Special Issue "Remote Sensing of Floodpath Lakes and Wetlands"

A special issue of Remote Sensing (ISSN 2072-4292).

Deadline for manuscript submissions: closed (31 October 2017).

Special Issue Editors

Dr. Yeqiao Wang
E-Mail Website
Guest Editor
Department of Natural Resources Science, University of Rhode Island, 1 Greenhouse Road, Kingston, RI 02881, USA
Tel. +1 401-874-4345
Interests: Terrestrial remote sensing, protected areas; coastal environments; wetlands; inventory and monitoring of ecological conditions; land use and land cover change; biodiversity conservation; mountainous regions; decision support
Special Issues and Collections in MDPI journals
Dr. Herve Yesou
E-Mail Website
Guest Editor
ICube – SERTIT, Université de Strasbourg, Institut Telecom Physiques Strasbourg, Parc d'Innovation, 300, Bd Sébastien Brant, BP 10413, F - 67412 Illkirch Graffenstaden, France
Tel. +33 (0)3 68 85 46 43; Fax: +33 (0)3 68 85 46 46
Interests: water body monitoring; water path; wetlands; biodiversity; ecological stakes; SAR; optical; time series analysis

Special Issue Information

Dear Colleagues,

Floodpath lakes and wetlands, which are affected by seasonal variations of water level and surface area are sensative to natural and anthropohenic impacts, such as climate change, human-induced intervantions on hydrological regimes, and land use management and land cover change. For example, Poyang Lake and Dongting Lake in the middle and lower reaches of the Yangtze River, are among the most representative floodpath lakes with dramatic spatial and temporal variation patterns in water and wetland dynamics. These large dynamic wetlands, such as Poyang Lake wetland, are recognized to be ones of the most important wetlands of the world for its extroordinary biodiversity and conservation challenges. Remote sensing has the unique capabilities and advantages in monitoring hydrological dynamics of floodpath lakes and wetlands in scientific explorations and management practices.

With the rapid development of remote sensing science and technologies, this Special Issue aims to publish original manuscripts of latest innovative research in recent advances in remote sensing of floodpath lakes and wetlands. Comprehensive reviews of this research field are also welcome. The potential topics include, but are not limited to:

  • State-of-the-art remote sensing technologies for capturing dynamics of floodpath lakes and wetlands
  • Evaluations of newly available and/or new development of remote sensing approaches for studying floodpath lakes and wetlands
  • Methods for processing multispatial, multitemporal, multisensor remote sensing data in monitoring of floodpath lakes and wetlands (e.g., integration of multisource geospatial data from in situ monitoring and measurements, UAV observations, satellite imagery, habitat assessments, social economic development and policy factors, etc.)
  • Applications of remote sensing in inventory, monitoring and management of floodpath lakes and wetlands (e.g., habitat mapping and biodiversity conservation, impacts from human activities, detection of extreme hydrological events, and environmental and ecological impact analysis)

Authors are required to check and follow the specific Instructions to Authors, https://www.mdpi.com/journal/remotesensing/instructions

Dr. Yeqiao Wang
Dr. Herve Yesou
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Floodpath lakes
  • Floodpath wetlands
  • Hydrological dynamics
  • Global Water Indices
  • Optical models
  • New sensor applications
  • Simulation modeling
  • Human activities
  • Socio-economic indicators

Published Papers (9 papers)

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Editorial

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Open AccessEditorial
Remote Sensing of Floodpath Lakes and Wetlands: A Challenging Frontier in the Monitoring of Changing Environments
Remote Sens. 2018, 10(12), 1955; https://doi.org/10.3390/rs10121955 - 05 Dec 2018
Cited by 3
Abstract
Monitoring of changing lake and wetland environments has long been among the primary focus of scientific investigation, technology innovation, management practice, and decision-making analysis. Floodpath lakes and wetlands are the lakes and associated wetlands affected by seasonal variations of water level and water [...] Read more.
Monitoring of changing lake and wetland environments has long been among the primary focus of scientific investigation, technology innovation, management practice, and decision-making analysis. Floodpath lakes and wetlands are the lakes and associated wetlands affected by seasonal variations of water level and water surface area. Floodpath lakes and wetlands are, in particular, sensitive to natural and anthropogenic impacts, such as climate change, human-induced intervention on hydrological regimes, and land use and land cover change. Rapid developments of remote sensing science and technologies, provide immense opportunities and capacities to improve our understanding of the changing lake and wetland environments. This special issue on Remote Sensing of Floodpath Lakes and Wetlands comprise featured articles reporting the latest innovative research and reflects the advancement in remote sensing applications on the theme topic. In this editorial paper, we review research developments using state-of-the-art remote sensing technologies for monitoring dynamics of floodpath lakes and wetlands; discuss challenges of remote sensing in inventory, monitoring, management, and governance of floodpath lakes and wetlands; and summarize the highlights of the articles published in this special issue. Full article
(This article belongs to the Special Issue Remote Sensing of Floodpath Lakes and Wetlands)

