CUTTING EDGE

• Install TensorFlow on Docker Running on Creodias vGPU Virtual Machine
  • Prerequisites
  • What We Are Going To Cover
  • Step 1: Update software on your VM and verify that the NVIDIA graphics card is working
  • Step 2: Install Docker
  • Step 3: Install and verify the NVIDIA Container Toolkit (ndivia-docker2)
  • Step 4 Install TensorFlow with vGPU support
  • What To Do Next
• Sample Deep Learning Workflow Using TensorFlow Running on Docker on Creodias vGPU Virtual Machine
  • What We Are Going To Do
  • Prerequisites
  • Code Explanation
  • Practical Workflow
  • Performance Comparison
  • What Can Be Done Next
• Install TensorFlow on vGPU enabled VM on Creodias
  • What Are We Going To Do
  • Prerequisites
  • Step 1 Verify the availability of the toolkit
  • Step 2 Install cuDNN
  • Step 3 Install TensorFlow
  • What To Do Next
• Sample Deep Learning workflow using vGPU and EO DATA on Creodias
  • What We Are Going To Do
  • The Prerequisites
  • Code Explanation
  • Practical Workflow
  • Performance Comparison
  • What Can Be Done Next
• Sample SLURM Cluster on Creodias Cloud with ElastiCluster
  • What We Are Going To Cover
  • Prerequisites
  • Always use the latest value of image id
  • Preparation Step 1 Create an OpenStack Keystone User
  • Preparation Step 2 Create a New Key Pair
  • Preparation Step 3 Create Security Group
  • Preparation Step 4 How to set up Python and virtual env
  • Preparation Step 5 Source OpenStack RC File
  • Preparation Step 6 Install ElastiCluster
  • Installation Step 1 Create ~/.elasticluster/config
  • Installation Step 2 How to Enter Correct Values into ElastiCluster Config Template
  • Installation Step 3 Run and verify cluster setup
  • Step 4 Troubleshooting and Debugging
  • What To Do Next
• Sample Workflow: Running EO Processing MPI jobs on a SLURM Cluster on Creodias Cloud
  • What We Are Going To Cover
  • Prerequisites
  • Step 1 Install mpi4py
  • Step 2 Install snappy
  • Step 3 Add EO Data Capabilities to the Cluster
  • Step 4 Install Additional Python Modules
  • Step 5 Run an Image Processing MPI Job
  • What To Do Next
• How to Login to Data Explorer on Creodias Cloud
  • What We Are Going To Cover
  • Prerequisites
  • Step 1 Open the Data Explorer website
  • Step 2 Log in to Data Explorer
  • What To Do Next
• How to Download a Single Product Using Data Explorer on Creodias Cloud
  • What We Are Going To Cover
  • Prerequisites
  • Step 1: Find a product that you are interested in
  • Step 2: Downloading a product
  • What To Do Next
• Processing Products with Data Explorer on Creodias Cloud
  • What We Are Going To Cover
  • Prerequisites
  • Step 1 Finding a product ready for processing
  • Step 2 Adding a product to your workspace
  • Step 3 Queuing up your products for processing
  • What To Do Next
• Processing Sentinel-5P data on air pollution using Jupyter Notebook on Creodias
  • Prerequisites
  • PART #1 - Download and prepare data
  • PART #2 - Conversion and zonal statistics
• Analyzing and monitoring floods using Python and Sentinel-2 satellite imagery on Creodias
  • Prerequisites
  • Step 1 Selecting the appropriate images
  • Step 2 Calculating MNDWI index for chosen images
  • Step 3 Identifying areas with increased water presence
  • Download the resulting images
  • What To Do Next
• Monitoring Urban Sprawl with Sentinel-1 SAR Data Using Pixel Value and Polarization Thresholding on Creodias
  • What Are We Going To Do
  • Prerequisites
  • Step 1 Accessing data from the cloud
  • Step 2 Urban areas extraction by thresholding
  • What To Do Next
• Using Sentinel-2 images to monitor mouth of the river Syr Darya and Aral Lake and analyzing it with NDWI index on Creodias
  • What is NDWI?
  • Advantages of using NDWI indicator
  • What We Are Going To Cover
  • Prerequisites
  • Define variables to hold the data
  • Work with RESTO API
  • Obtaining NDWI
  • Analysis
  • What To Do Next