scholarly journals The Complementary Use of Optical and SAR Data in Monitoring Flood Events and Their Effects

Proceedings ◽  
2018 ◽  
Vol 2 (11) ◽  
pp. 644 ◽  
Author(s):  
Melpomeni Zoka ◽  
Emmanouil Psomiadis ◽  
Nicholas Dercas
Keyword(s):  
Flash Flood ◽  
Radar Data ◽  
Flood Events ◽  
Threshold Method ◽  
Landsat 7 ◽  
Flooded Area ◽  
Earth Observation Satellites ◽  
Flooded Areas ◽  
Water Indices ◽  
Sentinel 2

This paper describes the synergetic use of earth observation satellites optical and radar data to detect flooded areas and explore the impacts of the flood event. A flash flood episode took place in May 2016, in the central-eastern part of West Thessaly (Central Greece). A Landsat-7 ETM+ and a Sentinel-1 SAR image were acquired. For Landsat-7 several water indices were applied and for the Sentinel-1 a threshold method was implemented. Furthermore, Sentinel-2 images were utilized so as to record the land use/cover of the flooded area. The inundated areas and the affected cultivations were delineated with high precision, and the financial effects were evaluated.

scholarly journals Synergistic Approach of Remote Sensing and GIS Techniques for Flash-Flood Monitoring and Damage Assessment in Thessaly Plain Area, Greece

Water ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 448 ◽  
Author(s):  
Emmanouil Psomiadis ◽  
Konstantinos Soulis ◽  
Melpomeni Zoka ◽  
Nicholas Dercas
Keyword(s):  
Flash Flood ◽  
Radar Data ◽  
Threshold Method ◽  
Plain Area ◽  
Elevation Data ◽  
Landsat 7 ◽  
Synergistic Approach ◽  
Flooded Area ◽  
Earth Observation Satellites ◽  
Elevation Model

This paper describes the synergetic use of earth observation satellites optical and radar data with a high-resolution digital elevation model (DEM) to detect flooded areas and explore the impacts of a flood event. A flash flood episode took place in May 2016, in the central-eastern part of West Thessaly (Central Greece). Landsat-7 ETM+ and a Sentinel-1 SAR images were acquired. For Landsat-7, several water indices were applied and for the Sentinel-1 a threshold method was implemented. Elevation data were also used to improve the delineation of the inundated areas, and to estimate flood water depth. Furthermore, Sentinel-2 images were utilized so as to record the land use/cover of the flooded area. The inundated areas and the affected cultivations were delineated with high precision, and the financial effects were evaluated.

scholarly journals Open Surface Water Mapping Algorithms: A Comparison of Water-Related Spectral Indices and Sensors

Water ◽  
2017 ◽  
Vol 9 (4) ◽  
pp. 256 ◽  
Author(s):  
Yan Zhou ◽  
Jinwei Dong ◽  
Xiangming Xiao ◽  
Tong Xiao ◽  
Zhiqi Yang ◽  
...  
Keyword(s):  
Surface Water ◽  
Water Body ◽  
Landsat 8 ◽  
Open Surface ◽  
Body Mapping ◽  
Water Index ◽  
Landsat 7 ◽  
Surface Water Bodies ◽  
Water Indices ◽  
Sentinel 2

Open surface water bodies play an important role in agricultural and industrial production, and are susceptible to climate change and human activities. Remote sensing data has been increasingly used to map open surface water bodies at local, regional, and global scales. In addition to image statistics-based supervised and unsupervised classifiers, spectral index- and threshold-based approaches have also been widely used. Many water indices have been proposed to identify surface water bodies; however, the differences in performances of these water indices as well as different sensors on water body mapping are not well documented. In this study, we reviewed and compared existing open surface water body mapping approaches based on six widely-used water indices, including the tasseled cap wetness index (TCW), normalized difference water index (NDWI), modified normalized difference water index (mNDWI), sum of near infrared and two shortwave infrared bands (Sum457), automated water extraction index (AWEI), land surface water index (LSWI), as well as three medium resolution sensors (Landsat 7 ETM+, Landsat 8 OLI, and Sentinel-2 MSI). A case region in the Poyang Lake Basin, China, was selected to examine the accuracies of the open surface water body maps from the 27 combinations of different algorithms and sensors. The results showed that generally all the algorithms had reasonably high accuracies with Kappa Coefficients ranging from 0.77 to 0.92. The NDWI-based algorithms performed slightly better than the algorithms based on other water indices in the study area, which could be related to the pure water body dominance in the region, while the sensitivities of water indices could differ for various water body conditions. The resultant maps from Landsat 8 and Sentinel-2 data had higher overall accuracies than those from Landsat 7. Specifically, all three sensors had similar producer accuracies while Landsat 7 based results had a lower user accuracy. This study demonstrates the improved performance in Landsat 8 and Sentinel-2 for open surface water body mapping efforts.

