{"title":"Preliminary Analysis For Automatic Tidal Inlets Mapping Using Google Earth Engine","authors":"J. Sartori, J. B. Sbruzzi, E. L. Fonseca","doi":"10.1109/LAGIRS48042.2020.9165650","DOIUrl":null,"url":null,"abstract":"This work aims to define the basic parameters for the automatic mapping of the channel between the Lagoa do Peixe and the Atlantic Ocean, which is located in the municipalities of Tavares and Mostardas, Rio Grande do Sul state, Brazil. The automatic mapping is based on an unsupervised classification of Landsat 8 satellite images at the Google Earth Engine cloud computing platform. The images used were selected to present both channel situations (opened and closed). Three images were selected with acquisition dates that presented the open channel and three that presented the closed channel. Each image was classified using the K-means clustering method, using separately band 6, band 7 (both located at shortwave infrared - SWIR) and the Normalized Difference Water Index (NDWI). Once the number of clusters must be defined a priori by the analyst, as well as the training sample area, these parameters were tested over the dataset and clustering results were compared. All of the generated clusters maps were analyzed over 10 random points, identifying the clustering hits and errors. Due to the absence of reference maps, all the final clustering maps for each date were compared with the composite true color image from the same acquisition date. The NDWI cluster maps showed the best results in separating water and non-water pixels.","PeriodicalId":111863,"journal":{"name":"2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/LAGIRS48042.2020.9165650","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This work aims to define the basic parameters for the automatic mapping of the channel between the Lagoa do Peixe and the Atlantic Ocean, which is located in the municipalities of Tavares and Mostardas, Rio Grande do Sul state, Brazil. The automatic mapping is based on an unsupervised classification of Landsat 8 satellite images at the Google Earth Engine cloud computing platform. The images used were selected to present both channel situations (opened and closed). Three images were selected with acquisition dates that presented the open channel and three that presented the closed channel. Each image was classified using the K-means clustering method, using separately band 6, band 7 (both located at shortwave infrared - SWIR) and the Normalized Difference Water Index (NDWI). Once the number of clusters must be defined a priori by the analyst, as well as the training sample area, these parameters were tested over the dataset and clustering results were compared. All of the generated clusters maps were analyzed over 10 random points, identifying the clustering hits and errors. Due to the absence of reference maps, all the final clustering maps for each date were compared with the composite true color image from the same acquisition date. The NDWI cluster maps showed the best results in separating water and non-water pixels.
这项工作旨在为位于巴西南里奥格兰德州塔瓦雷斯和莫斯塔达斯市的Lagoa do Peixe和大西洋之间的通道自动测绘定义基本参数。自动绘图是基于谷歌地球引擎云计算平台上对Landsat 8卫星图像的无监督分类。所使用的图像被选择来呈现两种通道情况(打开和关闭)。选取三幅图像,采集日期分别为开放通道和封闭通道。每张图像使用K-means聚类方法,分别使用波段6、波段7(均位于短波红外- SWIR)和归一化差水指数(NDWI)进行分类。一旦分析人员必须先验地定义聚类的数量,以及训练样本区域,这些参数将在数据集上进行测试,并比较聚类结果。所有生成的聚类图在10个随机点上进行分析,识别聚类命中和错误。由于缺乏参考地图,每个日期的所有最终聚类地图都与同一采集日期的合成真彩色图像进行比较。NDWI聚类图在分离水像元和非水像元方面效果最好。