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Towards a comprehensive and consistent global aquatic land cover characterization framework addressing multiple user needs
Remote Sensing of Environment ( IF 13.5 ) Pub Date : 2020-12-01 , DOI: 10.1016/j.rse.2020.112034
Panpan Xu , Martin Herold , Nandin-Erdene Tsendbazar , Jan G.P.W. Clevers

Abstract 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.

中文翻译:

建立一个全面、一致的全球水生土地覆盖特征描述框架,以满足多个用户的需求

摘要 水生土地覆盖是指在一年的大部分时间里受水存在显着影响的土地覆盖类型。监测全球水生土地覆盖类型在保护水生生态系统和维持它们为人类提供的生态系统服务方面发挥着至关重要的作用,同时为多种目的(例如气候建模、生物多样性保护、水资源管理)进行准确和一致的监测具有挑战性的。尽管有许多全球水生土地覆盖 (GALC) 数据集可用于监测水生生态系统,但这些数据集之间存在显着差异,这主要是由于不同土地与水相关监测方法和表征方案之间的不一致造成的。由于水生土地覆盖在地球上以多种不同的形式存在(例如湿地、开阔水域)并且可以通过不同的方法进行绘制,因此有必要考虑一个更加一致和全面的表征框架,不仅可以确保水生土地监测的一致性土地覆盖,但也满足对水生土地不同方面感兴趣的多个用户(例如气候用户、农业用户)的需求。在本研究中,我们通过 1) 审查了 33 个 GALC 数据集和从当前数据集的引文以及与水生生态系统相关的国际公约、政策和协议中确定的用户需求,2) 提出了水生土地覆盖的全球特征描述框架基于土地覆盖分类系统 (LCCS) 分类原则和确定的用户需求,3) 强调遥感技术为实施拟议框架提供的机遇和挑战。结果表明,用户需要或更喜欢关于水生类型的各种信息,包括植被类型、水的持久性、人工覆盖(即人工与自然)、水盐度和海洋可达性(即沿海与内陆)。许多用户需要具有中高空间分辨率、年内动态和年际变化的数据集。然而,现有的数据集都不能满足所有这些要求,并且缺乏严格的定量准确性评估来评估大多数 GALC 数据集的质量。提议的框架具有三个级别,允许用户通过组合不同级别和分类信息来推导出他们感兴趣的水生土地覆盖类型。这个全面的制图框架有助于弥合用户需求与当前 GALC 数据集之间的差距,以及一般和水生土地覆盖监测之间的差距。该框架的实施可以受益于不断发展的卫星数据可用性、改进的计算能力和开源机器学习算法,但同时它面临的挑战主要来自水生生态系统的复杂性。本研究中提出的框架为未来可操作的水生土地覆盖监测举措提供了见解,并将支持更好地了解和监测复杂的水生生态系统。
更新日期:2020-12-01
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