Python Tutorials
Python Tutorials
toolsrtm and scopeinpython share one continuous 20-chapter
learning path rather than two separate ones — almost every chapter here is ToolsRTM
material (only Chapter 06 is SCOPE-specific, covered on the SCOPEinR hub).
Below: the ToolsRTM-relevant chapters, grouped the same way as the full path, plus the
package-tagged runnable code examples.
Getting Started
A first simulation in minutes.
Parameters & Traits
What every trait means, physically.
Leaf Radiative Transfer Models
PROSPECT-D/PRO agree; LIBERTY (needle) diverges.
Canopy Radiative Transfer Models
fourSAIL vs. fourSAIL2 vs. INFORM, same leaf and LAI.
Soil & Atmosphere
BSM, MARMIT, and the SPART chain to top-of-atmosphere.
Building RTM Workflows
How the models chain together into real pipelines.
Sensor Simulation
Real, measured Sentinel-2A response curves, not idealized shapes.
Spectral Indices
NDVI's real saturation above LAI~4, vs. MSAVI's gentler response.
Sensitivity Analysis
Which trait dominates at each wavelength.
LUT Generation
Realistic trait sampling, including real trait co-variation.
LUT Inversion
Observed spectrum against its best-matching neighbours.
Machine-Learning Inversion
Random Forest and friends, trained on the LUT.
Deep-Learning Inversion
A dense network that genuinely learns: real loss curve, R²=0.95.
Choosing an Inversion Strategy
LUT matching vs. ML vs. deep learning: when to use which.
Retrieving Real EO Data
Pulling a real Sentinel-2 scene via STAC.
Preparing EO Observations
A real case where naive cloud masking fails, and a working fix.
Applying an Inversion Model Spatially
From a trained model to a pixel-by-pixel trait map.
Trait Maps & Uncertainty
Not just a map — how confident is it?
End-to-End Workflow (flagship)
Raw RTM parameters to a real, cross-checked trait map.
Leaf → Canopy
PROSPECT + fourSAIL, chained.
Alternative Leaf Models
LIBERTY and Fluspect-B.
INFORM
Explicit forest canopy model.
SPART
Full soil-plant-atmosphere chain.
MARMIT
Soil moisture model.
Sensor Convolution & Indices
Native spectrum to real bands to NDVI.
Global Sensitivity Analysis
Sobol indices, in code.
Machine-Learning Trait Inversion
Training and applying an inversion model.
Deep-Learning Trait Inversion
Dense network, minimal example.
1D-CNN on Hyperspectral Bands
PRISMA-resolution spectra, direct.
Real Sentinel-2 Capstone
Data-driven spatial index & Cab mapping.