Abstract
Knowledge of the spatial and temporal distribution of active layer thickness (ALT) throughout northern Alaska would help to understand the effects of climate change in the region, as well as to quantify how much the permafrost degradation manifestly in progress there is contributing to the accumulation of greenhouse gases in the atmosphere. For this reason, we are developing extensive high-resolution maps of ALT in northern Alaska. We use machine learning along with an extensive set of spatial data layers to upscale ALT from thousands of training pixels taken from high resolution swaths of estimated ALT derived from airborne polarimetric P-band synthetic aperture radar (SAR). The resulting maps of up-scaled ALT have been compared to thousands of validation samples set aside from the PolSAR-derived swaths and to in situ ALT measurements. The maps have achieved root-mean-square errors (RMSEs) of 5-7 cm relative to validation samples, and RMSEs of approximately 10-12 cm relative to in situ ALT measurements.
| Original language | English |
|---|---|
| Title of host publication | IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 3660-3663 |
| Number of pages | 4 |
| ISBN (Electronic) | 9781665427920 |
| DOIs | |
| State | Published - 2022 |
| Event | 2022 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2022 - Kuala Lumpur, Malaysia Duration: Jul 17 2022 → Jul 22 2022 |
Publication series
| Name | International Geoscience and Remote Sensing Symposium (IGARSS) |
|---|---|
| Volume | 2022-July |
Conference
| Conference | 2022 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2022 |
|---|---|
| Country/Territory | Malaysia |
| City | Kuala Lumpur |
| Period | 07/17/22 → 07/22/22 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 13 Climate Action
Keywords
- ABoVE
- ALT
- Random Forests
- Upscaling
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