Remote Sensing of Floodpath Lakes and Wetlands: A Challenging Frontier in the Monitoring of Changing Environments

Wang, Yeqiao

doi:10.3390/rs10121955

Cited by 34 publications

(21 citation statements)

References 153 publications

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“…These are important for water-related ecosystem services including water filtration, shoreline protection and food provision. Additionally, they are key habitats for wildlife including native and migratory water-bird species (Green, Bustamante, Janss, Fernández-Zamudio, & Díaz-Paniagua, 2016;Guo et al, 2017;Wang & Yésou, 2018). Wetlands are also popular destinations for recreational activities including hiking, fishing, bird watching and photography (Musamba, Boon, Ngaga, Giliba, & Dumulinyi, 2012;Park, Lee, & Peters, 2017).…”

Section: Introductionmentioning

confidence: 99%

Fusion of Sentinel-1 data with Sentinel-2 products to overcome non-favourable atmospheric conditions for the delineation of inundation maps

Manakos

Kordelas

Marini

2019

European Journal of Remote Sensing

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Sentinel-1 data are an alternative for monitoring flooded inland surfaces during cloudy periods. Supervised classification approaches with a single-trained model for the entire image demonstrate poor accuracy due to confusing backscatter conditions of the inundated areas in relation with the prevailing land cover features. This study follows instead a pixel-centric approach, which exploits the varying backscatter values of each pixel through a time series of Sentinel-1 images to train local Random Forest classification models per 3×3 pixels, and classifies each pixel in the target Sentinel-1 image, accordingly. Reference training data is retrieved from the timely close Sentinel-2-derived inundation maps. This study aims to identify the furthest mean day difference between the target Sentinel-1 image and available Sentinel-2 high accurate inundation maps (kappa coefficient-k > 0.9) that allows for the estimation of credible inundation maps for the Sentinel-1 target date. Various combinations of Sentinel-2 and Sentinel-1 training datasets are examined. The evaluation for eight target dates confirms that a Sentinel-1 inundation map with a k of 0.75 on average can be generated, when mean day difference is less than 30 days. The increment of the considered Sentinel-2 maps allows for the estimation of Sentinel-1 inundation maps with higher accuracy.

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Section: Introductionmentioning

confidence: 99%

Fusion of Sentinel-1 data with Sentinel-2 products to overcome non-favourable atmospheric conditions for the delineation of inundation maps

Manakos

Kordelas

Marini

2019

European Journal of Remote Sensing

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“…Despite significant progress in advanced methods of SAR imaging (TanDEM-X, Radarsat-2, COSMO SkyMed Second Generation, SAOCOM, ICEYE) and SAR data processing e.g. [22]- [24], this task still remains a challenging one [25], [26]. There are many reasons for this situation: multiple and > REPLACE THIS LINE WITH YOUR PAPER IDENTIFICATION NUMBER (DOUBLE-CLICK HERE TO EDIT) < 2 variable mechanisms of microwave scattering by the components of the complex wetland environment, SAR imaging parameters (wavelength, polarization, incidence angle) and last but not least the types of wetlands themselves [9], [27], [28].…”

Section: B Monitoring Of Wetlands With Remote Sensingmentioning

confidence: 99%

Riparian Wetland Mapping and Inundation Monitoring Using Amplitude and Bistatic Coherence Data From the TanDEM-X Mission

Mleczko

Mróz

Fitrzyk

2021

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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This paper focuses on bistatic coherence as an additional feature complementing amplitudes in classification space, permitting to monitor temporal changes in water extent on the wetland comprising surface water and inundated vegetation. The research was conducted on a herbaceous wetland. The TanDEM-X (TDX) images were acquired during the science phase: in bistatic mode with long perpendicular baselines. Two different sets of observations were computed: polarimetric amplitudes and interferometric coherences in single-pass mode. Next, the datasets composed of a multitemporal stack of images were classified using objectbased image analysis (OBIA). The main outcome of the experiment is that bistatic coherences increased greatly the overall accuracy of expected thematic classes. The overall accuracy (OA) shows that thematic categories were classified with higher accuracy when the bistatic coherence complemented polarimetric amplitudes. The OA is greater than 85% for all analyzed datatakes. The accuracy achieved using amplitudes only was higher than 70% but varied overtime. The bistatic coherence at X-band turned out to be really helpful in mapping high vegetation, which can be an indicator that this methodology can be directly used in the monitoring of common reed mowing or mapping highly invasive vegetation. Additionally, we could observe that short inundated vegetation was also mapped correctly, allowing flooded areas in this floodplain to be mapped with great precision throughout the growing season.

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“…As the amenity values of PAs attract the rapid developments and impacts of human-induced land use change, remote sensing has to meet an increasingly essential requirement to address a range of monitoring across spatial scales and from terrestrial to coastal and open waters [112,113]. Challenges and uncertainties remain for the data continuity and systematic technology improvements toward consistent long-term monitoring applications in the future [114].…”

Section: Challenges Of Remote Sensing Monitoring Of Protected Areasmentioning

confidence: 99%

Remote Sensing Applications in Monitoring of Protected Areas

et al. 2020

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Protected areas (PAs) have been established worldwide for achieving long-term goals in the conservation of nature with the associated ecosystem services and cultural values. Globally, 15% of the world’s terrestrial lands and inland waters, excluding Antarctica, are designated as PAs. About 4.12% of the global ocean and 10.2% of coastal and marine areas under national jurisdiction are set as marine protected areas (MPAs). Protected lands and waters serve as the fundamental building blocks of virtually all national and international conservation strategies, supported by governments and international institutions. Some of the PAs are the only places that contain undisturbed landscape, seascape and ecosystems on the planet Earth. With intensified impacts from climate and environmental change, PAs have become more important to serve as indicators of ecosystem status and functions. Earth’s remaining wilderness areas are becoming increasingly important buffers against changing conditions. The development of remote sensing platforms and sensors and the improvement in science and technology provide crucial support for the monitoring and management of PAs across the world. In this editorial paper, we reviewed research developments using state-of-the-art remote sensing technologies, discussed the challenges of remote sensing applications in the inventory, monitoring, management and governance of PAs and summarized the highlights of the articles published in this Special Issue.

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Remote Sensing of Floodpath Lakes and Wetlands: A Challenging Frontier in the Monitoring of Changing Environments

Cited by 34 publications

References 153 publications

Fusion of Sentinel-1 data with Sentinel-2 products to overcome non-favourable atmospheric conditions for the delineation of inundation maps

Fusion of Sentinel-1 data with Sentinel-2 products to overcome non-favourable atmospheric conditions for the delineation of inundation maps

Riparian Wetland Mapping and Inundation Monitoring Using Amplitude and Bistatic Coherence Data From the TanDEM-X Mission

Remote Sensing Applications in Monitoring of Protected Areas

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