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REMOTE SENSING FOR LAND & RESOURCES    2011, Vol. 23 Issue (1) : 52-56     DOI: 10.6046/gtzyyg.2011.01.10
Technology and Methodology |
Progressive Linear Prediction Fitting for Extracting DTM from Airborne LiDAR Data
ZHANG Jing 1, ZHANG Xiao-jun 1, JIANG Wan-shou 1, WANG Jian-chao 2, GUO Da-hai 2
(1.LIESMARS, Wuhan University, Wuhan 430079, China; 2.China Aero Geophysical Survey & Remote Sensing Center for Land and Resousces, Beijing 100083, China)
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Abstract   A progressive linear prediction filtering algorithm is proposed for extracting DEM from LiDAR data. Some processes are inserted in the ordinary linear prediction algorithm, such as gross error detection, initial value selection, landform analysis, and smoothness detection. The authors used this algorithm to process 6 datasets published by ISPRS as standard filtering test data. The results show that the improvement in the traditional methods can increase the precision of DEM.
Keywords Running water      Water supply network system      Module     
: 

TP 75

 
Issue Date: 22 March 2011
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ZHANG Jing, ZHANG Xiao-Jun, JIANG Wang-Shou, WANG Jian-Chao, GUO Da-Hai. Progressive Linear Prediction Fitting for Extracting DTM from Airborne LiDAR Data[J]. REMOTE SENSING FOR LAND & RESOURCES,2011, 23(1): 52-56.
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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2011.01.10     OR     https://www.gtzyyg.com/EN/Y2011/V23/I1/52


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