Xiyan Wu

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—Multiple leaf area index (LAI) products have been generated from remote-sensing data. Among them, the Moderate-Resolution Imaging Spectroradiometer (MODIS) LAI product (MOD15A2) is now routinely derived from data acquired by MODIS sensors onboard Terra and Aqua satellite platforms. However, the MODIS LAI product is not spatially and temporally continuous(More)
SAR data acquired over hilly terrain show geometric and radiometric distortions due to the side-looking configuration of the radar sensors. These effects usually lead to a distortion of the useful backscatter information related to land cover or bio-geophysical parameters. Post-processing approaches to remove such distortions are very important to broaden(More)
Leaf area index (LAI) is an important vegetation biophysical variable, and has been widely applied to estimation of crop yield, evapotranspiration, and net photosynthesis. Currently, there are many methods to estimate LAI from remote sensing data through the statistical relationship between LAI and spectral vegetation indices, physical model inversion or(More)
In this study, we proposed three optimized models for calculating the total volume of landslides triggered by the 2008 Wenchuan, China Mw 7.9 earthquake. First, we calculated the volume of each deposit of 1,415 landslides triggered by the quake based on pre- and post-quake DEMs in 20 m resolution. The samples were used to fit the conventional landslide(More)
Leaf area index (LAI) is an important parameter in canopy interception, evapotranspiration, and net photosynthesis. Satellite remote sensing enables derivation of LAI globally at desired spatial resolution and temporal frequency. And several LAI products have been produced from data acquired by Moderate Resolution Imaging Spectroradiometer (MODIS),(More)
In Australia, remotely sensed Landsat data is routinely used for mapping and monitoring changes in the extent of woody perennial vegetation. Time series remotely sensed satellite imagery and ground information is used to form multi-temporal classifications of presence/absence of woody cover. Two broad-scale operational land cover change and monitoring(More)
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