Weian Wang
Tongji University
21 Papers
73 Citations
Weian Wang is an academic researcher from Tongji University. The author has contributed to research in topics: Landslide & Wireless sensor network. The author has an hindex of 7, co-authored 21 publications. Previous affiliations of Weian Wang include Hong Kong Polytechnic University & State Bureau of Surveying and Mapping.
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Papers
Building-damage detection using pre- and post-seismic high-resolution satellite stereo imagery: A case study of the May 2008 Wenchuan earthquake
Xiaohua Tong,Zhonghua Hong,Shijie Liu,Xue Zhang,Huan Xie,Zhengyuan Li,Sonlin Yang,Weian Wang,Feng Bao +8 more
TL;DR: Wang et al. as mentioned in this paper presented an approach for the detection of buildings that have collapsed in an earthquake based on 3D geometric changes, particularly height change of the buildings, using pre- and post-seismic IKONOS stereo image pairs.
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55-year (1960–2015) spatiotemporal shoreline change analysis using historical DISP and Landsat time series data in Shanghai
TL;DR: Wang et al. as discussed by the authors analyzed 55 years of spatiotemporal shoreline changes in Shanghai, China, by integrating the historical Declassified Intelligence Satellite Photography (DISP) and Landsat time series data at five-year intervals from 1960 to 2015.
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Landslide Investigation with Remote Sensing and Sensor Network: From Susceptibility Mapping and Scaled-down Simulation towards in situ Sensor Network Design
Gang Qiao,Ping Lu,Marco Scaioni,Shuying Xu,Xiaohua Tong,Tiantian Feng,Hangbin Wu,Wen Chen,Yixiang Tian,Weian Wang,Rongxing Li +10 more
TL;DR: An integrated approach to landslide research based on remote sensing and sensor networks is presented, composed of three important parts: landslide susceptibility mapping using remote-sensing techniques for susceptible determination of landslide spots, scaled-down landslide simulation experiments for validation of sensor network for landslide monitoring, and in situ sensor network deployment for intensified landslide monitoring.
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Assessment of Geo-positioning Capability of High Resolution Satellite Imagery for Densely Populated High Buildings in Metropolitan Areas
TL;DR: In this article, the authors analyzed the geo-positioning capability of high-resolution satellite images in a very special metropolitan environment where within a relatively small region there are a large number of densely populated skyscrapers and high buildings.
An improved geopositioning model of QuickBird high resolution satellite imagery by compensating spatial correlated errors
TL;DR: Wang et al. as mentioned in this paper introduced space correlated errors (SCEs) and model them as signals in the bias-corrected rational function model (RFM) and estimate the SCEs at the ground control points (GCPs) together with the biascorrected parameters using least squares collocation.
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