Essential Remote Sensing Terms

Question 1

Atmospheric Windows in EMR

Answer 1

The spaces where EMR is not reflected by clouds or surfaces that allow spectral signatures.

Question 2

Wien’s Displacement Law

Answer 2

Relationship between

1) wavelength of radiation emitted
2) temperature of a blackbody/object

Question 3

Stefan-Bolzmann’s Law

Answer 3

Relationship between

1) total emitted radiation
2) temperature
3) w=sd^4

Question 4

Landsat 7 TM Bands/Radiation

Answer 4

Band 1- Blue/Green, .45-.52um. 
Band 2- Green, .52-.60um
Band 3- Red, .63-.69um
Band 4- Near Infrared, .76-.90um
Band 5- Mid-Infrared, 1.55-1.75um
Band 6- Far-Infrared, 10.4-12.5um
Band 7- Mid-Infrared, 2.08-2.35um

Question 5

Supervised classes

Answer 5

1. Need training data
2. uses the spectral signature defined in the training set.
3. it determines each class on what it resembles most in the training set.
4. common supervised classification algorithms are maximum likelihood and minimum-distance classification.

Question 6

Unsupervised classes

Answer 6

1. the outcomes (groupings of pixels with common characteristics) are based on software analysis of image
2. done without the user providing sample classes.
3. computer uses techniques to determine which pixels are related and groups them into classes.

Question 7

Maximum Likelihood

Answer 7

1. assigns each cell in the input raster to the class that it has the highest probability of belonging to.
2. finds the value of one or more parameters for a given statistic which makes the known likelihood distribution a maximum.
3. Supervised technique

Question 8

Minimum distance classification

Answer 8

1. used to classify unknown image data to classes which minimize the distance between the image data and the class in multi-feature space.
2. distance is defined as an index of similarity so that the minimum distance is the same as the maximum similarity.
3. Supervised technique

Question 9

Isodata

Answer 9

1. Unsupervised technique
2. Splits/merges clusters if…
3. either the number of members (pixel) in a cluster is less than a certain threshold or…
4. if the centers of two clusters are closer than a certain threshold.
5. Clusters are split into two different clusters if the cluster standard deviation exceeds a predefined value and the number of pixels

Question 10

K-mean

Answer 10

1. Unsupervised technique
2. minimize the within cluster variability.
3. objective function is the sums of squares distances (errors) between each pixel and its assigned cluster center.

Question 11

Radiance

Answer 11

1. Radiance is the variable directly measured by remote sensing instruments.
2. how much light the instrument “sees” from the object being observed.

Question 12

Parallelpiped Classifier

Answer 12

1. Supervised classification.
2. the threshold of each spectral (class) signature defined in the training data
3. determines whether a given pixel within the class or not.

Question 13

EMR Spectrum (From Shortest to Longest Wavelength)

Answer 13

1. Gamma rays
2. X-rays
3. UV
4. Visible light (B, G, R)
5. Infrared light
6. Microwaves
7. Radiowaves