气候变化领域集成服务门户(CCPortal): Towards a comprehensive and consistent global aquatic land cover characterization framework addressing multiple user needs

CCPortal

DOI	10.1016/j.rse.2020.112034
	Towards a comprehensive and consistent global aquatic land cover characterization framework addressing multiple user needs
	Xu P.; Herold M.; Tsendbazar N.-E.; Clevers J.G.P.W.
发表日期	2020
ISSN	00344257
卷号	250
英文摘要	Aquatic land cover represents the land cover type that is significantly influenced by the presence of water over an extensive part of a year. Monitoring global aquatic land cover types plays an essential role in preserving aquatic ecosystems and maintaining the ecosystem service they provide for humans, while at the same time their accurate and consistent monitoring for multiple purposes (e.g. climate modelling, biodiversity conservation, water resource management) remains challenging. Although a number of global aquatic land cover (GALC) datasets are available for use to monitor aquatic ecosystems, there are prominent variabilities among these datasets, which is primarily caused by the inconsistency between different land versus water-related monitoring approaches and characterization schemes. As aquatic land cover exists in many different forms on Earth (e.g. wetland, open water) and can be mapped by different approaches, it is necessary to consider a much more consistent and comprehensive characterization framework that not only ensures the consistency in the monitoring of aquatic land cover but also serves the needs of multiple users (e.g. climate users, agricultural users) interested in different aspects of aquatic lands. In this study, we addressed this issue by 1) reviewing 33 GALC datasets and user needs identified from the citing papers of current datasets and international conventions, policies and agreements in relation to aquatic ecosystems, 2) proposing a global characterization framework for aquatic land cover based on the Land Cover Classification System (LCCS) classifier principles and the identified user needs, and 3) highlighting the opportunities and challenges provided by remote sensing techniques for the implementation of the proposed framework. Results show that users require or prefer various kinds of information on aquatic types including vegetation type, water persistence, the artificiality of cover (i.e. artificial vs natural), water salinity, and the accessibility to the sea (i.e. coastal vs inland). Datasets with medium to high spatial resolution, intra-annual dynamics and inter-annual changes are needed by many users. However, none of the existing datasets can meet all these requirements and a rigorous quantitative accuracy assessment is lacking to evaluate its quality for most of the GALC datasets. The proposed framework has three levels and users are allowed to derive their aquatic land cover types of interest by combining different levels and classifiers of information. This comprehensive mapping framework can help to bridge the gap between user needs and current GALC datasets as well as the gap between generic and aquatic land cover monitoring. The implementation of the framework can benefit from evolving satellite-data availability, improved computation capability and open-source machine learning algorithms, although at the same time it faces challenges mainly coming from the complexity of aquatic ecosystems. The framework proposed in this study provides insights for future operational aquatic land cover monitoring initiatives and will support better understanding and monitoring of complex aquatic ecosystems. © 2020 The Author(s)
英文关键词	Aquatic land cover monitoring; Characterization framework; Global aquatic land cover dataset; LCCS; User needs
语种	英语
scopus关键词	Agricultural robots; Biodiversity; Classification (of information); Earth (planet); Learning algorithms; Machine learning; Monitoring; Remote sensing; Water conservation; Water management; Biodiversity conservation; High spatial resolution; International conventions; Land cover classification; Monitoring approach; Quantitative accuracy; Remote sensing techniques; Waterresource management; Aquatic ecosystems; accuracy assessment; aquatic ecosystem; conceptual framework; conservation planning; data set; ecosystem service; environmental planning; global perspective; land classification; land cover; satellite data
来源期刊	Remote Sensing of Environment
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/179145
作者单位	Laboratory of Geo-Information Science and Remote Sensing, Wageningen University & Research, Droevendaalsesteeg 3, Wageningen, 6708 PB, Netherlands
推荐引用方式 GB/T 7714	Xu P.,Herold M.,Tsendbazar N.-E.,et al. Towards a comprehensive and consistent global aquatic land cover characterization framework addressing multiple user needs[J],2020,250.
APA	Xu P.,Herold M.,Tsendbazar N.-E.,&Clevers J.G.P.W..(2020).Towards a comprehensive and consistent global aquatic land cover characterization framework addressing multiple user needs.Remote Sensing of Environment,250.
MLA	Xu P.,et al."Towards a comprehensive and consistent global aquatic land cover characterization framework addressing multiple user needs".Remote Sensing of Environment 250(2020).