Sample_Exam

Sample Remote Sensing Exam

1. A digital image is represented by a _____-dimensional array or matrix of numbers

2. A picture element (pixel) in a digital image has spatial, _____, radiometric and _____ resolution attributes

3. An image coordinate system to refers to the _______ of an individual pixel within the array image pixels

4. The digital intensity of each pixel in an image commonly defined by a _________ (DN) on a scale, which commences at 0 or ______ in a black-and-white image, and concludes at a value set by the radiometric ___________ of the image

5. List the main components of a digital image processing system:

a)

b)

c)

d)

6. The resolution of a pixel in a digital image depends on the ___________________(IFOV), altitude of remote sensing platform (satellite) and also on sampling rate along scan line

7. Maximum (DN), minimum, mean, median, mode, standard deviation, variance, and skewness are important summary measures of population (the scene) or sample (sub-scene), which can be represented in the __________ of the digital image

8. The image __________ shows the absolute count of pixels by DN or DN class, and numerical value of count or can be normalized to ______% using total number of pixels.

9 .The major steps of Image processing consists of which of the following components

a. Input of initial data

b. Pre-processing of initial data

c. Image restoration

d. Image enhancement

e. Feature Extraction

f. Decision and classification

g. Output and display

h. None/all of the above,

10. Pre-processing of initial remote sensing data can include which of the following steps

a. radiometric and geometric corrections

b. contrast enhancement

c. supervised classification

d. density slicing

e. unsupervised classification

f. edge enhancement

g. filtering and ratios

11. Systematic distortion in remote sensing data include which of the following

a. Scanner distortion

b. variations in the velocity of the satellite

c. Variations in mirror velocity

d. Scan skew

12. Contrast enhancement of remote sensing data can be accomplished by

a. Histogram equalization

b. Assigning contrasting colors to spectral bands

c. Gaussian histogram stretch

d. Linear histogram stretch

13. High Pass digital filters can be used to

a. smooth the digital image

b. suppress random noise in the image

c. emphasize local variations in the spectral signature

d. enhance edge detection

14. Directional digital filters can be used to

a. Emphsize regional variations in spectral signature

b. detect lineations with preferred orientations

c. emphasize edges having specific orientations

15. Density slicing is the process of dividing (slicing) image of continuous gray tones, or image in color, into separate, easily distinguishable __classes___________.

16. Image algebra is when one or more elements of image arithmetic are applied pixel by pixel, in which two or more data sets are combined. Which of the following are legitimate methods of image algebra

a. addition (e.g. MSS Band 4 + Band 7)

b. subtraction (e.g. Band 7 - Band 4)

c. single band density slicing (not)

d. multiplication (

e.g. Band 4 x Band 7)

e. division (e.g. Band 7 / Band 4

f. all/none of the above

17. Classification can take place in

a. Orbital space

b. Digital space

c. Inner space

d. Image Space

e. Feature (or measurement) Space

18 Steps in recognizing patterns in images in supervised classification are:

a. analyst 'trains' the known classifier to be used by the computer

b. computer assigns pixel of unknown identity to a specific class based on its DNs in two or

more bands and the structure of the specific classifier

c. Analyst assesses, and preferably measures, the results of classification

d. Analyst decides whether further processing is required, and makes necessary adjustments

to the classifier

e. Analyst interprets the identity of each class

f. all/none of the above

19. The training sites for supervised image classification

a. Identify the feature classes of interest

b. are representative sample(s) of each feature class

c. as homogeneous as possible

d. contain fewer than 5 pixels

e. should contain approximately 10 time the number of pixels as number of spectral bands

f. should always be a regular polygon

20. Unsupervised Image Classification includes

a. minimal initial input from analyst

b. a clustering algorithm to group pixels with like spectral characteristics

c. Identification of feature classes by analyst follows clustering of pixels by computer

d. Users training sites to cluster the pixels s in the image

21. Remote sensing satellites may have

a. equatorial orbits

b. true Polar orbits

c. near Polar orbits, further classified as

d. prograde orbits

e. retrograde orbits

22. The major uses of satellites in near polar, retrograde, sun-synchronous orbits are for

a. Earth resources sensing

b. Meteorological monitoring

c. Synoptic views of the Earth’s hemisphere

d. Monitoring data over the Earth’s poles

23. Match the spectral Landsat Thematic Mapper bands with the descriptive name

1 0.45-0.5

2 ?m, Reflective IR

2 0.52-0.60 ?m, Green

3 0.63-0.69 ?m, Red

4 0.76-0.90 ?m, Thermal IR

5 1.55-1.75 ?m, Reflective IR

6 10.4-12.5 ?m, Reflective IR

7 2.08-2.35 ?m, Blue part of spectrum

24. When observing sea surface temperature (SST) or other ocean-related phenomenon from satellite-based platforms that “look” though the Earth’s atmosphere what types of energy-matter interactions in the atmosphere must be considered? Your answer should describe any limitations placed on remote sensing with respect to the regions of the electromagnetic spectrum

25. Briefly discuss the concept of resolution with respect the remote sensing. Your answer should differentiate among the types of resolution and how each can influence the quality of remote sensing data.

26 resolution included in RS