Landsat Collection 2: Key Information and recommendations for data users and product developers
Submitted: 2025-03-07
|Accepted: 2025-04-23
|Published: 2025-05-22
Copyright (c) 2025 Xavier Pons, Cristina Cea, Óscar González-Guerrero, Jordi Cristóbal
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
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Keywords:
Landsat, Collection-2, radiance, TOA reflectance, BOA reflectance
Supporting agencies:
Xavier Pons is the recipient of an ICREA Academia Excellence in Research Grant (2023–2027)
SGR grant from Consolidated and Quality Research Groups of the Generalitat de Catalunya (SGR 2021 no. 00554)
Spanish MCIU Ministry DynaFun project (PID2023-152719OB-C21 MCIU/AEI/ ERDF,EU)
Abstract:
The United States Geological Survey (USGS) effort to provide coherent data for the Landsat series from various perspectives (e.g., geometric, radiometric, or metadata) is, without a doubt, admirable, especially considering the vast volume of data and the continuous scientific and technical challenges over many decades. Landsat Collection 2, initiated in 2020, represents the latest effort in this direction. This paper presents a detailed explanation of some important changes compared to previous distributions. The text highlights aspects of good practices (e.g., the choice of distribution format or the explicit coding of saturated pixels), radiometric inconsistencies (e.g., in areas of scene overlap or images taken on close dates), and decisions that pose difficulties for the user community (e.g., termination of the distribution of lower processing level products, exclusion of level 2 products for the first three Landsat satellites, inclusion of metadata that can lead to confusion, inconsistency of NoData values). It also addresses the significant differences in radiances between data processed by ESA (CEOS) and provides justification for the decision to change the meaning of the traditional DN, resulting in shifts in radiance rescaling factors (scale and offset) throughout the year. Furthermore, the paper offers alternatives for some problematic aspects of thermal infrared data processing. The aim is to assist other users and contribute to the debate on best practices in remote sensing image processing.
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