Answer:
a) correct answer is C
, b) 14º from the west to the north, c) v_{1g} = 300.79 km / h
Explanation:
This is a relative speed exercise using the addition of speeds.
1) when it is not specified regarding what is being measured, the medicine is carried out with respect to the Z Earth, therefore the correct answer is C
2 and 3) In this case we must compose the speed using the Pythagorean Theorem.
² = 
² + 
²
where v_{1a} is the speed of the airplane with respect to the air, v_{1g} airplane speed with respect to the Earth, v_{ag} air speed with respect to the Earth
in this case let's clear the speed of the airplane with respect to the Earth
v_{1g} = √(v_{1a}² - v_{ag}²)
v_{1g} = √ (310² - 75²)
v_{1g} = 300.79 km / h
we find the direction of the airplane using trigonometry
sin θ = v_{ag} / v_{1a}
θ = sin⁻¹ (v_{ag} /v_{1a})
θ = sin⁻¹ (75/310)
θ= 14º
the pilot must direct the aircraft at an angle of 14º from the west to the north
An experiment that involves using a Landsat satellite is given below;
Paddy lands detection through the use of Landsat-8 satellite images and object-based classification in cape town, South Africa.
<h3>What is the experiment about?</h3>
Rice is known to be one of the most vital food staples in a lot of countries, especially South Africa . Due to the irrigated rice production that tend to differs from other kinds of agricultural fields, this study was said to have created a paddy field mapping model via the use of phenological aspects, a lot of satellite sensor data, and also the use of object-based approach.
This study uses the phonological features of rice plants and also the use of an annual data regarding surface temperature (LST) to make the paddy map.
The core remote sensing data is made up of the yearly LST that is obtained from MODIS and multi-temporal Landsat-8 satellite imagery.
Based on the study, the total accuracy and kappa coefficient for the pixel-based classification method is seen to be 92% and 0.89.
Hence, An experiment that involves using a Landsat satellite is Paddy lands detection through the use of Landsat-8 satellite images and object-based classification in cape town, South Africa.
Learn more about Landsat satellite from
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