mohammad hossein bagheri; mohammadReza Farzaneh; behzad rayegani
Abstract
AbstractIntroduction: Flood is one of the main natural disasters in Iran, which has caused losses in different regions. The ability to produce accurate and timely flood assessments is an important safety tool for flood mitigation and response. Several methodologies have been developed to indicate the ...
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AbstractIntroduction: Flood is one of the main natural disasters in Iran, which has caused losses in different regions. The ability to produce accurate and timely flood assessments is an important safety tool for flood mitigation and response. Several methodologies have been developed to indicate the risks associated with flooding by using ground measurements. Satellite remote sensing data have been used for flood assessment because of their spatial resolution and capacity to provide information for areas of poor accessibility or lacking in ground measurements. High resolution satellite data is mainly useful for the spatial analysis of water pixels. When flood data (before and after of a flood event) are available, it is possible to classify land cover change, and thus identify which areas are flooded.Materials and Methods: The present study developed a methodology that uses Sentinel 1 images and global products to assess the losses caused by a flood in the province of Khuzestan (2020) and Chabahar-Konarak (2021-2022). In this study, in addition to Sentinel 1 satellite data, Landsat 8 satellite images have been used. The results of this research have turned into the development of a flood application in the Google Earth Engine software.Results: The results showed that the use of optically inactive images of this Landsat 8 or Sentinel 2 in cases where the cloud cover does not bother will increase the accuracy of the output. This issue is one of the specialization features in the conditions of uncertainty in determining the thresholds of changes in radar images. In the field of flood zone and subsequently estimation of losses from flood. Applying the method presented in the Google Earth Engine environment, due to the easy access to satellite images and global products, is a suitable solution for extracting the flood zone and subsequently estimating the agricultural and residential damages caused by floods.Discussion: Combining the information of radar and optical satellites can play an important role in the accuracy of the thresholds and extracting the flood zone. The limitations related to optical images such as cloud cover disturbances led to the use and evaluation of methodology based on radar images (without the use of optical images) in this research. According to the research methodology, there is no need to prepare and collect land information and global products regarding the population and its spatial distribution, land cover, permanent water areas and the digital elevation model of the land, with appropriate spatial accuracy (all information with spatial accuracy less than 100 meters) has been used. Fast access to processed satellite images, as well as general coding and processing of images and the implementation of the considered methodology in the Earth-engine environment are the main advantages of this study.