Assessing Amazon Rainforest Regrowth with GEDI and ICESat-2 Data

This repository contains code necessary to reproduce the results published in Milenković et al. 2022.

The input data and intermediate results are published and can be downloaded from .

Overview

Calibration of GEDI forest heights

• Calculate airborne LiDAR statistics per GEDI footprint:
  • GEDI_L2A_airborneLiDAR_footprintQuery.py
• Derive the GEDI calibration models and plot figures (Section 4.1):
  • GEDI_L2A_calibrationModels.py

Calibration of ICESat-2 forest heights

• Calculate airborne LiDAR statistics per ICESat-2 ATL08 segment:
  • ATL08_airborneLiDAR_segmentQuery.py
• Derive the ICESat-2 calibration models and plot figures (Section 4.2):
  • ATL08_calibrationModels.py

Forest Regrowth Assessment

• GEDI linear models fitted in 20-year regrowth period (Section 4.3.1):
  • GEDI_L2A_modeling_20years.py
  • GEDI_L2A_directAnalysis.py
• ICESat-2 linear models fitted in 20-year regrowth period (Section 4.3.2):
  • ATL08_directAnalysis.py
• GEDI and ICESat-2 non-linear models fitted in 33-year regrowth period (Section 4.5):
  • GEDI_ATL08_modeling_33years.py

Other Scripts

• Assign the forest age class and border pixel flag to GEDI shots and ATL08 segments:
  • GEDI_L2A_forAge_pointQuery.py
  • ATL08_forAge_pointQuery.py
• Figure with the distributions of calibrated GEDI ALL and ICESat-2 ALL forest heights (Section 4.3):
  • GEDI_ATL08_regrowthFigure_33years.py

Usage

It will be updated soon ...

Citation

If you find the code useful in your work, please consider citing the paper below:

• Milutin Milenković, Johannes Reiche, John Armston, Amy Neuenschwander, Wanda De Keersmaecker, Martin Herold, Jan Verbesselt, Assessing amazon rainforest regrowth with GEDI and ICESat-2 data, Science of Remote Sensing, 2022, 100051, ISSN 2666-0172, https://doi.org/10.1016/j.srs.2022.100051.