Evaluation of diverse classification approaches for land use/cover mapping in a Mediterranean region utilizing Hyperion data

作     者：Alata Elatawneh Chariton Kalaitzidis George P.Petropoulosc Thomas Schneider 

作者机构：Institute of Forest ManagementTechnische Universität Muünchen(TUM)85354 FreisingGermany Department of Geoinformation in Environmental ManagementMediterranean Agronomic Institute of Chania(MAICh)Chania 73100Greece INFOCOSMOS13341 AthensGreece 

出 版 物：《International Journal of Digital Earth》 (国际数字地球学报（英文）)

年 卷 期：2014年第7卷第3期

页      面：194-216页

核心收录：

学科分类：08[工学] 09[农学] 083002[工学-环境工程] 0830[工学-环境科学与工程（可授工学、理学、农学学位）] 0708[理学-地球物理学] 0804[工学-仪器科学与技术] 0903[农学-农业资源与环境] 0816[工学-测绘科学与技术] 081602[工学-摄影测量与遥感] 0835[工学-软件工程] 0704[理学-天文学] 0811[工学-控制科学与工程] 081102[工学-检测技术与自动化装置] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Hyperion Earth’s land use/cover mapping digital image analysis spectral angle mapper sub-pixel classification artificial neural networks Greece 

摘      要：Information on Earth’s land surface cover is commonly obtained through digital image analysis of data acquired from remote sensing *** this study,we evaluated the use of diverse classification techniques in discriminating land use/cover types in a typical Mediterranean setting using Hyperion *** this purpose,the spectral angle mapper(SAM),the object-based and the non-linear spectral unmixing based on artificial neural networks(ANNs)techniques were applied.A further objective had been to investigate the effect of two approaches for training sites selection in the SAM classification,namely of the pixel purity index(PPI)and of the direct selection of training points from the Hyperion imagery assisted by a QuickBird imagery and field-based training *** classification outperformed the other techniques with an overall accuracy of 83%.Sub-pixel classification based on the ANN showed an overall accuracy of 52%,very close to that of SAM(48%).SAM applied using the training sites selected directly from the Hyperion imagery supported by the QuickBird image and the field visits returned an increase accuracy by 16%.Yet,all techniques appeared to suffer from the relatively low spatial resolution of the Hyperion imagery,which affected the spectral separation among the land use/cover classes.