CUTTING EDGE
- Install TensorFlow on Docker Running on Creodias vGPU Virtual Machine
- Sample Deep Learning Workflow Using TensorFlow Running on Docker on Creodias vGPU Virtual Machine
- Install TensorFlow on vGPU enabled VM on Creodias
- Sample Deep Learning workflow using vGPU and EO DATA on Creodias
- 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
- How to Login to Data Explorer on Creodias Cloud
- How to Download a Single Product Using Data Explorer on Creodias Cloud
- Processing Products with Data Explorer on Creodias Cloud
- Processing Sentinel-5P data on air pollution using Jupyter Notebook on Creodias
- Analyzing and monitoring floods using Python and Sentinel-2 satellite imagery on Creodias
- Monitoring Urban Sprawl with Sentinel-1 SAR Data Using Pixel Value and Polarization Thresholding on Creodias
- Using Sentinel-2 images to monitor mouth of the river Syr Darya and Aral Lake and analyzing it with NDWI index on Creodias
- MODIS active fire detection in Portugal using Jupyter Notebook on Creodias
- Introduction
- Overview
- What you will do
- Prerequisites
- Required files
- Step 1. Install dependencies
- Step 2. Import libraries and define global settings
- Step 3. Load the Portugal area of interest
- Step 4. Search the STAC catalogue
- Step 5. Read and process the HDF4 files
- Step 6. Build aggregate time series
- Step 7. Plot Terra and Aqua fire detections
- Step 8. Plot annual fire activity by confidence
- Step 9. Plot the year-month fire heatmap
- Step 10. Plot fire seasonality by year
- Interpreting the results
- Limitations
- Conclusion
- What to do next
- MODIS land cover deforestation analysis in Brazil using Jupyter Notebook on Creodias
- Introduction
- Overview
- What you will do
- Prerequisites
- Required files
- Step 1. Install dependencies
- Step 2. Import libraries and configure S3 access
- Step 3. Define the area of interest and MODIS classes
- Step 4. Search the OData catalogue
- Step 5. Download and process scenes
- Step 6. Create an animated land cover map
- Step 7. Build aggregate time series
- Step 8. Plot land cover composition over time
- Step 9. Plot net area change
- Step 10. Plot annual forest loss rate
- Step 11. Print summary statistics
- Interpreting the results
- Limitations
- Conclusion
- What to do next
- MODIS reflectance desertification analysis in Spain using Jupyter Notebook on Creodias
- Introduction
- Overview
- What you will do
- Prerequisites
- Required files
- Step 1. Install dependencies
- Step 2. Import libraries and configure S3 access
- Step 3. Load the Andalusia area of interest
- Step 4. Search the STAC catalogue
- Step 5. Download HDF4 files from S3
- Step 6. Read HDF4 files and compute spectral indices
- Step 7. Create a three-panel animated GIF
- Step 8. Plot spectral index anomalies
- Step 9. Plot monthly mean profiles
- Interpreting the results
- Limitations
- Conclusion
- What to do next
- MODIS snow cover in Italy analysis using Jupyter Notebook on Creodias
- Introduction
- Overview
- What you will do
- Prerequisites
- Step 1. Install dependencies
- Step 2. Import libraries and define global settings
- Step 3. Load the Italian Alps area of interest
- Step 4. Search the OData catalogue
- Step 5. Read and process the HDF4 files
- Step 6. Build aggregate time series
- Step 7. Plot annual snow and cloud pixels
- Step 8. Plot annual snow anomaly
- Step 9. Plot the year-month heatmap
- Step 10. Compare monthly snow profiles by decade
- Interpreting the results
- Limitations
- Conclusion
- What to do next