干旱区生态环境知识资源中心(Arid): Generating Land Cover Maps in Semi-arid Regions Based on a 3D Semantic Segmentation Architecture Using Multi-temporal Sentinel-2 Satellite Images: A Case Study of Ludhiana District in Punjab, India

Arid

DOI	10.1007/s12524-024-01839-9
	Generating Land Cover Maps in Semi-arid Regions Based on a 3D Semantic Segmentation Architecture Using Multi-temporal Sentinel-2 Satellite Images: A Case Study of Ludhiana District in Punjab, India
	Buttar, Preetpal Kaur; Sachan, Manoj Kumar
通讯作者	Buttar, PK
来源期刊	JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING
ISSN	0255-660X
EISSN	0974-3006
出版年	2024
卷号	52 期号:2 页码:383-398
英文摘要	Using satellite imagery for land cover mapping is of utmost importance due to its role played in environmental management and protection, assessment of natural resources and human activities and planning for sustainable development. The objective of this research study is to generate high-resolution land use/land cover maps for the semi-arid regions. First, we introduce a novel district-scale land cover dataset for a semi-arid region spanning over an area of 4978 km2 of Ludhiana district located in the state of Punjab, India. The dataset is composed of multi-temporal, multi-spectral Sentinel-2 satellite images for the year 2020 along with their ground truth mask. Eight major land use/land cover classes were mapped at the pixel level. Second, in order to exploit the spatio-temporal nature of satellite imagery, we employ a 3D encoder-decoder-based semantic segmentation architecture to produce the land cover maps. Third, we show the relevance of incorporating temporal features of satellite data for land use/land cover mapping through experimental results. Mean Intersection over Union (mIoU) and F1 score of 89.30% and 94.35%, respectively, were achieved. This study is vital from the perspective of understanding the dynamics of land use/land cover patterns in the context of agriculturally rich areas experiencing rapid urban population growth and shrinkage of cropland.
英文关键词	Semantic segmentation Land cover mapping 3D encoder-decoder architecture Remote sensing Sentinel-2 Semi-arid regions
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:001168997000002
WOS关键词	NEURAL-NETWORKS ; CLASSIFICATION ; TIME
WOS类目	Environmental Sciences ; Remote Sensing
WOS研究方向	Environmental Sciences & Ecology ; Remote Sensing
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/404727
推荐引用方式 GB/T 7714	Buttar, Preetpal Kaur,Sachan, Manoj Kumar. Generating Land Cover Maps in Semi-arid Regions Based on a 3D Semantic Segmentation Architecture Using Multi-temporal Sentinel-2 Satellite Images: A Case Study of Ludhiana District in Punjab, India[J],2024,52(2):383-398.
APA	Buttar, Preetpal Kaur,&Sachan, Manoj Kumar.(2024).Generating Land Cover Maps in Semi-arid Regions Based on a 3D Semantic Segmentation Architecture Using Multi-temporal Sentinel-2 Satellite Images: A Case Study of Ludhiana District in Punjab, India.JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING,52(2),383-398.
MLA	Buttar, Preetpal Kaur,et al."Generating Land Cover Maps in Semi-arid Regions Based on a 3D Semantic Segmentation Architecture Using Multi-temporal Sentinel-2 Satellite Images: A Case Study of Ludhiana District in Punjab, India".JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING 52.2(2024):383-398.