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56 Cards in this Set
- Front
- Back
What is remote sensing? |
displaying info w/o touching it, getting info about something that we cant physically reach; art & science
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In what way is remote sensing a science? In what way is it an art? |
art because people can interpret different things, some level of user driven interpretation and input that will differentiate from other users; interpretations differ not just because of individual preference, but because that preference has been developed for that individual’s entire lifetime;
science bc of understanding physical targets and energy/wavelengths (example interested in objects w/ chlorophyl, you can develop a sensor that will target that— and there is a science behind the engineering of that sensor, understanding atmospheric modelling; held together by rules, scientific method, uses math & logic, physical sciences, biological sciences, social sciences; 4 developmental stages of science (RS is in stage 2- the rise of the field) |
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What are in situ measurements and how are they used in remote sensing? |
in situ = on the ground,
used to compare images captured from air vs what you see on the ground;
ground reference data; use to train classifications (background knowledge to go back and look at the recorded image and say that’s exactly where that road was, or tree, etc) |
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How can in situ measurements be collected? |
using instruments, transducers (a device that converts variations in a physical quantity, such as pressure or brightness, into an electrical signal, or vice versa);
thermometers, terrestrial lazer scanner, ocular estimation of vegetation cover using a daubenmire frame, spectrometers, etc should be callibrated in two ways: -geometrically and radiometrically (to % of reflecatnce) so that RS data can be obtained on diff dates and still be comparable to one anohter -calibrated with what is on the ground in terms of biophysical or cultural (land cover) characteristics |
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What types of bias might be introduced during in situ data collection? |
user bias (bias interpretating the data collected), subjectivity; user error, and instrument error; uncalibration, etc.
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Why is it a misnomer to refer to in situ data as ground truth data instead of ground reference data?
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Because there are many biases and errors that can happen on the ground; it may not be perfect fact, but should rather be used as a reference point for comparison.
recognizing that in situ data may contain error |
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What are some of the limitations and advantages associated with remote sensing? |
Advantages: studying large areas simultaneously; can save money, access to areas we can’t physically get to in person/unobtrusive; see in different spectral wavelengths, not just what the human eye can see; can remove user bias from on-ground sampling; provide fundamental biophysical information; 3 D estimations, multitemporal observations
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Describe in your own words, using examples, the remote sensing process.
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think about imagery
statement of the problem: form hypothesis, select appropriate logic (inductive/deductive/technological), select appropriate model (deterministic/empirical, etc, stochastic)
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Remote sensing industry trends |
aging workforce, which means that younger is needed definitely growing quickly;
a growing need for higher spatial resolution data; a growing need for hyperspectral??,
collecting more and more “real time” data;
greatest shortfall- multilingual and math skills;
aerial has most data collected need finer resolution data than coarse |
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Spatial, spectral, temporal and radiometric resolution
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Resolution: resolving power, ability of an optical system to distinguish between signals that are spatially near or spectrally similar ability of an optical system to distinguish between signals that are spaially near or spectrally similar
Spectral: the number and size of spectral regions the sensor records data in (blue, green, red, infrared, microwave)
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What are the four components of a remote sensing system? |
target, energy source, sensor, transmission path |
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The electromagnetic spectrum (EMS) |
know wavelengths & colors!! just like quiz
400nm=violet 475nm blue 510=green 570=yellow 590=orange 650=red
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Active versus passive remote sensing: |
Passive:radiation that eminates naturally from an object; ex: sun, Earth's surface
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Regions of the electromagnetic spectrum used in remote sensing (UV, Visible, NIR, SWIR): |
UV: .3-.4um VIS:.4-.7um; NIR: .7-1.3um; emittance energy; SWIR: 1.3-3um |
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Conversion of wavelengths from nanometers (nm) to micrometers (µm) and vice versa |
1 nm = .0001 um so, 1 um = 1000 nm 10 nm = .01 um 100 nm = .1 um 1000 nm = 1 um 1500 nm = 1.5 um etc... |
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The relationship between frequency and wavelengths: |
inverse relationship |
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How are photons and wavelengths related to the detection of electromagnetic radiation? |
electromagnetic energy can only be detected as it interacts with matter
a photodetector: photons interact with it and produces an electrical signal that varies in strength, proportional to # photons
measured by two fluctuating fields: electric & magnetic
wave concept- explains how electromagnetic energy moves, but energy can only be detected as it interacts with matter
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What is the relationship b/w an object’s temperature, the amount of NRG exiting the object, and the dominant wavelength at which the NRG is emitted?
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blackbody (theoretical substance that absorbs and radiates energy at the max possible rate per unit at each wavelength for a given temp..the perfect abosrber and emitter...
total emitted radiation is proportionate to its absolute temp (stefan-Boltzmann Law))
greater temp = greater amount of radiant energy emitted from object
as temp increases its dominant wl gets shorter Wien's Displacement Law- determine blackbody's dominant wl |
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How does electromagnetic energy interact with the atmosphere and earth?
