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NEON Data Science Institute 2018

2018-07-12 PREZI

Moving Geospatial Data Analysis onto hybrid Cloud & HPC

The purpose of this tutorial is to set up a linux-based Virtual Machine running on CyVerse Atmosphere or XSEDE Jetstream to do interactive geospatial analyses in Jupyter Notebooks and RStudio-Server.

The VM(s) can also be run in any other number of ways that the user sees fit.

Prerequisites

Downloads, access, and services

In order to complete this tutorial you will need access to the following services/software

Prerequisite Preparation/Notes Link/Download
CyVerse account You will need a CyVerse account to complete this exercise Register
Atmosphere access You must have access to Atmosphere Request Access
CyVerse Data Store allocation increase (Optional) You must be registered for CyVerse Request Increase (form #2)
Jetstream access (Optional) You must have registered with XSEDE Request Access
Cyberduck (Optional) Standalone program for uploading/downloading data to Data Store Download
Windows 10 Linux Subsystem (Optional) Install Ubuntu Bash on a Windows OS Installation Instructions

Platform(s)

We will use the following CyVerse platform(s):

Platform Interface Link Platform Documentation Quick Start
Data Store GUI/Command line Data Store Data Store Manual Guide
Discovery Environment Jupyter Notebooks / non-interactive Docker jobs Discovery Environment DE Manual Guide
Atmosphere Command line (ssh) and/or Desktop (VNC) Atmosphere Atmosphere Manual Guide

Application(s) used

Discovery Environment App(s):

Name Version Location App Link Notes/other
Jupyter Notebooks 0.1 TBA TBA TBA

Atmosphere Image(s):

Here are the tested Ubuntu images.

Warning: The latest version of Ubuntu (18.04) may not have current packages for some software.

Image Name Version Description Link
Ubuntu 18.04 GUI 1.0 Ubuntu 18.04 GUI XFCE Base Image
Ubuntu 18.04 non-GUI 1.0 Ubuntu 18.04 non-GUI Base Image
Ubuntu 16.04 GUI 2.1 Ubuntu 16.04 GUI XFCE Base Image
Ubuntu 16.04 non-GUI 1.6 Ubuntu 16.04 non-GUI Base Image

Jetstream Image(s):

Input and example data

In order to complete this tutorial you will need to have the following inputs prepared

Input File(s) Format Preparation/Notes Example Data
Discrete lidar *.laz, *.las, *.xyz, *.bin classified Data Portal
Orthophotography *.tif    
Hyperspectral *.hdf    

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