Please use this identifier to cite or link to this item: http://ktisis.cut.ac.cy/handle/10488/3635
Title: Flood mapping of Yialias river catchment area in Cyprus using Alos Palsar radar images
Authors: Tymvios, Filippos S. 
Alexakis, Dimitrios 
Themistocleous, Kyriacos 
Retalis, Adrianos 
Michaelides, Silas 
Pashiardis, Stelios 
Hadjimitsis, Diofantos G. 
Agapiou, Athos 
Keywords: Soil surveys
Advanced land observing satellites
Land cover
Landscape metrics
Linear regression models
Mediterranean region
Phased array type l-band synthetic aperture radars
Precipitation events
Soil moisture mapping
Agriculture
Catchments
Classification (of information)
Ecosystems
Flood control
Floods
Mapping
Mathematical models
Radar
Regression analysis
Remote sensing
Runoff
Satellite imagery
Soil moisture
Textures
Issue Date: 2012
Publisher: SPIE
Source: Proceedings of SPIE - The International Society for Optical Engineering, 2012, United Kingdom, Volume 8531, Article number 85310S
Abstract: This study strives to highlight the potential of flood inundation monitoring and mapping in a catchment area in Cyprus (Yialias river) with the use of radar satellite images. Due to the lack of satellite data acquired during dates flood inundation events took place, the research team selected specific images acquired during dates that severe precipitation events were recorded from the rain gauge station network of Cyprus Meteorological Service in the specific study area. The relationship between soil moisture and precipitation was thoroughly studied and linear regression models were developed to predict future flood inundation events. Specifically, the application of fully polarimetric (ALOS PALSAR) and data acquired over different dates for soil moisture mapping is presented. The PALSAR (Phased Array type L-band Synthetic Aperture Radar) sensor carried by the ALOS (Advanced Land Observing Satellite) have quadruple polarizations (HH, VV, HV, VH). The amount of returned radiation (as backscatter echoes) that dictates the brightness of the image depends on factors such as the roughness, size of the target relative to the signal's wavelength, volumetric and diffused scattering. The variation in soil moisture pattern during different precipitation events is presented through soil moisture maps obtained from ALOS PALSAR and data acquired during different dates with different precipitation rates. Soil moisture variation is clearly seen through soil moisture maps and the developed regression models are used to simulate future inundation events. The results indicated the considerable potential of radar satellite images in soil moisture and flood mapping in catchments areas of Mediterranean region. 2012 SPIE.
URI: http://ktisis.cut.ac.cy/jspui/handle/10488/3635
ISSN: 0277786X
DOI: 10.1117/12.974581
Rights: © SPIE
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