Automatic training sample collection utilizing multi-source land cover products and time-series Sentinel-2 images
Collecting reliable training samples plays a crucial role in improving the accuracy of land cover (LC) mapping products, which are essential foundational data for global environmental and climate change research. However, the process is labor-intensive and time-consuming, as it heavily relies on hum...
Saved in:
| Main Authors: | Yanzhao Wang, Yonghua Sun, Xuyue Cao, Yihan Wang, Wangkuan Zhang, Xinglu Cheng, Ruozeng Wang, Jinkun Zong |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2024-12-01
|
| Series: | GIScience & Remote Sensing |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/15481603.2024.2352957 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Training data in satellite image classification for land cover mapping: a review
by: Daniel Moraes, et al.
Published: (2024-12-01) -
Morpho-biological study of the grain sorghum collection of the fsbsi «ARC «Donskoy»
by: A. A. Kalyuzhny, et al.
Published: (2024-11-01) -
Forming and maintaining a collection of plant genetic resources of the Buckwheat (Fagopyrum Mill.) genus
by: О. В. Тригуб
Published: (2016-02-01) -
Field expedient stool collection methods for gut microbiome analysis in deployed military environments
by: Car Reen Kok, et al.
Published: (2025-06-01) -
Evaluation of novel 23-gauge winged blood collection set for venipuncture: Impact on patient pain perception
by: Mamta Soni
Published: (2022-01-01)