干旱区生态环境知识资源中心(Arid): A Novel Method for Identifying Crops in Parcels Constrained by Environmental Factors Through the Integration of a Gaofen-2 High-Resolution Remote Sensing Image and Sentinel-2 Time Series

Arid

DOI	10.1109/JSTARS.2023.3329987
	A Novel Method for Identifying Crops in Parcels Constrained by Environmental Factors Through the Integration of a Gaofen-2 High-Resolution Remote Sensing Image and Sentinel-2 Time Series
	Chen, Weijia; Liu, Guilin
通讯作者	Liu, GL
来源期刊	IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
ISSN	1939-1404
EISSN	2151-1535
出版年	2024
卷号	17 页码:450-463
英文摘要	Accurately mapping crop cultivation types is essential for the sustainable development of precision agriculture. Environmental restrictions on crop growth, such as soil salinization in arid zones, generally lead to spatial crop growth heterogeneity within cropland fields, which in turn generates differences in the spectral responses reflected in optical remote sensing images of the same croplands and leads to pixel-scale crop-mapping misclassifications. Thus, through this article, we proposed a method to solve this problem at the geoparcel scale by integrating geometric features from a Gaofen-2 high-resolution remote sensing image and the spectral-temporal features derived from Sentinel-2 time series. The results showed that cropland parcels could be accurately extracted from Gaofen-2 images by employing the U-Net semantic segmentation model with an overall accuracy (OA) reaching 97% and a kappa coefficient of 0.95. Then, geoparcel-scale crop types were mapped based on prior crop phenology knowledge and the corresponding Sentinel-2 time series using the time-weighted dynamic time warping (TWDTW) classification algorithm. The parcel-based TWDTW algorithm had an OA of 99.64%, a kappa coefficient of 0.99, and optimal spatial homogeneity in the results, thus outperforming the pixel-based TWDTW method. These results provide a potential solution for mapping crops under spatially heterogeneous cropland conditions affected by various environmental constraints.
英文关键词	Crop mapping parcel-based segment spectral-temporal features time-weighted dynamic time warping (TWDTW)
类型	Article
语种	英语
开放获取类型	gold
收录类别	SCI-E
WOS记录号	WOS:001123281300033
WOS关键词	CLASSIFICATION
WOS类目	Engineering, Electrical & Electronic ; Geography, Physical ; Remote Sensing ; Imaging Science & Photographic Technology
WOS研究方向	Engineering ; Physical Geography ; Remote Sensing ; Imaging Science & Photographic Technology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/404139
推荐引用方式 GB/T 7714	Chen, Weijia,Liu, Guilin. A Novel Method for Identifying Crops in Parcels Constrained by Environmental Factors Through the Integration of a Gaofen-2 High-Resolution Remote Sensing Image and Sentinel-2 Time Series[J],2024,17:450-463.
APA	Chen, Weijia,&Liu, Guilin.(2024).A Novel Method for Identifying Crops in Parcels Constrained by Environmental Factors Through the Integration of a Gaofen-2 High-Resolution Remote Sensing Image and Sentinel-2 Time Series.IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,17,450-463.
MLA	Chen, Weijia,et al."A Novel Method for Identifying Crops in Parcels Constrained by Environmental Factors Through the Integration of a Gaofen-2 High-Resolution Remote Sensing Image and Sentinel-2 Time Series".IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 17(2024):450-463.