Permafrost Dynamics Observatory: 3. Remote Sensing Big Data for the Active Layer, Soil Moisture, and Greening and Browning
Abstract Because of the remote nature of permafrost, it is difficult to collect data over large geographic regions using ground surveys. Remote sensing enables us to study permafrost at high resolution and over large areas. The Arctic‐Boreal Vulnerability Experiment's Permafrost Dynamics Observ...
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American Geophysical Union (AGU)
2025-01-01
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| Series: | Earth and Space Science |
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| Online Access: | https://doi.org/10.1029/2024EA003725 |
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| author | Elizabeth Wig Kevin Schaefer Roger Michaelides Richard Chen Leah K. Clayton Brittany Fager Lingcao Huang Andrew D. Parsekian Howard Zebker Yingtong Zhang Yuhuan Zhao |
| author_facet | Elizabeth Wig Kevin Schaefer Roger Michaelides Richard Chen Leah K. Clayton Brittany Fager Lingcao Huang Andrew D. Parsekian Howard Zebker Yingtong Zhang Yuhuan Zhao |
| author_sort | Elizabeth Wig |
| collection | DOAJ |
| description | Abstract Because of the remote nature of permafrost, it is difficult to collect data over large geographic regions using ground surveys. Remote sensing enables us to study permafrost at high resolution and over large areas. The Arctic‐Boreal Vulnerability Experiment's Permafrost Dynamics Observatory (PDO) contains data about permafrost subsidence, active layer thickness (ALT), soil water content, and water table depth, derived from airborne radar measurements at 66 image swaths in 2017. With nearly 58,000,000 pixels available for analysis, this data set enables new discoveries and can corroborate findings from previous studies across the Arctic‐Boreal region. We analyze the distributions of these variables and use a space‐for‐time substitution to enable interpretation of the effects of climate trends. Higher soil volumetric water content (VWC) is associated with lower ALT and subsidence, suggesting that Arctic soil may become drier as the climate warms. Soil VWC is bimodal, with saturated soil occurring more commonly in burned areas, while unburned areas are more commonly unsaturated. All permafrost variables show statistically significant differences from one land cover type to another; in particular, cropland has thicker active layers and developed land has lower seasonal subsidence than most other land cover types, potentially related to disturbance and permafrost thaw. While vegetation browning is not strongly associated with any of the measured permafrost variables, more greening is associated with less subsidence and ALT and with higher bulk soil VWC. |
| format | Article |
| id | doaj-art-df9aae627b324f129d999ef3dbcada2a |
| institution | Kabale University |
| issn | 2333-5084 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | American Geophysical Union (AGU) |
| record_format | Article |
| series | Earth and Space Science |
| spelling | doaj-art-df9aae627b324f129d999ef3dbcada2a2025-01-28T11:08:40ZengAmerican Geophysical Union (AGU)Earth and Space Science2333-50842025-01-01121n/an/a10.1029/2024EA003725Permafrost Dynamics Observatory: 3. Remote Sensing Big Data for the Active Layer, Soil Moisture, and Greening and BrowningElizabeth Wig0Kevin Schaefer1Roger Michaelides2Richard Chen3Leah K. Clayton4Brittany Fager5Lingcao Huang6Andrew D. Parsekian7Howard Zebker8Yingtong Zhang9Yuhuan Zhao10Department of Electrical Engineering Stanford University Stanford CA USANational Snow and Ice Data Center Cooperative Institude for Research in Environmental Sciences University of Colorado at Boulder Boulder CO USADepartment of Earth, Environmental, and Planetary Sciences Washington University St. Louis MO USAJet Propulsion Laboratory California Institute of Technology Pasadena CA USADepartment of Earth and Planetary Sciences Yale University New Haven CT USADepartment of Civil Engineering University of Colorado Denver Denver CO USAEarth Science and Observation Center Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado Boulder Boulder Colorado USADepartment of Geology and Geophysics University of Wyoming Laramie WY USADepartment of Electrical Engineering Stanford University Stanford CA USADepartment of Earth and Environment Boston University Boston MA USADepartment of Electrical and Computer Engineering University of Southern California Los Angeles CA USAAbstract Because of the remote nature of permafrost, it is difficult to collect data over large geographic regions using ground surveys. Remote sensing enables us to study permafrost at high resolution and over large areas. The Arctic‐Boreal Vulnerability Experiment's Permafrost Dynamics Observatory (PDO) contains data about permafrost subsidence, active layer thickness (ALT), soil water content, and water table depth, derived from airborne radar measurements at 66 image swaths in 2017. With nearly 58,000,000 pixels available for analysis, this data set enables new discoveries and can corroborate findings from previous studies across the Arctic‐Boreal region. We analyze the distributions of these variables and use a space‐for‐time substitution to enable interpretation of the effects of climate trends. Higher soil volumetric water content (VWC) is associated with lower ALT and subsidence, suggesting that Arctic soil may become drier as the climate warms. Soil VWC is bimodal, with saturated soil occurring more commonly in burned areas, while unburned areas are more commonly unsaturated. All permafrost variables show statistically significant differences from one land cover type to another; in particular, cropland has thicker active layers and developed land has lower seasonal subsidence than most other land cover types, potentially related to disturbance and permafrost thaw. While vegetation browning is not strongly associated with any of the measured permafrost variables, more greening is associated with less subsidence and ALT and with higher bulk soil VWC.https://doi.org/10.1029/2024EA003725permafrostsubsidenceactive layer thicknesssynthetic aperture radarremote sensingsoil moisture |
| spellingShingle | Elizabeth Wig Kevin Schaefer Roger Michaelides Richard Chen Leah K. Clayton Brittany Fager Lingcao Huang Andrew D. Parsekian Howard Zebker Yingtong Zhang Yuhuan Zhao Permafrost Dynamics Observatory: 3. Remote Sensing Big Data for the Active Layer, Soil Moisture, and Greening and Browning Earth and Space Science permafrost subsidence active layer thickness synthetic aperture radar remote sensing soil moisture |
| title | Permafrost Dynamics Observatory: 3. Remote Sensing Big Data for the Active Layer, Soil Moisture, and Greening and Browning |
| title_full | Permafrost Dynamics Observatory: 3. Remote Sensing Big Data for the Active Layer, Soil Moisture, and Greening and Browning |
| title_fullStr | Permafrost Dynamics Observatory: 3. Remote Sensing Big Data for the Active Layer, Soil Moisture, and Greening and Browning |
| title_full_unstemmed | Permafrost Dynamics Observatory: 3. Remote Sensing Big Data for the Active Layer, Soil Moisture, and Greening and Browning |
| title_short | Permafrost Dynamics Observatory: 3. Remote Sensing Big Data for the Active Layer, Soil Moisture, and Greening and Browning |
| title_sort | permafrost dynamics observatory 3 remote sensing big data for the active layer soil moisture and greening and browning |
| topic | permafrost subsidence active layer thickness synthetic aperture radar remote sensing soil moisture |
| url | https://doi.org/10.1029/2024EA003725 |
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