scholarly journals Satellite monitoring of flods by C-band radar data

2018 ◽  
pp. 4-12
Author(s):  
Dmytro Mozgovoy
Keyword(s):  
Image Processing ◽  
Spatial Resolution ◽  
Radar Data ◽  
Satellite Monitoring ◽  
Radar Images ◽  
Automated Image Processing ◽  
Monitoring Area ◽  
Flooded Areas ◽  
Sentinel 2

Automated image processing methodology is proposed for all-weather satellite monitoring of floods based on C-band radar data, which allows to determine the boundaries and areas of flooded areas when assessing the magnitude, dynamics and consequences of floods. Processing results comparison of medium spatial resolution scanner and radar images from Sentinel-1 and Sentinel-2 satellites is made. The advantages of a radar survey with cloudiness in the monitoring area are shown.

scholarly journals Evaluation of Damages Caused by Floods, Based on Satellite Images. Case Study: Jijia River, Slobozia-Dângeni Sector, July 2010

2018 ◽  
Vol 12 (2) ◽  
pp. 135-146 ◽  
Author(s):  
Elena Hutanu ◽  
Andrei Urzica ◽  
Andrei Enea
Keyword(s):  
Satellite Imagery ◽  
Flow Rate ◽  
Satellite Images ◽  
Good Accuracy ◽  
Arable Land ◽  
Maximum Extension ◽  
Landsat 7 ◽  
Flooded Area ◽  
Flooded Areas

Abstract This research aimed to identify flooded areas following the July 2010 floods, using Landsat 7-ETM + satellite imagery and a more efficient way to extract water bodies. By computing several indices, such as MNDWI, NDWI, NDVI, AWI, WRI and NDMI, it was concluded that, in the present case, the NDWI index was most effective, the data obtained having a very good accuracy. The studied area was the Jijia River Slobozia-Dângeni sector, the Landsat 7-ETM + images were taken on July 3, 2010. The flow rate at this time at the Dângeni station was 473 cm, decreasing compared to July 1, 2010 when the share reached 579 cm. The flooded area obtained is 15.80 km2, the maximum extension of the flood area on July 3, 2010 being approx. 1 km on the localities of Durneşti and Sapoveni. The study found 143 houses in 19 localities flooded. Of the total flooded areas, the largest share is held by arable land (44.58%), with a surface area of 7.04 km2.

scholarly journals A COMBINED STUDY OF FLOOD PROPAGATION MAPPING, USING SENTINEL-1 AND LANDSAT-8 DATA. A CASE STUDY FROM RIVER EVROS, GREECE

2017 ◽  
Vol 50 (3) ◽  
pp. 1711 ◽  
Author(s):  
A. Kyriou ◽  
K. Nikolakopoulos
Keyword(s):  
Radar Data ◽  
Optical Data ◽  
Landsat 8 ◽  
Flood Events ◽  
Water Index ◽  
Normalized Difference Water Index ◽  
Remote Sensing Techniques ◽  
Surrounding Areas ◽  
Flooded Areas

Floods are suddenly and temporary natural disasters, which influence equally important the society and the natural environment, affecting areas that are not normally covered by water. In the context of flood mapping, different remote sensing techniques may contribute in a sufficient and effective way. This paper deals with mapping the spread of water bodies from natural levees of the river Evros and therefore the flood event on the surrounding areas of the river. In this work, radar data from Sentinel-1 mission as well as optical data from Landsat-8 were utilized. Specifically, Sentinel-1 data before flood events were treated with respectively during flood, yielding an image which reflects the propagation of the event. Moreover, Landsat-8 data were acquired with the aim of identifying and mapping of flooded areas, utilizing the Normalized Difference Water Index calculation. The results of the two methods were compared and flooded areas were evaluated. 

scholarly journals A comparison of Sentinel-1 and Sentinel-2 in assessing flooded area and built-up land use: A case study of selected coastal districts in Andra Pradesh, India

