Automatic Inundation Mapping Using Sentinel-2 Data Applicable to Both Camargue and Doñana Biosphere Reserves

Georgios A Kordelas,Gaëtan Lefebvre,Ioannis Manakos,Brigitte Poulin

doi:10.3390/rs11192251

Abstract

Flooding periodicity is crucial for biomass production and ecosystem functions in wetland areas. Local monitoring networks may be enriched by spaceborne derived products with a temporal resolution of a few days. Unsupervised computer vision techniques are preferred, since human interference and the use of training data may be kept to a minimum. Recently, a novel automatic local thresholding unsupervised methodology for separating inundated areas from non-inundated ones led to successful results for the Doñana Biosphere Reserve. This study examines the applicability of this approach to Camarque Biosphere Reserve, and proposes alternatives to the original approach to enhance accuracy and applicability for both Camargue and Doñana wetlands in a scientific quest for methods that may serve accurately biomes at both protected areas. In particular, it examines alternative inputs for automatically estimating thresholds while applying various algorithms for estimating the splitting thresholds. Reference maps for Camargue are provided by local authorities, and generated using Sentinel-2 Band 8A (NIR) and Band 12 (SWIR-2). The alternative approaches examined led to high inundation mapping accuracy. In particular, for the Camargue study area and 39 different dates, the alternative approach with the highest overall Kappa coefficient is 0.84, while, for the Doñana Biosphere Reserve and Doñana marshland (a subset of Doñana Reserve) and 7 different dates, is 0.85 and 0.94, respectively. Moreover, there are alternative approaches with high overall Kappa for all areas, i.e., at 0.79 for Camargue, over 0.91 for Doñana marshland, and over 0.82 for Doñana Reserve. Additionally, this study identifies the alternative approaches that perform better when the study area is extensively covered by temporary flooded and emergent vegetation areas (i.e., Camargue Reserve and Doñana marshland) or when it contains a large percentage of dry areas (i.e., Doñana Reserve). The development of credible automatic thresholding techniques that can be applied to different wetlands could lead to a higher degree of automation for map production, while enhancing service utilization by non-trained personnel.

Highlights

Wetlands, which constitute unique habitats for many different plant and animal species, are important for their water-related ecosystem services, such as food provision, water filtration, and protection against soil erosion [1]
This study focuses on wetland areas and examines alternative approaches of the original automated local thresholding approach presented in Reference [23] with the objective to suggest alternative approaches, which may produce credible results for both Camargue and Doñana wetlands, i.e., Remote Sens. 2019, 11, 2251 be identified as possibly applicable to further wetland areas and biomes
This study examines automatic thresholding alternative approaches for separating inundated class pixels from non-inundated class pixels by utilizing atmospherically corrected S2 data

Summary

Introduction

Wetlands, which constitute unique habitats for many different plant and animal species, are important for their water-related ecosystem services, such as food provision, water filtration, and protection against soil erosion [1]. They provide important recreational and leisure activities, such as bird watching, fishing, and hiking [2]. Numerous approaches, utilizing optical or radar data for estimating water surface areas, have been proposed in the literature.

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Conclusion