Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

PhotonLabeler: An Inter-disciplinary Platform for Visual Interpretation and Labeling of ICESat-2 Geolocated Photon Data

Version 1 : Received: 11 August 2020 / Approved: 13 August 2020 / Online: 13 August 2020 (08:08:40 CEST)

A peer-reviewed article of this Preprint also exists.

Malambo, L.; Popescu, S. PhotonLabeler: An Inter-Disciplinary Platform for Visual Interpretation and Labeling of ICESat-2 Geolocated Photon Data. Remote Sens. 2020, 12, 3168. Malambo, L.; Popescu, S. PhotonLabeler: An Inter-Disciplinary Platform for Visual Interpretation and Labeling of ICESat-2 Geolocated Photon Data. Remote Sens. 2020, 12, 3168.

Journal reference: Remote Sens. 2020, 12, 3168
DOI: 10.3390/rs12193168

Abstract

NASA’s ICESat-2space-borne photon-counting lidar mission is providing global elevation measurements that will provide significant benefits to a variety of bio-geoscience research applications. Given the novelty of elevation and the derived data products from the ICESat-2 mission, the research community needs software tools that can facilitate photon-level analyses to support product validation and development new analysis methods. Here, we describe PhotonLabeler, a free graphic user interface (GUI) for manual labeling and visualization of ICESat-2 Geolocated Photon data (ATL03). Developed in MATLAB, the GUI facilitates the reading and display of ATL03 Hierarchical Data Format (HDF) files, the manual labeling of individual photons into target classes of choice using a number of point selections tools and enables eventual saving of labeled data in ASCII format. Other capabilities include saving and loading of labeling sessions to manage labeling tasks over time. We expect labeled data generated using the application to serve two main purposes. First, serve as ground truth for validating various products from ICESat-2 mission, especially for study sites around the world that do not have existing reference datasets such as airborne lidar. Second, serve as training and validation data in the development of new algorithms for generating various ICESat-2 data products. We demonstrate the first use case through a validation case study for the land and vegetation product (ATL08), which provides canopy and terrain height estimates, over two sites. For the first site, located in northwestern Zambia, we used ICESat-2 ATL03 data acquired at night and for our second site in Texas, US, we used ATL03 data acquired during the day. The PhotonLabeler application is freely available as a compiled MATLAB binary to enable free access and utilization by interested researchers.

Subject Areas

ICESat-2; photon-counting lidar; photon labeling; visualization; ATL03; ATL08; visual interpretation; solar-induced noise

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