Earth System Science Data
Earth System Science Data
Earth System Science Data
Articles | Volume 16, issue 9
Articles | Volume 16, issue 9
https://doi.org/10.5194/essd-16-4311-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-16-4311-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 16, issue 9
Data description paper
 | 
23 Sep 2024
Data description paper |  | 23 Sep 2024

A globally sampled high-resolution hand-labeled validation dataset for evaluating surface water extent maps

Rohit Mukherjee, Frederick Policelli, Ruixue Wang, Elise Arellano-Thompson, Beth Tellman, Prashanti Sharma, Zhijie Zhang, and Jonathan Giezendanner

Viewed

Total article views: 3,983 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
3,363 397 223 3,983 66 63
  • HTML: 3,363
  • PDF: 397
  • XML: 223
  • Total: 3,983
  • BibTeX: 66
  • EndNote: 63
Views and downloads (calculated since 30 Aug 2023)
Cumulative views and downloads (calculated since 30 Aug 2023)

Viewed (geographical distribution)

Total article views: 3,983 (including HTML, PDF, and XML) Thereof 3,792 with geography defined and 191 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 20 Nov 2024
Download
Short summary

Global water resource monitoring is crucial due to climate change and population growth. This study presents a hand-labeled dataset of 100 PlanetScope images for surface water detection, spanning diverse biomes. We use this dataset to evaluate two state-of-the-art mapping methods. Results highlight performance variations across biomes, emphasizing the need for diverse, independent validation datasets to enhance the accuracy and reliability of satellite-based surface water monitoring techniques.

Read more
Altmetrics
Final-revised paper
Preprint