Training Polygon Shapefile
URL: https://github.com/initze/DL_RTS_Paper/raw/main/data/GT_Set_Nitze_etal_2021_TrainingSet_RTS.zip
Dataset description:
In a warming Arctic, permafrost-related disturbances, such as retrogressive thaw slumps (RTS), are becoming more abundant and dynamic, with serious implications for permafrost stability...
Avots: Developing and Testing a Deep Learning Approach for Mapping Retrogressive Thaw Slumps (CA, RU)
Šim resursam pašreiz vēl nav izveidots skats.
Papildus informācija
| Lauks | Vērtība |
|---|---|
| Data last updated | 2022. gada 30. marts |
| Metadata last updated | 2022. gada 30. marts |
| Izveidots | 2022. gada 30. marts |
| Formāts | SHP |
| Licence | Creative Commons Attribution 4.0 |
| Datastore active | False |
| Datastore contains all records of source file | False |
| Has views | False |
| Id | cd1c672c-af44-45ac-8726-2d1d4a5a4b3b |
| Mimetype | application/zip |
| Package id | b21faa71-88a3-4097-9153-2b665cd2c995 |
| Position | 0 |
| State | active |
| Tracking summary | {'total': 10, 'recent': 1} |
Attention! The specified license is that of the dataset. Licenses from other sources, e.g. publications or figures related to the dataset, may be subject to other licenses.