is emitted in what regions of the EmlectroMagnetic Radiation Spectrum?

    Explanation
    The correct answer is UV to SWIR. This means that most electromagnetic radiation from the Sun is emitted in the ultraviolet (UV) to shortwave infrared (SWIR) regions of the electromagnetic radiation spectrum. Additionally, the answer UV to 2.5 micrometers is also correct, as it encompasses the UV region up to a wavelength of 2.5 micrometers. Both answers indicate that the Sun emits radiation in the UV range and extends into the SWIR range, providing a comprehensive explanation of the regions in which the electromagnetic radiation is emitted.

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  • 2. 

    On the ElectroMagnetic Radiation Spectrum, what is the visible light range in micrometers?

    Explanation
    The visible light range in micrometers on the electromagnetic radiation spectrum is 0.4 to 0.7. This range corresponds to the wavelengths of light that are perceivable by the human eye. Light with shorter wavelengths, below 0.4 micrometers, is ultraviolet and cannot be seen, while light with longer wavelengths, above 0.7 micrometers, is infrared and also invisible to the naked eye.

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  • 3. 

    What percentage of the Sun's ElectroMagnetic Radiation is in the visible region of the EMR spectrum?

    Explanation
    The answer is 41% because the visible region of the electromagnetic radiation (EMR) spectrum refers to the range of wavelengths that can be detected by the human eye, which is approximately 400 to 700 nanometers. The Sun emits a wide range of EMR, and only a small portion falls within the visible region. Therefore, 41% of the Sun's EMR is in the visible region.

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  • 4. 

    What is the 1st step of the Remote Sensing Process?

    Explanation
    The first step of the Remote Sensing Process is to identify the problem or objective that needs to be addressed using remote sensing techniques. This involves determining the specific information or data that is required, as well as the purpose or goal of the remote sensing analysis. Identifying the problem helps in defining the scope of the project and guides the subsequent steps of data acquisition, processing, and analysis.

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  • 5. 

    What is the 2nd step in the Remote Sensing Process?

    Explanation
    The second step in the Remote Sensing Process is data collection. This involves gathering information or data from the targeted area using various remote sensing techniques such as satellite imagery, aerial photography, or ground-based sensors. Data collection is crucial as it provides the necessary information for further analysis and interpretation in the remote sensing process.

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  • 6. 

    What is the 3rd step in the Remote Sensing process?

    Explanation
    The 3rd step in the Remote Sensing process is Image Processing. Once the data is collected through remote sensing techniques, it needs to be processed to enhance the image quality, remove any noise or distortions, and extract valuable information from the image. Image processing involves various techniques such as image enhancement, image classification, and image interpretation. This step is crucial in making the data more useful and understandable for further analysis and decision-making.

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  • 7. 

    What is the 4th and final step of the Remote Sensing Process?

    Explanation
    The 4th and final step of the Remote Sensing Process is the generation of Information Products. After data acquisition, preprocessing, and analysis, the remote sensing data is processed further to extract valuable information. This step involves the interpretation, classification, and visualization of the data to generate meaningful products such as maps, images, or reports. These information products provide valuable insights and aid in decision-making processes in various fields such as agriculture, urban planning, environmental monitoring, and disaster management.

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  • 8. 

    What are 2 aspects of Digital Image Processing?

    Explanation
    Digital Image Processing involves various operations and techniques to manipulate digital images. Preprocessing is the initial step in image processing, which includes tasks like image acquisition, noise removal, and image resizing. It aims to enhance the quality of the image and make it suitable for further analysis. Enhancement, on the other hand, focuses on improving the visual appearance of the image by adjusting contrast, brightness, and sharpness. Both preprocessing and enhancement are crucial aspects of Digital Image Processing as they help in improving the overall quality and usability of the images.

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  • 9. 

    What are the 3 aspects of Image Preprocessing (in regards to digital image processing)?

    Explanation
    The three aspects of image preprocessing in digital image processing are noise removal, radiometric calibration, and geometric rectification. Noise removal involves removing unwanted random variations in pixel values that can distort the image. Radiometric calibration is the process of adjusting the image's pixel values to ensure accurate representation of the scene's radiometric properties. Geometric rectification involves correcting any geometric distortions in the image caused by factors such as camera angle or lens distortion, so that the image accurately represents the real-world scene.

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  • 10. 

    What are 4 examples of Spectral Image Enhancement?

