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Improving global land cover characterization through data fusion

Improving global land cover characterization through data fusion

作     者:Xiao-Peng Song Chengquan Huang John R.Townshend 

作者机构:Department of Geographical SciencesUniversity of MarylandCollege ParkMDUSA 

出 版 物:《Geo-Spatial Information Science》 (地球空间信息科学学报(英文))

年 卷 期:2017年第20卷第2期

页      面:141-150页

核心收录:

学科分类:0303[法学-社会学] 0709[理学-地质学] 08[工学] 0708[理学-地球物理学] 0705[理学-地理学] 0813[工学-建筑学] 0833[工学-城乡规划学] 0812[工学-计算机科学与技术(可授工学、理学学位)] 

基  金:funded by NASA’s Making Earth System Data Records for Use in Research Environments(MEaSUREs)Program[grant number NNX08AP33A] the NASA Earth and Space Science Fellowship(NESSF)Program[grant number NNX12AN92H] 

主  题:Satellite remote sensing land cover data fusion regression tree global 

摘      要:Global-scale land cover characterization has advanced from a spatial resolution of 1×1°in the mid-1990s to 30×30 m resolution to ***,some mapping challenges exist persistently regardless of the increasing spatial *** fusion has been proved as an effective way of improving land cover *** we applied a machine learning-based data integration approach for improving global-scale forest cover *** approach employed six coarse-resolution(250-1000 m)global land cover maps as input and various regional,higher-resolution land cover data-sets as reference to build regression tree models per *** average error of 10-fold cross validation of the regression tree models varied between 7.70 and 15.68% forest cover and the r2 varied between 0.76 and 0.94,indicating the robustness of the trained *** a result of data fusion,the synthesized global forest cover map was more accurate than any input global *** also showed that other major vegetative land cover types such as cropland,woodland,grassland,and wetland all exhibit similar magnitude of discrepancies as forest among existing land cover *** developed method,because of its type-and scale-invariant feature,can be implemented for other land cover types for improving their global *** ensemble approach can also be internalized for improving data quality when generating a global land cover product,where multiple versions can be produced and subsequently integrated.

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