53. Assignment 7#
53.1. Classification part 1#
Make a jupyter notebook that reproduces the false color examples inLandsat 8 false color examples for your scene (you’ll need to rerun Clipping multiple bands– v0.3 version 3 to get the clipped fmask, and rerun Landsat 1: Dowloading Landsat and Sentinel data from NASA to download all of the HLS tifs for bands 1,2,3,4,5,6,7,9,10,11,fmask if you don’t have them).
Choose one band combination that looks interesting, and compare it with the land classification you created using Working with surface class data for your image with the same bounding box and pixel size – comment on an y similarities and differences you can find. Is the classification accurate?
53.1.1. Stull Radar problem#
Answer the following questions in a Jupyter notebook, using a function to define the radar equation.
Suppose a Nexrad radar (Stull p.~246) is receiving a signal with returned power Pr = -58 dBm. Using the radar equation find the precipitation rate under the assumption that there is no attenuation and that it is a rainstorm (i.e. liquid water) 100 km away from the radar.
Now keep everything the same, but make the mistake of guessing that it’s a snowstorm, which means that K2=0.208 and we use the snowfall Z-RR relation of \(Z=2000*RR^2\). What is the new incorrect precip rate?
Now assume it’s rain, but make the mistake of guessing that there’s a factor of La=2 attenuation between the target and the rainstorm. What is the new precip rate?
Nexrad coefficients:
#coefficents for nexrad
R1=2.17e-10#range factor, km, Stull 8.25
Pt=750.e3 #transmitted power, W, stull p. 246
b=14255 #equipment factor, Stull 8.26