Research

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Open AccessArticle
Wetland Mapping Using SAR Data from the Sentinel-1A and TanDEM-X Missions: A Comparative Study in the Biebrza Floodplain (Poland)
Remote Sens. 2018, 10(1), 78; https://doi.org/10.3390/rs10010078 - 09 Jan 2018
Cited by 8
Abstract
This research is related to the eco-hydrological problems of the herbaceous wetland drying and biodiversity loss in the floodplain lakes of the Middle Basin of the Biebrza River (Poland). An experiment was set up, with its main goals as follows: (i) mapping the [...] Read more.
This research is related to the eco-hydrological problems of the herbaceous wetland drying and biodiversity loss in the floodplain lakes of the Middle Basin of the Biebrza River (Poland). An experiment was set up, with its main goals as follows: (i) mapping the vegetation types and the temporarily or permanently flooded areas, and (ii) comparing the usefulness of the C-band Sentinel-1A (S1A) and X-band TerraSAR-X/TanDEM-X (TSX/TDX) for mapping purposes. The S1A imagery was acquired on a regular basis using the dual polarization VV/VH and the Interferometric Wide Swath Mode. The TSX/TDX data were acquired in quad-pol, a fully polarimetric mode, during the Science Phase. The paper addresses the following aspects: (i) wetland mapping with the S1A multi-temporal series; (ii) wetland mapping with the fully polarimetric TSX/TDX data; (iii) comparing the wetland mapping using dual polarization TSX/TDX subsets, that is, the HH-HV, HH-VV and VV-VH; (iv) comparing wetland mapping using the S1A and TSX/TDX data based on the same polarization (VV-VH); (v) studying the suitability of the Shannon Entropy for wetland mapping; and (vi) assessing the contribution of interferometric coherence for wetland classification. Though the experimental results show the main limitations of the S1A dataset, they also highlight the good accuracy that can be achieved using the TSX/TDX data, especially those taken in fully polarimetric mode. Some practical outcomes significant for the study area management using SAR were also described. Full article
(This article belongs to the Special Issue Remote Sensing of Floodpath Lakes and Wetlands)
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Open AccessArticle
LakeTime: Automated Seasonal Scene Selection for Global Lake Mapping Using Landsat ETM+ and OLI
Remote Sens. 2018, 10(1), 54; https://doi.org/10.3390/rs10010054 - 31 Dec 2017
Cited by 6
Abstract
The Landsat series of satellites provide a nearly continuous, high resolution data record of the Earth surface from the early 1970s through to the present. The public release of the entire Landsat archive, free of charge, along with modern computing capacity, has enabled [...] Read more.
The Landsat series of satellites provide a nearly continuous, high resolution data record of the Earth surface from the early 1970s through to the present. The public release of the entire Landsat archive, free of charge, along with modern computing capacity, has enabled Earth monitoring at the global scale with high spatial resolution. With the large data volume and seasonality varying across the globe, image selection is a particularly important challenge for regional and global multitemporal studies to remove the interference of seasonality from long term trends. This paper presents an automated method for selecting images for global scale lake mapping to minimize the influence of seasonality, while maintaining long term trends in lake surface area dynamics. Using historical meteorological data and a simple water balance model, we define the most stable period after the rainy season, when inflows equal outflows, independently for each Landsat tile and select images acquired during that ideal period for lake surface area mapping. The images selected using this method provide nearly complete global area coverage at decadal episodes for circa 2000 and circa 2014 from Landsat Enhanced Thematic Mapper Plus (ETM+) and Operational Land Imager (OLI) sensors, respectively. This method is being used in regional and global lake dynamics mapping projects, and is potentially applicable to any regional/global scale remote sensing application. Full article
(This article belongs to the Special Issue Remote Sensing of Floodpath Lakes and Wetlands)
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Open AccessFeature PaperArticle
Comparing Pixel- and Object-Based Approaches in Effectively Classifying Wetland-Dominated Landscapes
Remote Sens. 2018, 10(1), 46; https://doi.org/10.3390/rs10010046 - 28 Dec 2017
Cited by 9
Abstract
Wetland ecosystems straddle both terrestrial and aquatic habitats, performing many ecological functions directly and indirectly benefitting humans. However, global wetland losses are substantial. Satellite remote sensing and classification informs wise wetland management and monitoring. Both pixel- and object-based classification approaches using parametric and [...] Read more.
