Alex Kappel alexkapps

TCP/IP and Subnet Masking: https://www.youtube.com/watch?v=EkNq4TrHP_U

Subnetting Demystified - Part 5 CIDR Notation: https://youtu.be/t5xYI0jzOf4

None of these are pansharpened (YET)

Amazon (LC82250602013174LGN00)

Palestine/Israel (LC81740382014188LGN00)

Natural Disasters:

History of Thrust and Megathrust earthquakes

point data and radius of effect (does magnitude have associated radius?)
Seismic Activity? Livestream from somewhere monitoring online?

History of Floods in Mexico

Raster surface showing former incidents of flood? SRTM data to show lowland elevations more prone to flooding?

History of Hurricanes

##Visualizing North Korea's Worst Drought in Decades

The Democratic Peoples Republic of Korea (North Korea) is experiencing its worst drought in over a decade. According to reports, some areas have experienced 70 days without rain as well as the lowest rainfall levels since 1961. As food shortages are already a problem for North Korea, the damage that this drought will likely cause for harvests is cause for serious alarm. Food shortages in the 1990s led to an estimated million deaths.

We used satellite data to measure what areas are most impacted by the drought. We examined MODIS Normalized Difference Vegetation Index (NDVI) data to evaluate current vegetation levels across the country as a proxy for drought. The map below shows the difference between current vegetation le

	STATE_CODE_001,STRUCTURE_NUMBER_008,COUNTY_CODE_003,FEATURES_DESC_006A,latitude,longitude,OWNER_022,FUNCTIONAL_CLASS_026,YEAR_BUILT_027,ADT_029,YEAR_ADT_030,OPEN_CLOSED_POSTED_041,STRUCTURE_TYPE_043B,OPR_RATING_METH_063,OPERATING_RATING_064,INV_RATING_METH_065,INVENTORY_RATING_066,YEAR_RECONSTRUCTED_106,PERCENT_ADT_TRUCK_109,FUTURE_ADT_114,YEAR_OF_FUTURE_ADT_115,SUFFICIENCY_RATING,lat_decimal_degrees,lon_decimal_degrees
	22,AFLAAWUB06103 ,15,Macks Bayou ,32313200,934032238,72,14,1998,2000,2008,P,1,0,32.4,0,32.4,0.0,5,6500,2030,92.5,32.5255555556,93.6755555556
	55,P48005000000000,95,APPLE RIVER ,45272460,921849800,3,9,1978,440,1998,P,1,1,34.0,1,22.7,0.0,0,440,2031,84.2,45.4566666667,92.3136111111
	26,13699,3,WERNERS CREEK ,46095980,870402900,21,9,1922,5,2013,A,2,8,55.7,8,43.1,1980.0,0,6,2033,48.0,46.1663888889,87.0672222222
	18, 1IN3365,101,Turkey Creek ,38510620,867475990,73,9,2003,600,2008,A,19,1,54.4,1,32.6,0.0,10,650,2029,98.6,38.8516666667,87.2541666667
	24,

	#converts DMS lat/long format columns like '89444400','89444400' to decimal degrees
	#Author: Alex Kappel

	import pandas as pd

	#assigns file location
	input_path = '~/Documents/test.csv'

	#imports csv
	df = pd.read_csv(input_path, sep=',', encoding='utf-8')

	import pandas, folium


	inputfile = '/home/alex/Desktop/test/data/level_1a.tsv'

	df1a = pandas.read_csv(inputfile, sep='\t')

	map_1 = folium.Map(location=[34.5242, 69.17935], zoom_start=7)#, width='100%', height='100%')

	for index, row in df1a.iterrows():

	// Use Gists to store code you would like to remember later on
	console.log(window); // log the "window" object to the console