    Explanation
    The correct answer includes four examples of spectral image enhancement techniques: contrast stretching, ratioing, indices, and transforms. Contrast stretching is a method to increase the difference between the darkest and brightest parts of an image. Ratioing involves dividing the reflectance values of two different wavelengths to enhance specific features. Indices are mathematical combinations of spectral bands that highlight specific vegetation or mineral properties. Transforms involve converting the image from one domain to another, such as from spatial to frequency domain, to enhance certain features or remove noise.

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  • 11. 

    What are 3 examples of Spatial Image enhancement?

    Explanation
    Spatial image enhancement refers to techniques that enhance the visual quality of an image by manipulating its spatial characteristics. Low pass filters are used to remove high-frequency noise and smooth the image, resulting in a blurred effect. High pass filters enhance the edges and details in an image by suppressing low-frequency components. Directional filters are used to enhance specific directions or orientations in an image, such as vertical or horizontal edges. These filters can be applied individually or combined to improve the overall spatial quality of an image.

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  • 12. 

    What are the 2 forms of change detection?

    Explanation
    The two forms of change detection are numeric and post classification. Numeric change detection involves analyzing the numerical values of different variables to identify changes over time. This can include comparing pixel values or statistical measures like mean or standard deviation. On the other hand, post classification change detection involves classifying different land cover or land use categories and comparing the changes in these categories over time. This method is useful for detecting changes in vegetation, urbanization, or other land cover types.

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  • 13. 

    Why are there absorption features in the blue and red regions of the visible Electro Magnetic Radiation Spectrum?

    Explanation
    Chlorophyll is a pigment found in plants that is responsible for absorbing light energy during photosynthesis. It absorbs light most efficiently in the blue and red regions of the visible electromagnetic spectrum. This is because chlorophyll molecules have specific molecular structures that allow them to absorb photons of light with specific energies corresponding to these regions. The absorption of light by chlorophyll triggers a series of chemical reactions that convert light energy into chemical energy, which is then used by plants for photosynthesis.

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  • 14. 

    Why on a typical vegetation spectral response curve is there high scattering in the Near Infrared region of the Electro Magentic Radiation Spectrum?

    Explanation
    The high scattering in the Near Infrared region of the electromagnetic radiation spectrum on a typical vegetation spectral response curve can be attributed to the mesophyll, leaf structure, and cell structure. Mesophyll refers to the inner tissue of a leaf, which contains a high concentration of chloroplasts that scatter light. The leaf structure, including its shape, size, and arrangement of cells, can also contribute to the scattering of light. Additionally, the cell structure within the leaf, such as the presence of air spaces and cell walls, can cause light to scatter as it passes through the leaf.

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  • 15. 

    What are the three valleys in the typical spectral response curve for vegetation?

    Explanation
    The three valleys in the typical spectral response curve for vegetation are caused by water absorption. These valleys occur at specific wavelengths where water molecules in the vegetation absorb light energy. This absorption affects the reflectance of light by vegetation, resulting in lower reflectance values at these wavelengths. By analyzing the spectral response curve, scientists can identify and study the water content and health of vegetation.

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  • 16. 

    Which of the following two plants has a higher reflectance for it's spectral response curve?

    • A.

      Conifer

    • B.

      Deciduous

    Correct Answer
    A. Conifer
    Explanation
    Conifers are evergreen plants that have needle-like leaves. They are adapted to retain their leaves throughout the year, which allows them to maximize their photosynthetic activity. This adaptation also contributes to their higher reflectance for their spectral response curve. Deciduous plants, on the other hand, shed their leaves during certain seasons, reducing their overall reflectance. Therefore, conifers have a higher reflectance compared to deciduous plants.

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  • 17. 

    What is; a linear regression (r^2) of Red and NIR spectral responses

    Correct Answer
    tassel cap
    Explanation
    A tassel cap is a term used in agriculture to describe the top part of a corn plant where the tassel emerges. It is responsible for producing pollen, which is essential for pollination and the development of corn kernels. The question is asking for the linear regression (r^2) of the Red and NIR spectral responses, but the answer provided, tassel cap, does not seem to be related to the question or the concept of linear regression.

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  • 18. 

    What term describes: when plants flower, plant growth cycle

    Correct Answer
    Phenology
    Explanation
    Phenology refers to the study of cyclic and seasonal natural phenomena, especially in relation to climate and plant and animal life. It involves observing and documenting the timing of events such as flowering, leafing, and fruiting in plants. Therefore, the term "phenology" accurately describes the process of tracking plant growth cycles and the timing of flowering in plants.

