Bathymetry of supraglacial lakes and streams on the Greenland Ice Sheet from high-resolution aerial photography
This repository contains tools for deriving supraglacial lake bathymetry from NASA's Airborne Topographic Mapper (ATM) aerial imagery using NASA's Ames Stereo Pipeline (ASP), a suite of free and open source, automated geodesy and stereogrammetry tools. The repository is comprised of Jupyter notebooks, Python™ code and data files with the intention of publicly sharing tools and results as the project evolves. It is a living repository intended to invite people to contribute and comment and use the tools that are being developed.
To reference this repository use:
Note
- Surface Topography and Vegetation (STV) Community Meeting at NASA GSFC, October 2024: Poster
- Poster presentation at AGU's Annual Meeting 2024 in Washington, DC.: Poster Linkt to AGU abstract
Jupyter notebooks currently available in this repository (more to come):
- Tutorial: Step 1: Automatic detection of supraglacial lakes and surface classification using classic image segmentation methods such as Otsu multi-thresholding and Connected Component Analysis (CCA) on both natural-color imagery and NDWIice.
- Tutorial: Step 2: Automatic detection of supraglacial lakes using the AI-based Segment Anything Model (SAM) (Kirillov, A. et al., 2023).
- Tutorial: Conversion of CAMBOTv2 L0 natural-color (RGB) images to single-channel grayscale (luminance) images for use with the Ames Stereo Pipeline (ASP). The tutorial covers different ways of converting RGB to luminance.
- Tutorial: Known challenges for SfM for supraglacial hydrology: Notebook illustrating known challenges for SfM for supraglacial hydrology, such as caustic and lake ice cover.
- Tool: Conversion of CAMBOTv2 GPS antenna positions to the camera's focal plane position for use with the Ames Stereo Pipeline (ASP).
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Tool: Parse ASP camera calibration files using the TSAI distortion model and extract focal lengths
$f_{u, v}$ as well as radial ($k_{1, 2}$ ) and tangential ($p_{1, 2}$ ) lens distortion parameters (see: ASP frame camera models). - Tool: Toolbox for converting commonly used Metashape lens calibration formats to NASA's Ames Stereo Pipeline (ASP) Tsai format with tools for analysing a large number of Metashape error statics etc. The toolbox, written by C. Wayne Wright, contains an NBDEV enabled Jupyter notebook, a Python™ library module, and a pip package installer. It runs (and has been tested) in Google Colab, Windows, and Linux/WSL2.
- Tutorial: Sample raster data along a profile: Notebook demonstrating how to create a profile from start and end coordinates and sample raster values along the profile.
- Tutorial: ✨ Calculate the azimuth and elevation of the sun's illumination with refraction correction: Notebook demonstrating how to calculate the azimuth and elevation of the Sun's illumination for a given time and location on Earth. It also applies a refreaction correction using meteorological parameters from MERRA-2 and converts angles to a projected coordinate system.
- Tutorial: ✨ Calculate the azimuth of true north in projected coordinates and plot it on a map: Notebook demonstrating calculation of the azimuth of true north for a given location and map projection. It also provides helper functions for plotting north arrows and scale bars on projected maps in selectable positions on the map.
Python™ code currently available in this repository (more to come):
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Parse ASP camera calibration files using the TSAI distortion model and extract intrinsic parameters, such as focal lengths
$f_{u, v}$ , radial ($k_{1, 2, 3}$ ) and tangential lens distortion parameters ($p_{1, 2}$ ) , as well as extrinsic parameters such as camera pose (see: ASP frame camera models). - Convert ASP residual output files to GeoPackage (GPKG) for plotting with GIS packages
- Convert ATM HDF5 lidar point clouds: convert ATM HDF5 lidar point clouds to ASCII CSV or GeoPackage (GPKG) for plotting with GIS packages.
- Convert KT19 surface temperature measurements: convert KT19 surface temperature measurements to GeoDataFrame and save as GeoPackage (GPKG).
- Calculate the index of refraction of water depending on temperature, wavelength, and salinity using Christopher Parrish's (2020) empirical model
- Calculate NDWIice from L1B georeferenced GeoTiff files and save NDWIice as GeoTiff
Notebooks and repositories related to this project:
Lidar review tools from C. Wayne Wright using ATM supraglacial lake data as example:
Recommended resources:
- Ames Stereo Pipeline user manual
- Ames Stereo Pipeline user group & support forum
- Ames Stereo Pipeline daily build
- Jupyter-ready docker image with ASP pre-installed from the University of Washington Terrain Analysis and Cryosphere Observation Lab
- Ames Stereo Pipeline tutorials from the University of Washington Terrain Analysis and Cryosphere Observation Lab
- Christopher Parrish's (2020) empirical model for calculating the refractive index of water
Publications relevant to the Structure from Motion (SfM) Bathymetry repository:
- Beyer, R. A., Alexandrov, O., and McMichael, S.: The Ames Stereo Pipeline: NASA’s Open Source Software for Deriving and Processing Terrain Data, Earth and Space Science, 5, 537–548, https://doi.org/10.1029/2018EA000409, 2018.
- Harpold, R., Yungel, J., Linkswiler, M., and Studinger, M.: Intra-scan intersection method for the determination of pointing biases of an airborne altimeter, International Journal of Remote Sensing, 37, 648–668, https://doi.org/10.1080/01431161.2015.1137989, 2016.
- Otsu, N.: A Threshold Selection Method from Gray-Level Histograms, IEEE Trans. Syst., Man, Cybern., 9, 62–66, https://doi.org/10.1109/TSMC.1979.4310076, 1979.
- Palaseanu-Lovejoy, M., Alexandrov, O., Danielson, J., and Storlazzi, C.: SaTSeaD: Satellite Triangulated Sea Depth Open-Source Bathymetry Module for NASA Ames Stereo Pipeline, Remote Sensing, 15, 3950, https://doi.org/10.3390/rs15163950, 2023.
- Shean, D. E., Alexandrov, O., Moratto, Z. M., Smith, B. E., Joughin, I. R., Porter, C., and Morin, P.: An automated, open-source pipeline for mass production of digital elevation models (DEMs) from very-high-resolution commercial stereo satellite imagery, ISPRS Journal of Photogrammetry and Remote Sensing, 116, 101–117, https://doi.org/10.1016/j.isprsjprs.2016.03.012, 2016.
- Slocum, R. K., Wright, W., and Parrish, C.: Guidelines for Bathymetric Mapping and Orthoimage Generation using sUAS and SfM, An Approach for Conducting Nearshore Coastal Mapping, https://doi.org/10.25923/07MX-1F93, 2019.
- Studinger, M., Manizade, S. S., Linkswiler, M. A., and Yungel, J. K.: High-resolution imaging of supraglacial hydrological features on the Greenland Ice Sheet with NASA’s Airborne Topographic Mapper (ATM) instrument suite, The Cryosphere, 16, 3649–3668, https://doi.org/10.5194/tc-16-3649-2022, 2022.
- Yang, K. and Smith, L. C.: Internally drained catchments dominate supraglacial hydrology of the southwest Greenland Ice Sheet: Greenland Internally Drained Catchment, J. Geophys. Res. Earth Surf., 121, 1891–1910, https://doi.org/10.1002/2016JF003927, 2016.