干旱区生态环境知识资源中心(Arid): An Object- and Shapelet-Based Method for Mapping Planted Forest Dynamics from Landsat Time Series

Arid

DOI	10.3390/rs14246188
	An Object- and Shapelet-Based Method for Mapping Planted Forest Dynamics from Landsat Time Series
	Xue, Xiaojing; Wei, Caiyong; Yang, Qin; Tian, Lingwen; Zhu, Lihong; Meng, Yuanyuan; Liu, Xiangnan
通讯作者	Liu, XN
来源期刊	REMOTE SENSING
EISSN	2072-4292
出版年	2022
卷号	14 期号:24
英文摘要	Large-scale afforestation in arid and semi-arid areas with fragile ecosystems for the purpose of restoring degradation and mitigating climate change has raised issues of decreased groundwater recharge and ambiguous climatic benefits. An accurate planted forest mapping method is necessary to explore the impacts of afforestation expansion on fragile ecosystems. However, distinguishing planted forests from natural forests using remote sensing technology is not a trivial task due to their strong spectral similarities, even when assisted by phenological variables. In this study, we developed an object- and shapelet-based (OASB) method for mapping the planted forests of the Ningxia Hui Autonomous Region (NHAR), China in 2020 and for tracing the planting years between 1991 and 2020. The novel method consists of two components: (1) a simple non-iterative clustering to yield homogenous objects for building an improved time series; (2) a shapelet-based classification to distinguish the planted forests from the natural forests and to estimate the planting year, by detecting the temporal characteristics representing the planting activities. The created map accurately depicted the planted forests of the NHAR in 2020, with an overall accuracy of 87.3% (Kappa = 0.82). The area of the planted forest was counted as 0.56 million ha, accounting for 67% of the total forest area. Additionally, the planting year calendar (RMSE = 2.46 years) illustrated that the establishment of the planted forests matched the implemented ecological restoration initiatives over the past decades. Overall, the OASB has great potential for mapping the planted forests in the NHAR or other arid and semi-arid regions, and the map products derived from this method are conducive to evaluating forestry eco-engineering projects and facilitating the sustainable development of forest ecosystems.
英文关键词	planted forests mapping shapelet-based classification image segmentation object-level time series forestry eco-engineering projects
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:000902930700001
WOS关键词	TEMPORAL SEGMENTATION ; CLASSIFICATION ; PLANTATIONS ; EXPANSION ; RESTORATION ; ALGORITHM ; NINGXIA ; INDEX ; PIXEL ; LIDAR
WOS类目	Environmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
WOS研究方向	Environmental Sciences & Ecology ; Geology ; 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/2XILL650/394250
推荐引用方式 GB/T 7714	Xue, Xiaojing,Wei, Caiyong,Yang, Qin,et al. An Object- and Shapelet-Based Method for Mapping Planted Forest Dynamics from Landsat Time Series[J],2022,14(24).
APA	Xue, Xiaojing.,Wei, Caiyong.,Yang, Qin.,Tian, Lingwen.,Zhu, Lihong.,...&Liu, Xiangnan.(2022).An Object- and Shapelet-Based Method for Mapping Planted Forest Dynamics from Landsat Time Series.REMOTE SENSING,14(24).
MLA	Xue, Xiaojing,et al."An Object- and Shapelet-Based Method for Mapping Planted Forest Dynamics from Landsat Time Series".REMOTE SENSING 14.24(2022).