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CONS 127 Exam Questions With Correct Answers Already Passed!!!

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CONS 127 Exam Questions With
Correct Answers Already Passed!!!
What is the difference between data, information, and knowledge? CORRECT
ANSWERS Data are the facts and descriptors of the world we are living in (this tree is
20m tall).
Information is recorded data or captured facts (an image).
Knowledge is organized information (a map)

What is the definition of big data? CORRECT ANSWERS Big data can be broken into 4
dimensions which are volume, variety, velocity, veracity. Data becomes big data when
the collection/recording of data outpaces analysis and distribution.

What is the difference between data and knowledge? CORRECT ANSWERS Data is
the facts of the world and knowledge is the organization of all the collected data.

What are the four big V's of data? Explain how each can be related to remote sensing
big data. CORRECT ANSWERS Volume, variety, velocity, and veracity.

Volume - is related to sensing big data as the Landsat program provides continuous
space based moderate resolution remote sensing.

Variety - is related to sensing big data as there are both active and passive remote
sensing. The different ways that we have to collect data allows for the observation and
study of more of earths natural processes and features.

Velocity - is related to sensing big data because currently the rate at which we can
collect and receive information is daily as in we are able to see an image of most
locations taken on that day.

Veracity - is related to sensing big data because remote sensing can be used to confirm
accuracy in existing existing maps assess in any changes in fact occurred.

Give two examples of big data networks. CORRECT ANSWERS Meteorological
networks and phenological networks.

Describe one geospatial network in detail: What remote sensing data sets does it use?
What qualifies that network as a big data network? CORRECT ANSWERS Phenological
Network:
(1) Near surface remote sensing and satellite remote sensing (specifically MODIS) is
used to collect images and to monitor vegetation by looking at the NDVI and the
Spectral Signature. Data from near surface remote sensing is consistent, inexpensive
and very accurate with a much higher spatial and temporal resolution compared to
remote sensing images that are collected by satellites. However the scale of near

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