Monitoring and spatial-temporal analysis of Stryama river flood event, Karlovo municipality, Bulgaria, occurred on 02.09.2022 by the methods of remote sensing
{"title":"Monitoring and spatial-temporal analysis of Stryama river flood event, Karlovo municipality, Bulgaria, occurred on 02.09.2022 by the methods of remote sensing","authors":"Andrey Stoyanov","doi":"10.1117/12.2684415","DOIUrl":null,"url":null,"abstract":"The aim of the study is to present results derived from monitoring the flood event on river Stryama, located in Karlovo municipality, Bulgaria occurred on 02.09.2022 due to extreme intensive rainfalls. During the flood event the rainfall had increased up to 250 l/m2, and the water level of the Stryama River in some regions had reached up to 3 meters in 8 hours. Stryama river is situated in central Bulgaria, Plovdiv district, it springs up from Stara planina mountain and its length is 110 km. The applied methodology in the following survey includes use of Sentinel-2 MSI optical data and Tasseled Cap Transformation (TCT) of selected satellite imagery for change detection and estimating the territorial extent of areas affected by the flood waters. Satellite imagery of different temporal points were chosen before and after the flood event in order to track the water dynamics around the riverbed. The calculation of the spatial and temporal characteristics of the river waters were accomplished by segmenting of Sentinel-2 multispectral imagery. The application of the matrix for Tasseled Cap Transformation segments the optical images in 3 components: TCT-brightness, TCT-wetness, TCT-greenness. On the basis of TCT-wetness component and its values the dynamics and territorial distribution of river waters were monitored for the chosen temporal period. On the basis of TCT-greenness component and Normalized Differential Greenness Index (NDGI) an assessment of the impact of flood waters on the vegetated areas was made.","PeriodicalId":222517,"journal":{"name":"Remote Sensing for Agriculture, Ecosystems, and Hydrology XXV","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Remote Sensing for Agriculture, Ecosystems, and Hydrology XXV","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2684415","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
The aim of the study is to present results derived from monitoring the flood event on river Stryama, located in Karlovo municipality, Bulgaria occurred on 02.09.2022 due to extreme intensive rainfalls. During the flood event the rainfall had increased up to 250 l/m2, and the water level of the Stryama River in some regions had reached up to 3 meters in 8 hours. Stryama river is situated in central Bulgaria, Plovdiv district, it springs up from Stara planina mountain and its length is 110 km. The applied methodology in the following survey includes use of Sentinel-2 MSI optical data and Tasseled Cap Transformation (TCT) of selected satellite imagery for change detection and estimating the territorial extent of areas affected by the flood waters. Satellite imagery of different temporal points were chosen before and after the flood event in order to track the water dynamics around the riverbed. The calculation of the spatial and temporal characteristics of the river waters were accomplished by segmenting of Sentinel-2 multispectral imagery. The application of the matrix for Tasseled Cap Transformation segments the optical images in 3 components: TCT-brightness, TCT-wetness, TCT-greenness. On the basis of TCT-wetness component and its values the dynamics and territorial distribution of river waters were monitored for the chosen temporal period. On the basis of TCT-greenness component and Normalized Differential Greenness Index (NDGI) an assessment of the impact of flood waters on the vegetated areas was made.