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EO-based modelling and mapping of permafrost
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Observations have shown that climate is warming, and permafrost is thawing. The major questions now facing us are what are its impacts and consequences, and what can we can do about it. To answer these questions, we need to know more details about permafrost
thaw, such as how permafrost will thaw, where, when, and how much. Field observations are essential, but they have limitations in spatial and temporal coverages. Satellite remote sensing (or Earth Observation, EO) can provide detailed spatial information about land surface, and process-based models
are important tools for data synthesizing, process understanding, and future projections. EO-based modelling combines these two technologies and can provide spatial distributions and changes based on observations and our understanding. Following this approach, we developed a processbased permafrost
model considering the impacts of climate, vegetation, snow, water, soil features and geological conditions. With the inputs of atmospheric climate, vegetation and ground surface conditions from remote sensing, and soil and geological data, we can model ground temperature profiles, active-layer
thickness, permafrost conditions, and their spatial distributions and changes with time. We conducted a nation-wide permafrost modelling and mapping study for Canada. The model simulated ground temperature, permafrost distribution, active-layer thickness, and permafrost depth are comparable with
observations. The results show that the area underlain by permafrost in Canada will be reduced by 16-20% from the 1990s to the 2090s, and permafrost degradation will continue after the 21st century because the ground thermal regime is in disequilibrium. Now we are working with Parks Canada
Agency to model and map permafrost in some northern national parks at a higher spatial resolution. This collaboration not only serves Parks Canada Agency for their monitoring and management operations, but it also provides us a reliable and cost-effective test bed for our methods and results. This
EObased permafrost modelling and mapping work has been supported by the climate change program in ESS, a GRIP project, ParkSpace, funded by Canadian Space Agency, and a IPY project, CiCAT.
Title: EO-based modelling and mapping of permafrost
Description:
Observations have shown that climate is warming, and permafrost is thawing.
The major questions now facing us are what are its impacts and consequences, and what can we can do about it.
To answer these questions, we need to know more details about permafrost
thaw, such as how permafrost will thaw, where, when, and how much.
Field observations are essential, but they have limitations in spatial and temporal coverages.
Satellite remote sensing (or Earth Observation, EO) can provide detailed spatial information about land surface, and process-based models
are important tools for data synthesizing, process understanding, and future projections.
EO-based modelling combines these two technologies and can provide spatial distributions and changes based on observations and our understanding.
Following this approach, we developed a processbased permafrost
model considering the impacts of climate, vegetation, snow, water, soil features and geological conditions.
With the inputs of atmospheric climate, vegetation and ground surface conditions from remote sensing, and soil and geological data, we can model ground temperature profiles, active-layer
thickness, permafrost conditions, and their spatial distributions and changes with time.
We conducted a nation-wide permafrost modelling and mapping study for Canada.
The model simulated ground temperature, permafrost distribution, active-layer thickness, and permafrost depth are comparable with
observations.
The results show that the area underlain by permafrost in Canada will be reduced by 16-20% from the 1990s to the 2090s, and permafrost degradation will continue after the 21st century because the ground thermal regime is in disequilibrium.
Now we are working with Parks Canada
Agency to model and map permafrost in some northern national parks at a higher spatial resolution.
This collaboration not only serves Parks Canada Agency for their monitoring and management operations, but it also provides us a reliable and cost-effective test bed for our methods and results.
This
EObased permafrost modelling and mapping work has been supported by the climate change program in ESS, a GRIP project, ParkSpace, funded by Canadian Space Agency, and a IPY project, CiCAT.
Related Results
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