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Atmosphere: Scattering (Raleigh, Mie, Nonselective) Earth: Reflectance, absorption, transmission |
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Atmosphere: Scattering (Rayleigh, Mie, Non-Selective)
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Rayleigh - wavelength dependent, mostly in upper 4.5 km of atmosphere Scattering by particles that are smaller than the wavelength of visible and near infrared radiation...more scattering at smaller wavelengths....blue sky and red sunsets
Mie-wavelength dependent, longer wl than Raleigh, lower 4.5 km of atmosphere Particles in the atmosphere are ~equal in size to the wavelength of the scattered radiation... influences longer wavelengths...dust, pollen, smoke...smog is reddish brown
Non-Selective: lower portions of atmosphere all wavelengths equally affected...particles are larger than the wavelengths...most common...water droplets in clouds...gray haze
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Earth: Reflectance, absorption, transmission
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Absorption- atmosphere is preventing the transmission of radiation Ozone (O3 and O2), Water (H2O), and Carbon Dioxide (CO2) are responsible for most of the solar radiation absorption that occurs absorbed and re-radiated at longer wavelengths atmospheric windows
Reflectance- occurs when a ray of light is re-directed as it strikes a nontransparent surface The nature of the reflection depends on sizes of surface irregularities in relation to the wavelength of the radiation considered - Specular Reflection: reflection off a smooth object (ie. smooth body of water, mirrors) Diffuse Reflection : off of rough objects (clothes, roadways, etc)
Transmission: occurs when radiation is neither reflected or absorbed, but passes through a substance without significant weakening.
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How are remote sensing image data organized and formatted?
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Organization: Formats: ways of storing 24-bit images (RGB images)
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What is full width half max? |
a measure of the width of a distribution, defines band center
remember that graph
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What is radiance and how is it measured: |
radiant energy- total energy radiated in all directions towards or away from a surface (Joules);
radiance: the total energy in a certain direction per unit area and solid angle. describes what the sensor measures; the amount of radiation coming from an area
spectral radiance- a function of frequency (Hz);
radiance flux density emitted from a unit area, unit solid angle, unit wavelength (w/m^2*sr*wl)
don't need to know formulas but know in what unit and what those units mean
measured in Joules, Watts expressed in per unit wavelength
steradian--- this is what she wants defines the angle over which reflectance from the earth's surface is measured unit for a solid angle of a sphere
the concept of radiance leaving a specific projected source area on the ground, in a specific direction, and within a specific solid angle. this is the most precise radiometric measurement used in RS
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Supervised and unsupervised classifications (know what they are & examples of each):
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Supervised: you define the spectral class- user defined training pixels, pixels where both the spectral values and the class is known spectral signatures are developed from specified locations in the image (training sites) (defined by user)
Unsupervised: a program defines the spectral class- no extraneous data is used, classes are determined purely on difference in spectral values; basically, like-pixels are clumped together and automatically labeled as the same classification- so two green things would be labeled as vegetation when one might be a green car. or vice versa- too many classifications in heterogeneous pictures-- labeling too many different objects and the user will have to manually go through and combine classifications to make the map more meaningful. isodata, k-means |
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Mixed pixel problem |
a pixel whose digital number represents the average of several spectral classes within the area that it covers n the ground, each emitted or reflected by a different type of material. this is common along edges of features; |
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Hard versus fuzzy classifications:
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hard- each pixel belongs to the class it most clearly resembles, sharper; homogenous areas (croplands, water bodies), dependent upon spatial scale and the variance of classes, low classification accuracy in homogenous areas; isodata, parallelpiped, centroid/k-means, max likelihood, neural networks
fuzzy- softer, each pixel can belong to more than one class and has membership grades for each class; heterogeneous areas relative to spatial scale (residential areas, mixed forests), gradients (forest—>savana, clear —> turbid water); linear mixure modeling,
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Training versus validation data
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Training data- areas of an image that have a known identity; identity can be based on: analyst knowledge, field observations/data, maps and digital imagery
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Pixel unmixing and how it relates to hyperspectral data
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pixel unmixing is commonly performed by employing a least squared (LS) errer crierion, making it sensitive to outliers. as an alternative, the least median of squares (LMedS) method is propost- not only is it extremely robust, but it is efficient hyperspectrial= image spectromoters; hyperspectral data is often used to deterine what materials are present in a scene. materials of interest could include roadways, water bodies, etc. Trivially, each pixel of a hyperspectral image could be compared to a material database to determine the type of material making up the pixel. However, many hyperspectral imaging platforms have low resolution (>5m per pixel) causing each pixel to be a mixture of several materials. The process of unmixing one of these 'mixed' pixels is called hyperspectral image unmixing or simply hyperspectral unmixing.
other supervised classifiers: linear spectral unmixing |
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compare RS derived classification map with reference data (that is believed to accurately reflect the true land cover)
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Analog versus digital
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analog- aerial photographs, any continuous signal for which the time varying feature (variable of the signal is a representation of some other time varying quantity; uses some property of the medium to convey a signal; any information can be conveyed by this; theoretically has infinite resolution more accurate than digital, but suffers more atmospheric interference
digital is more easilier manipulated
analog is waves of energy (lower frequency than your household microwave). The signal alternates between up and down, but the frequencies can vary as to how high up and down the signal goes, and those differing frequencies give the distinct picture you view. When an analog signal is having problems, you will see a fuzzy picture because the microwaves are not as high or low as they should be.
