# Inundation Extent Mapping by Synthetic Aperture Radar: A Review
## 3 Relative Strengths and Limitations of Existing Techniques
### Selected Studies of Combined Approaches  
Many operational agencies are dedicated to providing NRT flood maps based on SAR, including the International Charter Space and Major Disasters ([[https://disasterscharter.org/web/guest/home](https://disasterscharter.org/web/guest/home)]([https://disasterscharter.org/web/guest/home](https://disasterscharter.org/web/guest/home))), the United Nations Institute for Training and Research (UNITAR, [[https://unitar.org/unosat/](https://unitar.org/unosat/)]([https://unitar.org/unosat/](https://unitar.org/unosat/))), the Copernicus Emergency Management Service (EC EMS, [[https://emergency.copernicus.eu/mapping/ems/emergency-management-service-mapping](https://emergency.copernicus.eu/mapping/ems/emergency-management-service-mapping)]([https://emergency.copernicus.eu/mapping/ems/emergency-management-service-mapping](https://emergency.copernicus.eu/mapping/ems/emergency-management-service-mapping))), the European Space Agency (ESA, [[http://www.esa.int/Our_Activities/Observing_the_Earth/Copernicus/Sentinel-1](http://www.esa.int/Our_Activities/Observing_the_Earth/Copernicus/Sentinel-1)]([http://www.esa.int/Our_Activities/Observing_the_Earth/Copernicus/Sentinel-1](http://www.esa.int/Our_Activities/Observing_the_Earth/Copernicus/Sentinel-1))), the German Aerospace Center (DLR [[https://www.dlr.de/](https://www.dlr.de/)]([https://www.dlr.de/](https://www.dlr.de/))), the Centre d'Etudes Spatiales de la BIOSphere (CESBIO, [[http://www.cesbio.ups-tlse.fr/index_us.htm](http://www.cesbio.ups-tlse.fr/index_us.htm)]([http://www.cesbio.ups-tlse.fr/index_us.htm](http://www.cesbio.ups-tlse.fr/index_us.htm))), and the Canada Space Agency (CSA, [[http://www.asc-csa.gc.ca/eng/satellites/disasters.asp](http://www.asc-csa.gc.ca/eng/satellites/disasters.asp)]([http://www.asc-csa.gc.ca/eng/satellites/disasters.asp](http://www.asc-csa.gc.ca/eng/satellites/disasters.asp))). Despite this, past studies have only partially addressed the operational demands of real-time inundation mapping in terms of automation and accuracy. Often,tedious human intervention to reduce over-detection, as well as filtering to reduce under-detection caused by strong scatter disturbances and speckle-caused noise, are needed when using satellite SAR data for inundation mapping. As our space is limited, we selected from the studies mentioned above some representative ones for in-depth analysis to show how and why different methods can be combined and the strengths and limits of such combinations. These are summarized below. [PERSON] et al. [53] applied SBA [55] to determine the global threshold for binary (water and non-water) classification. In SBA, a SAR image is first divided into splits (sub-tiles) to determine their individual thresholds using the Kittler and Illingworth (KI) method [75], global minimum, and quality index. Then, only qualified splits showing sufficient water and non-water pixels are selected to get the global threshold. The OO segmentation algorithm (implemented in e-cognition software) is used to segment the image into continuous and non-overlapping object patches at different scales. Then the global threshold is applied to each object. Eventually, topography is used as an option to fine-tune the results. SBA is employed to deal with the heterogeneity of SAR backscattering from the same object in time and space. The intention of applying the OO segmentation algorithm is to reduce false alarms and speckle noise. OO was, however, originally designed for high-resolution optical sensors, which have no consideration of noise like speckle and water-like areas. The fine-tuning procedure can only deal with floodplain extended from identified water bodies, leaving inundated areas isolated from known water sources. To avoid the drawback of fixing tile size to SAR images of different places and resolution [53; 55; 76], [PERSON] et al. [77] propose the hierarchical SBA (HSBA) method with variable tile size, and they post-processed the binary water mask derived by HSBA using RGA and CD, similar to [PERSON] et al.