Wetland ecosystems straddle both terrestrial and aquatic habitats, performing many ecological functions directly and indirectly benefitting humans. However, global wetland losses are substantial. Satellite remote sensing and classification informs wise wetland management and monitoring. Both pixel- and object-based classification approaches using parametric and non-parametric algorithms may be effectively used in describing wetland structure and habitat, but which approach should one select? We conducted both pixel- and object-based image analyses (OBIA) using parametric (Iterative Self-Organizing Data Analysis Technique, ISODATA, and maximum likelihood, ML) and non-parametric (random forest, RF) approaches in the Barguzin Valley, a large wetland (~500 km2) in the Lake Baikal, Russia, drainage basin. Four Quickbird multispectral bands plus various spatial and spectral metrics (e.g., texture, Non-Differentiated Vegetation Index, slope, aspect, etc.) were analyzed using field-based regions of interest sampled to characterize an initial 18 ISODATA-based classes. Parsimoniously using a three-layer stack (Quickbird band 3, water ratio index (WRI), and mean texture) in the analyses resulted in the highest accuracy, 87.9% with pixel-based RF, followed by OBIA RF (segmentation scale 5, 84.6% overall accuracy), followed by pixel-based ML (83.9% overall accuracy). Increasing the predictors from three to five by adding Quickbird bands 2 and 4 decreased the pixel-based overall accuracy while increasing the OBIA RF accuracy to 90.4%. However, McNemar’s chi-square test confirmed no statistically significant difference in overall accuracy among the classifiers (pixel-based ML, RF, or object-based RF) for either the three- or five-layer analyses. Although potentially useful in some circumstances, the OBIA approach requires substantial resources and user input (such as segmentation scale selection—which was found to substantially affect overall accuracy). Hence, we conclude that pixel-based RF approaches are likely satisfactory for classifying wetland-dominated landscapes. Full article
(This article belongs to the Special Issue Remote Sensing of Floodpath Lakes and Wetlands)
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Open AccessArticle
Remote Sensing of Hydrological Changes in Tian-e-Zhou Oxbow Lake, an Ungauged Area of the Yangtze River Basin
Remote Sens. 2018, 10(1), 27; https://doi.org/10.3390/rs10010027 - 25 Dec 2017
Cited by 3
Abstract
The hydrological pattern changes have a great influence on the wetland environment. However, some important wetland areas often lack historical observations due to economic and physical conditions. The Tian-e-Zhou oxbow lake wetland is an important habitat for two endangered species and also has [...] Read more.
The hydrological pattern changes have a great influence on the wetland environment. However, some important wetland areas often lack historical observations due to economic and physical conditions. The Tian-e-Zhou oxbow lake wetland is an important habitat for two endangered species and also has very little historical hydrological data. Remote sensing images can be used to explore the historical water area fluctuation of lakes. In addition, remote sensing can also be used to obtain historical water levels based on the water boundary elevation integrated with a topographic data (WBET) method or the level-surface area relationship curve (LRC) method. In order to minimize the uncertainty of the derived results, both methods were introduced in the extraction of the water level of Tian-e-Zhou during 1992–2015. The results reveal that the hydrological regime of the oxbow lake has experienced a significant change after the Shatanzi Levee construction in 1998. With the impact of the levee, the mean annual water surface area of the lake was reduced by 5.8 km2 during the flood season, but, during the non-flood season, it was increased by 1.35 km2. For the same period, the water level of the lake during the flood season also showed a 1.47 m (WBET method) or 3.21 m (LRC method) decrease. The mean annual water level increased by 1.12 m (WBET method) or 0.75 m (LRC method). Both results had a good accuracy with RMSE (root-mean-square errors) of less than 0.4 m. Furthermore, the water level differences between the Yangtze River channel and the oxbow lake increased by at least 0.5 m. It is found that the hydrological pattern of the oxbow lake changed significantly after the levee construction, which could bring some disadvantages to the habitats of the two endangered species. Full article
(This article belongs to the Special Issue Remote Sensing of Floodpath Lakes and Wetlands)
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Open AccessArticle
Determination of the Downwelling Diffuse Attenuation Coefficient of Lake Water with the Sentinel-3A OLCI
Remote Sens. 2017, 9(12), 1246; https://doi.org/10.3390/rs9121246 - 01 Dec 2017
Cited by 14
Abstract
The Ocean and Land Color Imager (OLCI) on the Sentinel-3A satellite, which was launched by the European Space Agency in 2016, is a new-generation water color sensor with a spatial resolution of 300 m and 21 bands in the range of 400–1020 nm. [...] Read more.
