Global Wetland Datasets: a Review

Hu, Shengjie; Niu, Zhenguo; Chen, Yanfen

doi:10.1007/s13157-017-0927-z

Cited by 83 publications

(71 citation statements)

References 49 publications

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“…Consequently, these techniques now allow for spatial detection of wetland habitat over time at the (inter-) annual and the climate-scale and thus complement estimates from theoretical modeling and empirical, site-specific studies [21][22][23][24]. Nevertheless, thematic mapping of wetlands are also often static in time, at coarse spatial resolution or performed on a local scale [25].…”

Section: Introductionmentioning

confidence: 99%

“…Reviews of remote sensing techniques for the identification of wetland vegetation mention many studies, which use multi-spectral data to perform supervised and unsupervised image classification in order to detect wetlands and wetland vegetation [25,26]. Some studies showed a successful use of supervised classification to monitor wetland evolution [22][23][24].…”

Section: Introductionmentioning

confidence: 99%

“…The use of unsupervised decision tree (DT) classification procedures is a step towards automated land cover classification. DT classification implies several advantages as it is a simple, objective, flexible, computationally fast approach, which provides the opportunity to integrate data on different measurement scales [25,26,34,35]. In particular, for the classification of coastal areas, the ability to integrate additional data helps to improve their accurate detection [25,26].…”

Section: Introductionmentioning

confidence: 99%

“…DT classification implies several advantages as it is a simple, objective, flexible, computationally fast approach, which provides the opportunity to integrate data on different measurement scales [25,26,34,35]. In particular, for the classification of coastal areas, the ability to integrate additional data helps to improve their accurate detection [25,26]. Liu et al (2008) [28] applied a DT classification procedure combined with local tidal information to monitor mangrove forest changes.…”

Section: Introductionmentioning

confidence: 99%

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Trends in the Seaward Extent of Saltmarshes across Europe from Long-Term Satellite Data

2019

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Saltmarshes provide crucial functions for flora, fauna, and humankind. Thus far, studies of their dynamics and response to environmental drivers are limited in space and time. Satellite data allow for looking at saltmarshes on a large scale and over a long time period. We developed an unsupervised decision tree classification method to classify satellite images into saltmarsh vegetation, mudflat and open water, integrating additional land cover information. By using consecutive stacks of three years, we considered trends while taking into account water level variations. We used Landsat 5 TM data but found that other satellite data can be used as well. Classification performance for different periods of the Western Scheldt was almost perfect for this site, with overall accuracies above 90% and Kappa coefficients of over 0.85. Sensitivity analysis characterizes the method as being robust. Generated time series for 125 sites across Europe show saltmarsh area changes between 1986 and 2010. The method also worked using a global approach for these sites. We reveal transitions between saltmarsh, mudflat and open water, both at the saltmarsh lower edge and interior, but our method cannot detect changes at the saltmarsh-upland boundary. Resulting trends in saltmarsh dynamics can be coupled to environmental drivers, such as sea level, tidal currents, waves, and sediment availability.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Trends in the Seaward Extent of Saltmarshes across Europe from Long-Term Satellite Data

2019

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“…Wetland reclamation is one of land use changes that have important impacts on the climate system. Since the twentieth century, more than 50% of wetlands in parts of North America, Europe, Australia, and New Zealand have been degraded or lost due to climate change or anthropogenic disturbance (Hu et al, 2017), which have affected climate systems with extensive and intensive influence at different scales. At the global scale, wetland drainage may exert influence on global climate through changes of CO 2 and CH 4 emissions (Chen & Tian, 2007;Erwin, 2009;Pielke et al, 2011;Rojstaczer & Deverel, 2013;Schneider & Eugster, 2007;Song et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

Impacts of Wetland Reclamation and Paddy Field Expansion on Observed Local Temperature Trends in the Sanjiang Plain of China

Liu

Zhang

2019

JGR Earth Surface

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The warming or cooling effects on regional climate in response to early land use change may be strengthened, weakened, or eliminated by the same or opposite effect in the subsequent land use/management period. Taking the Sanjiang Plain in China as our study area, this paper analyzed the surface temperature change due to land use/land management changes from the mid‐1950s to 2015, based on the land surface temperature response model and the observation minus reanalysis (OMR) method using remote sensing data, meteorological observation data, and reanalysis data. Results revealed a magnitude of monthly mean land surface warming up to 1.31 °C due to the land use change from wetland to rain‐fed farmland and a cooling effect of −1.32 °C caused by the land management change from rain‐fed farmland to paddy fields during the growing season. The trends were confirmed using OMR method. Land surface temperature change based on remote sensing data was divided into radiative and nonradiative forcing. The nonradiative processes play a dominant role in regulating the local surface temperature. The monthly mean temperature differences in response to land use changes differ greatly during the growing season. The temperature difference was greater in May and June (spring) than in July and August (summer). Our study shows that the land use impact on regional climate could be switched dramatically, and it would be basically consistent with the impact of natural wetlands before reclamation in our study area right now, which provides important information for mitigating and adapting to global climate change at regional scale.

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