Science Service System
You are here : Home : Proposals_Summary

Summary of Proposal LAN2662

TitlePermafrost and thermokarst lakes monitoring on the Qinghai-Tibet plateau with high-resolution SAR images
Investigator Tang, Panpan - Institute of remote sensing and digital earth, Chinese academy of sciences, key laboratory of digital earth
Team Member
master student Zou, Pengfei - Institute of remote sensing and digital earth, Chinese academy of sciences, key laboratory of digital earth
assistant professor Tian, Bangsen - Institute of remote sensing and digital earth, Chinese academy of sciences, key laboratory of digital earth
Summary1. Background:As the Earth’s third pole, the Qinghai-Tibet Plateau contains the largest area(about 1.386 million km2) of high-altitude permafrost and huge number of thermokarstlakes. This environment is so fragile that serious permafrostdegradation have occurred due to the climate warming and human activities, andgreatly affected the hydrological cycle, engineeringinfrastructure, ecosystems, and climate feedback.What’s worse, the existence of thermokarst lakes hasaccelerated this process. To better understand the features ofpermafrost degradation and the evolutions of thermokarst lakes,their effect on the surface settlement and the security ofQinghai-Tibet railway/highway, the energy-related processes controlling theregional geomorphology and environment, and the characteristicsof backscatter from floating and grounded lake ice, high-resolution SARimages are needed. 2. Objectives: (1) Use multi-temporal SAR images to monitor the freeze-thawcycles and surface deformation of permafrost regions, especially including therailway, highway and the thermokarst lakeshores. (2) Develop a SAR-basedmethodology for monitoring and mapping thermokarst lakesdevelopment and drainage stage. (3) Evaluate the utility of X-band SARintensity, polarization and phase information for extracting lake ice thicknessand the atmospheric greenhouse gases methane. 3. Methods: (1) At microwave frequencies, seasonal freeze-thaw of the activelayer would significantly alter the soil dielectric constant and then the radarbackscattering coefficients (σ0). So use themulti-temporal SAR intensity images with repeat cycle could monitor thefreeze-thaw cycles of active layer, which is beneficial to estimating thelength of the growing season and annual productivity in the tundra. (2) Permafrostdegradation and seasonal freeze-thaw of active layer would cause secularsettlement and seasonal frost heave thaw settlement respectively, both of whichare harmful to the engineering infrastructure. Multi-temporal InSAR techniquecould monitor the surface deformation with a high precision. Attention is fixedon the railway, highway and thermokarst lakeshores, and high-resolution imagesare needed due to their small sizes. (3) Conduct comparison analysis with the multi-temporalimages to reveal the evolutions of thermokarst lakes, including the expansionof collapse zone and seasonal variations of lakeshore boundary, and identifyenvironmental vulnerability in relation to permafrost degradation andinfrastructure construction. (4) Multi-temporal radar backscatter data will becompiled for selected sites on the lakes during the period of ice cover.Significant changes in backscatter from the time of initial ice formation inautumn until the onset of the spring thaw will be observed and analyzed. Inorder to understand the unique characteristics of lake ice in Qing-TibetPlateau such as no snow ice layer, vigorous ablation and evaporation of surfaceice, smaller bubbles and low porosity, a microwave scattering model will bedeveloped. (5) Map the ice thickness of frozen tundra lakes and inverse the greenhousegas. For float-ice lake, dominated surface scattering from ice-watersurface and volume scattering from elongated vertical gas bubbles in the ice determinesthat the backscatter intensity is increasing with the ice thickness growth. High-resolutionSAR images could provide an excellent framework for lake ice measurement. Then basedon the scattering model simulation, we will find the relationships between thedensity of ice bubbles size and the backscattering coefficient,andthen develop some inversion algorithm for greenhouse gas.

Back to list of proposals

© DLR 2004-2016