在这项研究中,多传感器遥感数据集用于表征2018年10月24日登陆的威拉飓风淹没的土地利用和土地覆盖(LULC)。景观表征是使用无云Sentinel-2多光谱仪器(MSI)图像的无监督K均值算法完成的,在飓风威拉之前的旱季获得。在合成孔径雷达(SAR)Sentinel-1C波段上使用直方图阈值技术得出洪水图,并结合从Sentinel-2MSI图像得出的洪水图。两者,Sentinel-1和Sentinel-2图像是在Willa登陆后获得的。虽然LULC图达到了92%的准确率,使用实地调查期间收集的数据进行验证,洪水地图达到了90%的总体准确度,使用从社交网络数据中提取的位置进行验证,手动地理参考。农业类别是主要的土地利用(约2,624平方公里),其次是落叶林(1,591km2)和多年生亚森林(1,317km2)。约1,608平方公里代表永久湿地(红树林,盐沼,泻湖和河口,和沿海班),但该地区只有489平方公里属于水生表面(泻湖和河口)。洪水泛滥的面积为1,225平方公里,其中受影响最大的是农业(735平方公里)。我们的分析在LULC图中检测到盐沼类占据了541km2,飓风威拉期间,约328平方公里被洪水淹没。由于水流相对较快地消退,获得代表性图像来评估洪水事件是一个挑战。尽管如此,在这项研究中获得的高总体准确性使我们能够假设输出是可靠的,可以用于实施有效的保护策略,restoration,和湿地管理。此外,他们将提高地方政府和国家马里斯马什居民的能力,以做出明智的决定,保护脆弱地区免受气候变化带来的不同威胁。
In this study, multisensor remote sensing datasets were used to characterize the land use and land covers (LULC) flooded by Hurricane Willa which made landfall on October 24, 2018. The landscape characterization was done using an unsupervised K-means algorithm of a cloud-free Sentinel-2 MultiSpectral Instrument (MSI) image, acquired during the dry season before Hurricane Willa. A flood map was derived using the histogram thresholding technique over a Synthetic Aperture Radar (SAR) Sentinel-1 C-band and combined with a flood map derived from a Sentinel-2 MSI image. Both, the Sentinel-1 and Sentinel-2 images were obtained after Willa landfall. While the LULC map reached an accuracy of 92%, validated using data collected during field surveys, the flood map achieved 90% overall accuracy, validated using locations extracted from social network data, that were manually georeferenced. The agriculture class was the dominant land use (about 2,624 km2), followed by deciduous forest (1,591 km2) and sub-perennial forest (1,317 km2). About 1,608 km2 represents the permanent wetlands (mangrove, salt marsh, lagoon and estuaries, and littoral classes), but only 489 km2 of this area belongs to aquatic surfaces (lagoons and estuaries). The flooded area was 1,225 km2, with the agricultural class as the most impacted (735 km2). Our analysis detected the saltmarsh class occupied 541 km2in the LULC map, and around 328 km2 were flooded during Hurricane Willa. Since the water flow receded relatively quickly, obtaining representative imagery to assess the flood event was a challenge. Still, the high overall accuracies obtained in this study allow us to assume that the outputs are reliable and can be used in the implementation of effective strategies for the protection, restoration, and management of wetlands. In addition, they will improve the capacity of local governments and residents of Marismas Nacionales to make informed decisions for the protection of vulnerable areas to the different threats derived from climate change.