干旱区生态环境知识资源中心(Arid): Desert landform detection and mapping using a semi-automated object-based image analysis approach

Arid

DOI	10.1016/j.jaridenv.2022.104721
	Desert landform detection and mapping using a semi-automated object-based image analysis approach
	Garajeh, Mohammad Kazemi; Feizizadeh, Bakhtiar; Weng, Qihao; Moghaddam, Mohammad Hossein Rezaei; Garajeh, Ali Kazemi
通讯作者	Garajeh, MK (corresponding author)，Univ Tabriz, Dept Remote Sensing & GIS, Tabriz, Iran.
来源期刊	JOURNAL OF ARID ENVIRONMENTS
ISSN	0140-1963
EISSN	1095-922X
出版年	2022
卷号	199
英文摘要	Traditional landform modeling approaches are labor-intensive and time-consuming. We proposed and developed a semi-automated object-based image analysis (OBIA) rule set approach for desert landforms detection and mapping. Sentinel-2 image and digital elevation model (DEM) were acquired for the study area. The multi resolution segmentation algorithm was employed on the datasets to select relevant features to define appropriate segmentation scales for all landform categories. Object-based rule sets were then employed using spatial (DEM and its derivatives, e.g., slope, aspect, and hillshade) and spectral information for semi-automated classification of the desert landforms. Desert landforms are detected and classified into four classes: saline dome, barchan, playa, and dune. The Fuzzy Synthetic Evaluation (FSE) technique was applied in concert with the error matrix to validate the accuracy of the classification results based on field data, Google Earth, and geological maps. Our findings demonstrated the highest confidence of overall accuracy (OA) 96.21%, 92.58%, 95.99%, and 95.05% respectively, for the saline dome, barchan, playa, and dune. Results showed the strong potential of the rule-based OBIA remote sensing approach for desert landform detection and delineation. Results further demonstrated the efficiency of spatial and spectral features for desert landforms detection and delineation.
英文关键词	Object-based image analysis (OBIA) Fuzzy rule-based classification Desert landforms Geomorphology Earth's landforms
类型	Article
语种	英语
收录类别	SCI-E ; SSCI
WOS记录号	WOS:000747874400001
WOS关键词	MULTIRESOLUTION SEGMENTATION ; ACCURACY ASSESSMENT ; SCALE PARAMETER ; HIGH-PLAINS ; CLASSIFICATION ; COVER ; QUALITY ; PIXEL ; SOIL ; AREA
WOS类目	Ecology ; Environmental Sciences
WOS研究方向	Environmental Sciences & Ecology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/376205
作者单位	[Garajeh, Mohammad Kazemi; Feizizadeh, Bakhtiar; Moghaddam, Mohammad Hossein Rezaei] Univ Tabriz, Dept Remote Sensing & GIS, Tabriz, Iran; [Feizizadeh, Bakhtiar] Univ Tabriz, Inst Environm, Tabriz, Iran; [Weng, Qihao] Hong Kong Polytech Univ, Dept Land Surveying & Geoinformat, Hung Hom, Kowloon, Hong Kong, Peoples R China; [Garajeh, Ali Kazemi] Tech Inst 2 Tabriz, Dept Econ & Management, Tabriz, Iran
推荐引用方式 GB/T 7714	Garajeh, Mohammad Kazemi,Feizizadeh, Bakhtiar,Weng, Qihao,et al. Desert landform detection and mapping using a semi-automated object-based image analysis approach[J],2022,199.
APA	Garajeh, Mohammad Kazemi,Feizizadeh, Bakhtiar,Weng, Qihao,Moghaddam, Mohammad Hossein Rezaei,&Garajeh, Ali Kazemi.(2022).Desert landform detection and mapping using a semi-automated object-based image analysis approach.JOURNAL OF ARID ENVIRONMENTS,199.
MLA	Garajeh, Mohammad Kazemi,et al."Desert landform detection and mapping using a semi-automated object-based image analysis approach".JOURNAL OF ARID ENVIRONMENTS 199(2022).