Articles | Volume 15, issue 2
© Author(s) 2023. This work is distributed underthe Creative Commons Attribution 4.0 License.
TreeSatAI Benchmark Archive: a multi-sensor, multi-label dataset for tree species classification in remote sensing
- Final revised paper (published on 08 Feb 2023)
- Preprint (discussion started on 26 Sep 2022)
Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor |
: Report abuse
RC1: 'Comment on essd-2022-312', Anonymous Referee #1, 03 Oct 2022
- AC1: 'Reply on RC1', Christian Schulz, 23 Nov 2022
- RC2: 'Comment on essd-2022-312', Anonymous Referee #2, 27 Nov 2022
Peer review completion
AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Christian Schulz on behalf of the Authors (23 Dec 2022) Author's response Author's tracked changes Manuscript
ED: Publish as is (03 Jan 2023) by Jia Yang
AR by Christian Schulz on behalf of the Authors (05 Jan 2023) Manuscript
Ahlswede et al introduce the TreeSatAI Benchmark Archive, a new data for tree species classification in Central Europe based on multi-sensor data from aerial, Sentinel-1 and Sentinel-2 imagery. This dataset contains labels of 20 European tree species (i.e., 15 tree genera). They also tested deep learning and machine learning models (residual neural networks (ResNet), multi-layer perceptron (MLP) or Light Gradient Boosting Machine (LightGBM) models) performances on this new dataset. This dataset is helpful to pre-train DL models for classifying species.
Overall, the manuscript conducted good work on data collection, statistic analysis, and results presentation. I think it is publishable if several minor issues can be addressed.