Tengyu Zhang

Evapotranspiration Variations in the Mississippi River Basin Estimated From GPS Observations

Evapotranspiration (ET) is one of the key variables in water cycle and ecological systems, whereas it is difficult to quantify ET variations from traditional observations in large river basins, e.g., Mississippi River basin (MRB). In this paper, a new geodetic tool, i.e., Global Positioning System (GPS), is used for the first time to estimate monthly ET variations at a regional scale. Based on the water balance equation, the monthly ET variation is estimated using the GPS-derived terrestrial water storage (TWS) from January 2006 to July 2015 in MRB. The annual amplitude of GPS-inferred TWS in MRB agrees well with the results of Gravity Recovery and Climate Experiment. The ET variations from the water balance approach agree well with the land surface modeling and remote sensing data. The correlation of GPS-inferred ET with other ET products is higher than 0.8, which indicates that the GPS-estimated ET well characterizes the ET variations in MRB. The annual amplitude of GPS-inferred ET variations is 47.9 mm/month, which is close to that from land surface modeling of North American Land Data Assimilation System, and a little larger than MODerate Resolution Imaging Spectroradiometer. The mean monthly ET reaches its maximum in June-July and its minimum in December, which is consistent with the periodic pattern of radiative energy in a year. Furthermore, the ET variations are mainly dominated by the temperature change in MRB.

Glacial density and GIA in Alaska estimated from ICESat, GPS and GRACE measurements: Glacial Density and GIA in Alaska

The density of glacial volume change in Alaska is a key factor in estimating the glacier mass loss from altimetry observations. However, the density of Alaskan glaciers has large uncertainty due to the lack of in situ measurements. In this paper, using the measurements of Ice, Cloud, and land Elevation Satellite (ICESat), Global Positioning System (GPS), and Gravity Recovery and Climate Experiment (GRACE) from 2003 to 2009, an optimal density of glacial volume change with 750 kg/m is estimated for the first time to fit the measurements. The glacier mass loss is 57.5 6.5 Gt by converting the volumetric change from ICESat with the estimated density 750 kg/m. Based on the empirical relation, the depth-density profiles are constructed, which show glacial density variation information with depths in Alaska. By separating the glacier mass loss from glacial isostatic adjustment (GIA) effects in GPS uplift rates and GRACE total water storage trends, the GIA uplift rates are estimated in Alaska. The best fitting model consists of a 60 km elastic lithosphere and 110 km thick asthenosphere with a viscosity of 2.0 × 10 Pa s over a two-layer mantle.

Ice mass balance and GIA effects in tibet estimated from GRACE and ICESat measurements

The Glacial Isostatic Adjustment (GIA) effect in the Tibetan Plateau has been controversial because the past and present dimensions of ice sheets are not clear and in-situ observations are less. In this study, the Gravity Recovery And Climate Experiment (GRACE) and Ice, Cloud, and land Elevation Satellite (ICESat) measurements are used to estimate the ice mass balance and Glacier Isostatic Adjustment (GIA) effects in the Tibetan Plateau. The GIA effects, which contribute to the uncertainty in estimating the ice mass change on the Tibetan plateau, are very controversial. The total mass change measured by ICESat and hydrological models are subtracted from the GRACE terrestrial water storage, and the residual signals are mainly the GIA effects. After the correction of truncation and filtering effects from GRACE, the GIA effects are estimated by residual signal, which are further compared and validated by GIA models.

Automatic Recognition of Impact Craters on the Martian Surface from DEM and Images

Impact craters are the most outstanding and attractive geomorphological features on the surface of the planets, showing variety and complexity of the surface morphology. The accurate recognition of impact craters on Mars is very useful to analyze and understand the relative dating of Martian surface. In this chapter, four crater-detection methods have been presented and discussed with various extent of discrimination ability on Martian images or topography data. The modified ad boosting approach demonstrates the best performance in classification of craters, while the algorithms based on topography data have low efficiency in automatic detection. Comparing to previous solutions, the modified ad boosting method has greatly improved the detecting performance of the algorithm and reduced detection time.

Automatic recognition of Martian craters based on MOLA-derived digital topography

The recognition of impact craters can provide information on impact craters history and Martian evolution processes as well as for Martian rover landing site. Most previous studies about machine detection of impact craters on Mars are based on imagery data, however, it has large uncertainty in image processing. In this study, we present a novel approach for automatic recognition of impact craters based on the Mars Orbiter Laser Altimeter (MOLA)-derived digital topography data. Topographic curvature, which delineates impact crater on Digital Elevation Model (DEM), can be deduced from topography data. The thresholding map of curvature is transformed into a binary map, from which we can detect impact craters by combination of segmentation and flooding algorithms. More impact craters on Mars with confirmation algorithm can be effectively distinguished truly, which are added the existing catalog of manually identified Martian craters. It will be more useful for the study on impact craters history and Martian evolution processes as well as Martian rover landing navigation.