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Open AccessArticle

Introducing WIW for Detecting the Presence of Water in Wetlands with Landsat and Sentinel Satellites

1
Tour du Valat Research Institute, Le Sambuc, 13200 Arles, France
2
CNRS UMR LETG-Angers, University of Angers, LETG Angers-LEESA, UMR CNRS 6554, 2 Boulevard Lavoisier, 49045 Angers CEDEX, France
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(19), 2210; https://doi.org/10.3390/rs11192210
Received: 9 August 2019 / Revised: 15 September 2019 / Accepted: 20 September 2019 / Published: 21 September 2019
(This article belongs to the Section Environmental Remote Sensing)
Many wetlands are characterized by a vegetation cover of variable height and density over time. Tracking spatio-temporal changes in inundation patterns of these wetlands remains a challenge for remote sensing. Water In Wetlands (WIW) was predicted using a dichotomous partitioning of reflectance values encoded based on ground-truth (n = 4038) and optical-space derived (n = 7016) data covering all land cover types (n = 17) found in the Rhône delta, southern France. The models were developed with spectral data from Sentinel 2, Landsat 7, and Landsat 8 sensors, hence providing a monitoring tool that covers a 35-year period (same sensor for Landsat 5 and 7). A single model combining the near infrared (NIR ≤ 0.1558 to 0.1804, depending on sensors) and short-wave infrared (SWIR2 ≤ 0.0871 to 0.1131) wavelengths was identified by three independent analyses, each one using a different satellite. Overall accuracy of water maps ranged from 89% to 94% for the training samples and from 90% to 94% for the validation samples, encompassing standard water indices that systematically underestimate flooding duration under vegetation cover. Sentinel 2 provided the highest performance with a kappa coefficient of 0.82 for both samples. Such tool will be most useful for monitoring the water dynamics of seasonal wetlands, which are particularly sensitive to climate change while providing multiple services to humankind. Considering the high temporal resolution of Sentinel 2 (every 5 days), cumulative water maps built with the WIW logical rule could further be used for mapping a wide range of wetlands which are either periodically or permanently flooded. View Full-Text
Keywords: dichotomous partitioning; wetland hydrology; remote sensing; satellite data; water detection dichotomous partitioning; wetland hydrology; remote sensing; satellite data; water detection
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MDPI and ACS Style

Lefebvre, G.; Davranche, A.; Willm, L.; Campagna, J.; Redmond, L.; Merle, C.; Guelmami, A.; Poulin, B. Introducing WIW for Detecting the Presence of Water in Wetlands with Landsat and Sentinel Satellites. Remote Sens. 2019, 11, 2210.

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