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wave concept
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explains how electromagnetic energy moves, but must interact with matter for it to be detected |
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atmospheric windows
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what doens;t get absorbed, wavelengths that are easily transmitted |
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incident radiation |
absorbed + reflected + transmitted radiation; law of conservation energy
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emittance energy |
mainly derived from shortwave energy from sun that has been absorved, then re-radiated at longer wavelengths; strongest at the far infrared region; reveals info about thermal properties of materials |
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How do some sensors we discussed in class compare in terms of these resolutions? |
Landsat had lower SPECTRAL resolution (wider bandwidths) than the Benchtop field spectrometer, which has the highest spectral resolution. MODIS has greater TEMPORAL resolution than Landsat (MODIS is daily and Landsat is every 14 days). Landsat has higher SPATIAL resolution than MODIS (Landsat has 30 m pixels and MODIS has 250 m pixels). Landsat 8 has greater RADIOMETRIC resolution (11-bit) than Landsat 7 and 5, which record 8-bit intensity information.
Landsat has lower res and wider bandwidths, |
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How would you plot band statistics and apply a band stretch?
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know what it means to generate a histogram: a representation of a frequency distribution by means of rectangles whose widths represent class intervals and whose areas are proportional to the corresponding frequencies; a graphical representation of the pixels exposed in your image
histograms allow us to analyze extremely large datasets by reducing them to a single graph that can show primary, secondary, and tertiary peaks in data as well as give a visual representation of the statistical significance of those peaks
you can connect the shape of a histogram with the mean and median of statistical data that you use to create it-- the relationship between mean and median can help predict shape of histogram
how to plot band stats: tools->Stats->compute stats->select input file->hit ok->choose histogram
stretching: altering the distribution of digital numbers changes the contrast
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How would you apply a filter? |
Select a filter to apply-->click convolutions (this is where most kernels can be found)-->edit kernel matrix and save-->restore kernel-->select input file for convolution-->save file-->hit ok and filtering process begins!
filtering improves readability of the image or extract desired info from image
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error matrices |
consists of n x n array/matrix where n represents the number of categories
the probabiliity % that the classifier has labeled an image pixel into the ground truth grass. it is the probability of a reference pixel being correctly classified |
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user accuracy |
user accuracy: determines the reliability of the map as a predictive device- it will tell the user the chances of, when going into the area on th ground, that hte map will be classified correectly |
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producer's accuracy |
tells teh analyst that for an actual landscape represented on the map, a certain amount of that landscape was correctly classified
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overall accuracy |
the total classification accuracy |
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How would you calculate scale and building height in an analog photo? |
S = Dp / Drw
still need height (tan(angle) x distance) + eye height
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digital number |
the generic term for pixel values
describe pixel values that have not yet been calibrated into meaningful units
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classifications |
based on spectral class- group of n- dimensional vectors of a feature, one pixel at a time, work in spectral domain only, very powerful for sorting thru spectral domain |
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For which of the following wavelengths, give the region of the electromagnetic spectrum (UV, Vis, NIR, SWIR) and convert wl to um 1550nm 532nm 350nm
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1.55um-SWIR .532um-vis .35um-UV |
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EM energy is detected when it interacts with _. _ describes how electromagnetic energy travels and _ are related to how em radiation is detected and recorded by a sensor |
matter, wavelengths, photons |
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as the sun's energy travels through the atmosphere, it is altered by particles and gases in the atmosphere through scattering and absorption: t/f |
true |
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Wein's displacement law indicates that as temps increase the peak radiance shifts toward: |
shorter & cooler wavelengths |
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incoming shortwave radiation is absorbed by the Earth and re-emitted in the |
thermal (dominant at 9.66 um) |
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which reflectance signature has the lower spectral resulution, Landsat 5 or HyMap |
Landsat 5 has lower |
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the following systems operate through active RS except: a) sonar b) radar c) lidar d) multipsectral |
multispectral |
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MODIS has a higher temporal resolution than landsat, but a coarser spatial res. t/f |
true |
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t/f: as the temp of an object increases, it dominant wavelength sifts toward longer wavelengths |
false (shorter) |
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all of the folowing are all supervised classifications, except spectral angle mapper isodata max likelihood decision trees |
isodata |
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according to wien's displacement law, earth's peak wavelength is longer than the sun's peak emittance (t/f) |
true |