Towards a comprehensive and consistent global aquatic land cover characterization framework addressing multiple user needs

Xu, Panpan; Herold, Martin; Tsendbazar, Nandin‐Erdene; Clevers, J.G.P.W.

doi:10.1016/j.rse.2020.112034

Cited by 18 publications

(11 citation statements)

References 121 publications

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“…According to the review of currently available GALC datasets by Xu et al [6], users prefer datasets with ≤100 m resolution, thus, the spatial resolution of the prototype GALC database was set to 100 m. The nominal year of the static prototype database was chosen as 2015 because more global products describing GALC are available around 2015 compared with other years [6]. General steps taken in this study are summarized in Figure 1.…”

Section: Methodsmentioning

confidence: 99%

“…The prototype GALC database was built upon the LCCS-based GALC characterization framework proposed by Xu et al [6] (Figure 2). Level-1 identifies aquatic land cover as a whole, representing the discrimination of aquatic and non-aquatic lands.…”

Section: Global Aquatic Land Cover Characterization Frameworkmentioning

confidence: 99%

“…Remote sensing provides an efficient way to monitor the spatial distribution of aquatic land. As there is a lack of uniform and comprehensive aquatic land cover classification schemes, current Global Aquatic Land Cover (GALC) datasets have often been narrowed down to specific classes [4], most of which focus on providing the information of water bodies [5,6] while missing the vegetation and wet soils that are key components of aquatic ecosystems [2]. Currently, the most comprehensive GALC product that describes a variety of aquatic classes is the Global Lakes and Wetlands Database (GLWD) [7].…”

Section: Introductionmentioning

confidence: 99%

“…Depending on the application, GALC map users may require aquatic information at different levels of detail. GALC datasets are most commonly applied to define the region of interest using the general distribution of aquatic land cover [6]. In some other cases, more detailed information on aquatic lands is needed.…”

Section: Introductionmentioning

confidence: 99%

“…The ISO-certified United Nations Land Cover Classification System (LCCS) offers a good way to standardize the terminology of a land cover type by combining a set of independent diagnostic attributes, i.e., classifiers [14]. Built upon the LCCS approach, a three-level GALC characterization framework was developed recently [6] which identifies aquatic land cover from general to detailed levels. By organizing the information on a level and classifier basis, this framework not only reflects the complexity of aquatic ecosystems but also allows users to derive the information for their own applications.…”

Section: Introductionmentioning

confidence: 99%

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Assessing a Prototype Database for Comprehensive Global Aquatic Land Cover Mapping

Tsendbazar

Herold

et al. 2021

Remote Sensing

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The monitoring of Global Aquatic Land Cover (GALC) plays an essential role in protecting and restoring water-related ecosystems. Although many GALC datasets have been created before, a uniform and comprehensive GALC dataset is lacking to meet multiple user needs. This study aims to assess the effectiveness of using existing global datasets to develop a comprehensive and user-oriented GALC database and identify the gaps of current datasets in GALC mapping. Eight global datasets were reframed to construct a three-level (i.e., from general to detailed) prototype database for 2015, conforming with the United Nations Land Cover Classification System (LCCS)-based GALC characterization framework. An independent validation was done, and the overall results show some limitations of current datasets in comprehensive GALC mapping. The Level-1 map had considerable commission errors in delineating the general GALC distribution. The Level-2 maps were good at characterizing permanently flooded areas and natural aquatic types, while accuracies were poor in the mapping of temporarily flooded and waterlogged areas as well as artificial aquatic types; vegetated aquatic areas were also underestimated. The Level-3 maps were not sufficient in characterizing the detailed life form types (e.g., trees, shrubs) for aquatic land cover. However, the prototype GALC database is flexible to derive user-specific maps and has important values to aquatic ecosystem management. With the evolving earth observation opportunities, limitations in the current GALC characterization can be addressed in the future.

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Section: Methodsmentioning

confidence: 99%

Section: Global Aquatic Land Cover Characterization Frameworkmentioning

confidence: 99%