CUTTING EDGE

Cutting Edge articles cover advanced workflows that combine CODE-DE-Lab cloud resources with Earth observation processing, Jupyter notebooks, ESA SNAP, Python, GPU-enabled computing, and selected scientific processing examples.

Use this section when you need practical examples for remote sensing analysis, SNAP-based processing, notebook workflows, or advanced scientific workloads.

Sentinel and remote sensing workflows

Sentinel and remote sensing workflows

• Analyzing and monitoring floods using Python and Sentinel-2 satellite imagery on CODE-DE-Lab
• How to Download a Single Product Using Data Explorer on CODE-DE-Lab Cloud
• Processing Products with Data Explorer on CODE-DE-Lab FRA1-3 Cloud
• Processing Sentinel-5P data on air pollution using Jupyter Notebook on CODE-DE-Lab
• Using Sentinel-2 images to monitor mouth of the river Syr Darya and Aral Lake and analyzing it with NDWI index on CODE-DE-Lab
• Monitoring Urban Sprawl with Sentinel-1 SAR Data Using Pixel Value and Polarization Thresholding on CODE-DE-Lab

ESA SNAP

ESA SNAP

• Coupling ESA SNAP to Python on an CODE-DE-Lab VM
• Installation of ESA SNAP on an CODE-DE-Lab VM
• Using the ESA SNAP Processor on an CODE-DE-Lab VM

GPU, TensorFlow, and deep learning

GPU, TensorFlow, and deep learning

• Install TensorFlow on Docker Running on CODE-DE-Lab vGPU Virtual Machine
• Install TensorFlow on FRA1-3 vGPU enabled VM on CODE-DE-Lab
• Sample Deep Learning Workflow Using TensorFlow Running on Docker on CODE-DE-Lab vGPU Virtual Machine
• Sample Deep Learning workflow using FRA1-3 vGPU and EO DATA on CODE-DE-Lab

Clusters, SLURM, and MPI

Clusters, SLURM, and MPI

• Create a SLURM Cluster with Terraform
• Sample Workflow: Running EO Processing MPI Jobs on a SLURM Cluster on CODE-DE-Lab Cloud

Data Explorer

Data Explorer

• How to Login to Data Explorer on CODE-DE-Lab Cloud

Jump to

• CUTTING EDGE
  • Sentinel and remote sensing workflows
  • ESA SNAP
  • GPU, TensorFlow, and deep learning
  • Clusters, SLURM, and MPI
  • Data Explorer

↑