Study on crustal deformation of Wenchuan Ms8.0 earthquake using wide-swath ScanSAR and MODIS

This paper presents a broad-range study of the co-seismic deformation field of Wenchuan Ms8.0 earthquake by ScanSAR interferometry. The results show co-seismic displacements ranging from - 19.8 on the footwall side of the seismogenic fault to 73.6 cm on the hanging-wall side, or from - 22.4 to 77.2 cm with atmospheric-delay correction by MODIS. These results differ from the GPS line-of-sight results by 4. 58 cm to 2.78 cm, respectively, on the average. We could not obtain the displacements near the earthquake-rupture zone due to incoherence problem.

Spatiotemporal Modeling of Monthly Precipitation in the Upper Shiyang River Watershed in West Central Gansu,Northwest China

This paper outlines a methodology to estimate monthly precipitation surfaces at 1-kin resolution for the Upper Shiyang River watershed （USRW） in northwest China. Generation of precipitation maps is based on the application of a four-variable genetic algorithm （GA） trained on 10 years of weather and ancillary data, i.e., surface air temperature, relative humidity, Digital Elevation Model-derived estimates of elevation, and time of year collected at 29 weather stations in west-central Gansu and northern Qinghai province. An observed-to-GA predicted data comparison of 10 years of precipitation collected at the 29 weather stations showed that about 84% of the variability in observed values could be explained by the trained GA, including variability in two independent datasets. Point-comparisons of observed and modeled precipitation along an elevation-rainfall gradient demonstrated near-similar spatiotemporal patterns. A precipitation surface for USRW for July, 2005, was developed with the trained GA and input surfaces of surface air temperature and relative humidity generated from Moderate Resolution Imaging Spectroradiometer sensor （MODIS） products of land surface temperature. Spatial tendencies in predicted maximum and minimum values of surface air temperature, relative humidity, and precipitation within a 2-kin radius circle around selected weather stations were in close agreement with the values measured at the weather stations.

A simple data assimilation method for improving the MODIS LAI time-series data products based on the object analysis and gradient inverse weighted filter

A simple data assimilation method for improving estimation of moderate resolution imaging spectroradiometer （MODIS） leaf area index （LAI） time-series data products based on the gradient inverse weighted filter and object analysis is proposed. The properties and quality control （QC） of MODIS LAI data products are introduced. Also, the gradient inverse weighted filter and object analysis are analyzed. An experiment based on the simple data assimilation method is performed using MODIS LAI data sets from 2000 to 2005 of Guizhou Province in China.

A global terrestrial ecosystem respiration dataset(2001-2010)estimated with MODIS land surface temperature and vegetation indices

This paper describes how a validated semi-empirical,but physiologically based,remote sensing model-Ensemble_all-was upscaled using MODIS land surface temperature data(MOD11C2),enhanced vegetation indices(MOD13C1)and land-cover data(MCD12C1)to produce a global terrestrial ecosystem respiration data set(Reco)for January 2001-December 2010.The temporal resolution of this data set is 1 month,the spatial resolution is 0.05°,and the range is from 55°S to 65°N and 180°W to 180°E(crop and natural vegetation mosaic is not included).After crossvalidating our data set using in-situ observations as well as Reco outputs from an empirical variable_Q10 model,a LPJ_S1 process model and a machine learning method model,we found that our data set performed well in detecting both temporal and spatial patterns in Reco’s simulation in most ecosystems across the world.This data set can be found at http://www.dx.doi.org/10.11922/sciencedb.934.