The Ocean and Land Color Imager (OLCI) on the Sentinel-3A satellite, which was launched by the European Space Agency in 2016, is a new-generation water color sensor with a spatial resolution of 300 m and 21 bands in the range of 400–1020 nm. The OLCI is important to the expansion of remote sensing monitoring of inland waters using water color satellite data. In this study, we developed a dual band ratio algorithm for the downwelling diffuse attenuation coefficient at 490 nm (Kd(490)) for the waters of Lake Taihu, a large shallow lake in China, based on data measured during seven surveys conducted between 2008 and 2017 in combination with Sentinel-3A-OLCI data. The results show that: (1) Compared to the available Kd(490) estimation algorithms, the dual band ratio (681 nm/560 nm and 754 nm/560 nm) algorithm developed in this study had a higher estimation accuracy (N = 26, coefficient of determination (R2) = 0.81, root-mean-square error (RMSE) = 0.99 m−1 and mean absolute percentage error (MAPE) = 19.55%) and validation accuracy (N = 14, R2 = 0.83, RMSE = 1.06 m−1 and MAPE = 27.30%), making it more suitable for turbid inland waters; (2) A comparison of the OLCI Kd(490) product and a similar Moderate Resolution Imaging Spectroradiometer (MODIS) product reveals a high consistency between the OLCI and MODIS products in terms of the spatial distribution of Kd(490). However, the OLCI product has a smoother spatial distribution and finer textural characteristics than the MODIS product and contains notably higher-quality data; (3) The Kd(490) values for Lake Taihu exhibit notable spatial and temporal variations. Kd(490) is higher in seasons with relatively high wind speeds and in open waters that are prone to wind- and wave-induced sediment resuspension. Finally, the Sentinel-3A-OLCI has a higher spatial resolution and is equipped with a relatively wide dynamic range of spectral bands suitable for inland waters. The Sentinel-3B satellite will be launched soon and, together with the Sentinel-3A satellite, will form a two-satellite network with the ability to make observations twice every three days. This satellite network will have a wider range of application and play an important role in the monitoring of inland waters with complex optical properties. Full article
(This article belongs to the Special Issue Remote Sensing of Floodpath Lakes and Wetlands)
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Open AccessArticle
Investigation of Water Temperature Variations and Sensitivities in a Large Floodplain Lake System (Poyang Lake, China) Using a Hydrodynamic Model
Remote Sens. 2017, 9(12), 1231; https://doi.org/10.3390/rs9121231 - 28 Nov 2017
Cited by 7
Abstract
Although changes in water temperature influence the rates of many ecosystem processes in lakes, knowledge of the water temperature regime for large floodplain lake systems subjected to multiple stressors has received little attention. The coupled models can serve to derive more knowledge on [...] Read more.
Although changes in water temperature influence the rates of many ecosystem processes in lakes, knowledge of the water temperature regime for large floodplain lake systems subjected to multiple stressors has received little attention. The coupled models can serve to derive more knowledge on the water temperature impact on lake ecosystems. For this purpose, we used a physically-based hydrodynamic model coupled with a transport model to examine the spatial and temporal behavior and primary causal factors of water temperature within the floodplain of Poyang Lake that is representative of shallow and large lakes in China. Model performance is assessed through comparison with field observations and remote sensing data. The daily water temperature variations within Poyang Lake were reproduced reasonably well by the hydrodynamic model, with the root mean square errors of 1.5–1.9 °C. The modeling results indicate that the water temperature exhibits distinct spatial and temporal variability. The mean seasonal water temperatures vary substantially from 29.1 °C in summer to 7.7 °C in winter, with the highest value in August and the lowest value in January. Although the degree of spatial variability differed considerably between seasons, the water temperature generally decreases from the shallow floodplains to the main flow channels of the lake. As expected, the lake water temperature is primarily affected by the air temperature, solar radiation, wind speed and the inflow temperature, whereas other factors such as cloud cover, relative humidity, precipitation, evaporation and lake topography may play a complementary role in influencing temperature. The current work presents a first attempt to use a coupled model approach, which is therefore a useful tool to investigate the water temperature behavior and its major causal factors for a large floodplain lake system. It would have implications for improving the understanding of Poyang Lake water temperature and supporting planning and management of the lake, its water quality and ecosystem functioning. Full article
(This article belongs to the Special Issue Remote Sensing of Floodpath Lakes and Wetlands)
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Open AccessArticle
