It is clear from the workshop discussions that a multiscale, multisensor approach, using ground-based, airborne, and spaceborne instruments, would substantially advance the current state of knowledge of permafrost landscapes and, in the process, provide critically needed information on subsurface properties that determine the vulnerability of permafrost systems to warming. The data sets and products thus derived—and necessarily calibrated and validated with field measurements—would allow parameterization and development of more realistic permafrost models than would otherwise be possible. Taken together, these remote sensing–derived maps of properties and improved models would advance our understanding and prediction of the state of permafrost landscapes and associated feedbacks to the climate system.
Many participants said that additional high-quality information on permafrost properties is needed for models to realistically capture processes and faithfully predict likely future outcomes at any scale—from local to regional to global. To achieve this desired objective, they noted that a range of remote sensing data sets are needed, from measurements of properties of the land surface that provide indirect indicators of permafrost properties to more direct measurements that can be used to estimate those same properties. Specific desired temporal and spatial resolutions for each variable can be found in Tables 2.1 and 2.2. Many workshop participants noted that ice content is particularly important, because it strongly influences the vulnerability of permafrost to degradation (thaw) and thus the processes that follow that degradation (e.g., surface subsidence, thermokarst formation, and the release of old carbon frozen for decades to centuries and millennia).
Although there are a number of current remote sensing instruments on various platforms and planned missions for estimating surface variables relevant to indirect inference of permafrost properties, there are few such instruments or missions for direct estimation of permafrost properties. Several participants said that current remote sensing observations and derived data sets will be used in innovative ways to map aspects of permafrost landscapes or indirectly infer subsurface properties. The upcoming ICESat-2 mission will also be valuable for providing time series of surface topography that could be used to map surface deformation and thermokarst features.
However, as noted by numerous participants, there is a pressing need to advance remote sensing products in the near future, in particular for direct observations of permafrost properties. Polarimetric, InSAR, and LiDAR may be particularly valuable. Of the planned spaceborne missions, workshop participants considered the SMAP mission, planned for launch in late 2014, to be valuable for providing frequent (2-3 days) freeze/thaw and soil moisture products, albeit at relatively coarse (~3 km at best) spatial resolution. The U.S. L-band polarimetric InSAR mission would be particularly valuable for mapping higher resolution (100 m or better) seasonal freeze/thaw cycles, surface deformation, and subsidence. Even so, additional advancements are needed to more directly map permafrost features. P-band SAR, such as that planned for the BIOMASS mission, scheduled for launch in 2019, has the poten-
tial to advance remote sensing of active layer thickness and soil moisture content (and, based on studies with GPR, perhaps even ice content). However, BIOMASS P-band satellite will be restricted from transmitting in most of North America, Europe, and northern Eurasia because of spectrum usage conflicts (especially usage by military services). Such restriction is currently not imposed in Central and South America, allowing BIOMASS to acquire data over the tropics. Regardless of the frequency transmit permission, however, the spatial resolution of BIOMASS (200 m or coarser) is not as high as desired, as noted by many workshop participants.
Numerous participants said that most of the advances in permafrost mapping in the near future are likely to come from studies based on the use of airborne instrumentation coupled with field measurements used for calibration and validation efforts and associated model development. For example, P-band stripmap SAR data can be acquired across large regions, where military radars and communications are not affected, to retrieve active layer and other subsurface properties. The potential of using multiple-receiver multiple-transmitter airborne radars, at low frequencies (P-band and lower), has also been demonstrated for 3D imaging of subsurface features and should be exploited here as well, said several participants. L-band InSAR data can be acquired over areas where increases in seasonal thaw and long-term permafrost degradation create substantial deformation of the surface because of changes in subsurface moisture/ice content. High-resolution LiDAR data can be acquired over areas where there is thermokarst activity, often indicative of rapid permafrost degradation. AEM can be acquired over areas where boreholes and other field measurements allow the AEM data to be calibrated to map permafrost extent, depth to top of permafrost, permafrost thickness, near-surface soil moisture and ice content, and other variables of interest. Each of these airborne observations allows upscaling of field measurements to much larger areas while building on the information that can be discerned from current and planned spaceborne missions. This multitiered approach, scaling from field to aircraft to satellite observations, would allow high-resolution and spatially extensive retrievals and would thus enable the use of satellite observations over regions where no aircraft or field measurements exist.
As discussed by numerous participants, progress in improving models—both land surface/subsurface permafrost and hydrological models and remote sensing models for developing advanced retrieval algorithms—must be made in the immediate future. In situ and remotely sensed data can be used as model inputs and calibration data sets, and/or for validation. Multisensor data fusion and modeling have been extremely successful in the atmospheric reanalysis community and could be employed to a greater extent in land surface modeling, particularly in permafrost regions. Steps are being taken in this direction by programs such as NASA’s Arctic Boreal Vulnerability Experiment, the Department of the Interior’s and the U.S. Geological Survey’s Integrated Ecosystem Model Project, and the Department of Energy’s Next Generation Ecosystem Experiment, all of which could be leveraged in advancing remote sensing of permafrost.