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  • 19. 

    What is the name of the following equation: NIR - Red / NIR + Red

    • A.

      Enhanced Vegetation Index

    • B.

      Normalized Difference Vegetation Index

    • C.

      Vegetation Index

    • D.

      Plant Stress Index

    Correct Answer
    B. Normalized Difference Vegetation Index
    Explanation
    The equation given, NIR - Red / NIR + Red, is known as the Normalized Difference Vegetation Index (NDVI). NDVI is a widely used index in remote sensing to measure and monitor vegetation health and density. It quantifies the difference between near-infrared (NIR) and red light reflected by vegetation, providing valuable information about plant growth, biomass, and overall vegetation vigor.

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  • 20. 

    What plant index is intimately related to the MODIS remote sensing satellite?

    Correct Answer
    EVI
    Enhanced Vegetation Index
    Explanation
    The correct answer is EVI, which stands for Enhanced Vegetation Index. This index is closely linked to the MODIS remote sensing satellite. The EVI is a vegetation index that takes into account the atmospheric influences and other factors that can affect the accuracy of vegetation monitoring. It provides a more accurate representation of vegetation health and density compared to other indices. Therefore, the EVI is commonly used in conjunction with the MODIS satellite data to assess vegetation dynamics and monitor changes in plant growth over time.

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  • 21. 

    In EVI what does the Blue constant correct for?

    Correct Answer
    atmospheric scattering
    Explanation
    The Blue constant in EVI corrects for atmospheric scattering. Atmospheric scattering refers to the phenomenon where particles in the Earth's atmosphere scatter sunlight in all directions, causing the sky to appear blue. This scattering can affect the accuracy of remote sensing data, particularly in the blue wavelength range. The Blue constant in EVI helps to account for this scattering effect and improve the accuracy of vegetation indices derived from satellite imagery.

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  • 22. 

    In the EVI what does the constant "L" correct for?

    Correct Answer
    Soil Background
  • 23. 

    What length wavelengths penetrates water deeper and allows you to see the bottom better?

    Correct Answer
    440 to 540 nm
    Explanation
    Wavelengths in the range of 440 to 540 nm penetrate water deeper and allow for better visibility of the bottom. This is because water absorbs longer wavelengths more easily, causing them to be scattered or absorbed before reaching the bottom. Shorter wavelengths, such as those in the given range, are less absorbed by water, allowing them to travel deeper and provide clearer visibility of the underwater environment.

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  • 24. 

    What is the best wavlength region to discriminate land from water boundaries?

    Correct Answer
    NIR to SWIR
    740 - 2500 nm
    Explanation
    The best wavelength region to discriminate land from water boundaries is the NIR to SWIR region, specifically within the range of 740 - 2500 nm. This is because near-infrared (NIR) and shortwave infrared (SWIR) wavelengths are able to penetrate water to a certain extent, allowing for differentiation between land and water. The specific range of 740 - 2500 nm is chosen because it provides optimal contrast between land and water features, making it easier to distinguish boundaries accurately.

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  • 25. 

    What wavlength best distinguishes between clouds and snow?

    Correct Answer
    1.6
    Explanation
    The wavelength of 1.6 is the best for distinguishing between clouds and snow because it falls within the near-infrared range. Near-infrared radiation is able to penetrate through clouds, allowing for differentiation between cloud particles and snow particles. Clouds tend to reflect more near-infrared radiation than snow, which absorbs more of this wavelength. Therefore, by analyzing the amount of near-infrared radiation reflected or absorbed, one can effectively distinguish between clouds and snow.

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  • 26. 

    This is the Correct USGS land cover classifications in the correct order: Urban Agriculture Range Forest Wetland Water Tundra Barren Perennial Snow

    • A.

      True

    • B.

      False

    Correct Answer
    B. False
    Explanation
    Correct Order:
    Urban
    Agriculture
    Range Land
    Forest Land
    Water
    Wetland
    Barren
    Tundra
    Perennial Snow

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  • 27. 

    What are the three water absorption band wavlengths?

    Correct Answer
    1.4, 1.9, 2.7
    Explanation
    The three water absorption band wavelengths are 1.4, 1.9, and 2.7. These wavelengths correspond to specific regions in the electromagnetic spectrum where water molecules absorb electromagnetic radiation. This absorption occurs due to the vibrational and rotational movements of water molecules. The absorption bands at these wavelengths are important in various scientific fields, such as remote sensing and spectroscopy, as they provide valuable information about the presence and properties of water in different environments.

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