Application of Landsat Imagery to Investigate Lake Area Variations and Relict Gull Habitat in Hongjian Lake, Ordos Plateau, China
Remote Sens. 2017, 9(10), 1019; https://doi.org/10.3390/rs9101019 - 30 Sep 2017
Cited by 3
Abstract
Lakes in arid and semi-arid regions have an irreplaceable and important role in the local environment and wildlife habitat protection. Relict Gull (Larus relictus), which is listed as a “vulnerable” bird species in the IUCN Red List, uses only islands in lakes for [...] Read more.
Lakes in arid and semi-arid regions have an irreplaceable and important role in the local environment and wildlife habitat protection. Relict Gull (Larus relictus), which is listed as a “vulnerable” bird species in the IUCN Red List, uses only islands in lakes for habitat. The habitat with the largest colonies in Hongjian Lake (HL), which is located in Shaanxi Province in China, has been severely threatened by persistent lake shrinkage, yet the variations in the area of the lake and the islands are poorly understood due to a lack of in situ observations. In this study, using the Modified Normalized Difference Water Index, 336 Landsat remote sensing images from 1988–2015 were used to extract the monthly HL water area and lake island area, and the driving factors were investigated by correlation analysis. The results show that the lake area during 1988–2015 exhibited large fluctuations and an overall downward trend of −0.94 km2/year, and that the lake area ranged from 55.02 km2 in 1997 to 30.90 km2 in 2015. The cumulative anomaly analysis diagnosed the lake variations as two sub-periods with different characteristics and leading driving factors. The average and change trend were 52.88 and 0.21 km2/year during 1988–1998 and 38.85 and −1.04 km2/year during 1999–2015, respectively. During 1988–1998, the relatively high precipitation, low evapotranspiration, and low levels of human activity resulted in a weak increase in the area of HL. However, in 1999–2015, the more severe human activity as well as climate warming resulted in a fast decrease in the area of HL. The variations in lake island area were dependent on the area of HL, which ranged from 0.02 km2 to 0.22 km2. As the lake size declined, the islands successively outcropped in the form of the four island zones, and the two zones located in Northwest and South of HL were the most important habitats for Relict Gull. The formation of these island zones can provide enough space for Relict Gull breeding. Full article
(This article belongs to the Special Issue Remote Sensing of Floodpath Lakes and Wetlands)
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Open AccessArticle
Application of Sentinel 2 MSI Images to Retrieve Suspended Particulate Matter Concentrations in Poyang Lake
Remote Sens. 2017, 9(7), 761; https://doi.org/10.3390/rs9070761 - 23 Jul 2017
Cited by 22
Abstract
Suspended particulate matter (SPM) is one of the dominant water constituents in inland and coastal waters, and SPM concnetration (CSPM) is a key parameter describing water quality. This study, using in-situ spectral and CSPM measurements as well as Sentinel [...] Read more.
Suspended particulate matter (SPM) is one of the dominant water constituents in inland and coastal waters, and SPM concnetration (CSPM) is a key parameter describing water quality. This study, using in-situ spectral and CSPM measurements as well as Sentinel 2 Multispectral Imager (MSI) images, aimed to develop CSPM retrieval models and further to estimate the CSPM values of Poyang Lake, China. Sixty-eight in-situ hyperspectral measurements and relative spectral response function were applied to simulate Sentinel 2 MIS spectra. Thirty-four samples were used to calibrate and the left samples were used to validate CSPM retrieval models, respectively. The developed models were then applied to two Sentinel 2 MSI images captured in wet and dry seasons, and the derived CSPM values were compared with those derived from MODIS B1 (λ = 645 nm). Results showed that the Sentinel 2 MSI B4–B8b models achieved acceptable to high fitting accuracies, which explained 81–93% of the variation of CSPM. The validation results also showed the reliability of these six models, and the estimated CSPM explained 77–93% of the variation of measured CSPM with the mean absolute percentage error (MAPE) ranging from 36.87% to 21.54%. Among those, a model based on B7 (λ = 783 nm) appeared to be the most accurate one. The Sentinel 2 MSI-derived CSPM values were generally consistent in spatial distribution and magnitude with those derived from MODIS. The CSPM derived from Sentinel 2 MSI B7 showed the highest consistency with MODIS on 15 August 2016, while the Sentinel 2 MSI B4 (λ = 665 nm) produced the highest consistency with MODIS on 2 April 2017. Overall, this study demonstrated the applicability of Sentinel 2 MSI for CSPM retrieval in Poyang Lake, and the Sentinel 2 MSI B4 and B7 are recommended for low and high loadings of SPM, respectively. Full article
(This article belongs to the Special Issue Remote Sensing of Floodpath Lakes and Wetlands)
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