2020 ◽  
Vol 26 (2) ◽  
pp. 421-435
Author(s):  
Hemalatha Gonuguntla ◽  
Khudoyberdi Abdivaitov ◽  
Mahalingam Bose ◽  
Muzaffar Rakhmataliev
Keyword(s):  
Remote Sensing ◽  
Microwave Remote Sensing ◽  
Climatic Conditions ◽  
Area Estimation ◽  
Optical Imagery ◽  
Flooded Area ◽  
Pass Through ◽  
Flooded Areas ◽  
Microwave Data ◽  
Sentinel 2

In tropical climatic conditions, floods occur during heavy rainfall. Floods during this thick cloud cover partially stops the optical imagery to pass through the atmosphere and record the surface reflectance. Another kind of satellite imagery that is available is microwave remote sensing data that can pass through the clouds. However, the exploration of this microwave remote sensing began recently for earth observation applications. So, the algorithms and methods available for exploiting advantages from microwave data is still under research. The current part of the work is to explore the methods available to differentiate between the microwave data (Sentinel-1) and Optical imagery (Sentinel-2) in flooded and built-up area estimation. The ultimate aim is to conclude with most suitable datasets and fast computing methods in estimating the built-up area and flooded area during the emergency disaster time. Two case studies taken up for the study are August 2019 East Godavari floods and October 2019 Titli cyclone. So, the adopted method to estimate the flooded areas and built-up areas from the Sentinel-1A and Sentinel-2B was RGB clustering (Red, Green and Blue clustering) using the derived RGB colour combinations in snap 7.0 software. The datasets were classified into built-up, flooded area and vegetation areas using Random Forest supervised classification, a machine learning technique Validation of estimated built-up and flooded areas estimated from Sentinel-1A and Sentinel-2B was done using the random pixel distribution technique. Since the de-centralisation of estimated flooded areas and built-up area helps in fast distribution of the response forces to the affected area, estimation of built-up and flooded area was also taken up for the sub-districts of East Godavari district, India. Finally, the study estimates the damaged built-up and vegetation due to August 2019 East Godavari floods from Sentinel-1A and Sentinel-2B. Flooded area due to ‘Titli’ cyclone 2018 was estimated in East Godavari, Visakhapatnam and Vijianagaram districts of Andhra Pradesh state.

scholarly journals Characterization of a Mediterranean flash flood event using rain gauges, radar, GIS and lightning data

2008 ◽  
Vol 17 ◽  
pp. 35-41 ◽  
Author(s):  
M. Barnolas ◽  
A. Atencia ◽  
M. C. Llasat ◽  
T. Rigo
Keyword(s):  
Flash Flood ◽  
Radar Data ◽  
Convective Precipitation ◽  
Flood Event ◽  
Flood Events ◽  
Rain Gauges ◽  
Radar Echoes ◽  
Spatial Coverage ◽  
Ephemeral Rivers ◽  
Accumulated Rainfall

Abstract. Flash flood events are very common in Catalonia, generating a high impact on society, including losses in life almost every year. They are produced by the overflowing of ephemeral rivers in narrow and steep basins close to the sea. This kind of floods is associated with convective events producing high rainfall intensities. The aim of the present study is to analyse the 12–14 September 2006 flash flood event within the framework of the characteristics of flood events in the Internal Basins of Catalonia (IBC). To achieve this purpose all flood events occurred between 1996 and 2005 have been analysed. Rainfall and radar data have been introduced into a GIS, and a classification of the events has been done. A distinction of episodes has been made considering the spatial coverage of accumulated rainfall in 24 h, and the degree of the convective precipitation registered. The study case can be considered as a highly convective one, with rainfalls covering all the IBC on the 13th of September. In that day 215.9 mm/24 h were recorded with maximum intensities above 130 mm/h. A complete meteorological study of this event is also presented. In addition, as this is an episode with a high lightning activity it has been chosen to be studied into the framework of the FLASH project. In this way, a comparison between this information and raingauge data has been developed. All with the goal in mind of finding a relation between lightning density, radar echoes and amounts of precipitation. Furthermore, these studies improve our knowledge about thunderstorms systems.

scholarly journals MAPPING RECURRENT FLOODING ZONE ALONG ESTONIAN INLAND WATERS FROM SENTINEL-1 AND -2

2020 ◽  
Vol XLIII-B3-2020 ◽  
pp. 627-632
Author(s):  
L. Sipelgas ◽  
A. Aavaste ◽  
R. Uiboupin
Keyword(s):  
Spatial Planning ◽  
High Water ◽  
Statistical Information ◽  
Inland Waters ◽  
Additional Information ◽  
Local Municipalities ◽  
Flooding Zone ◽  
Flooded Area ◽  
Flooded Areas ◽  
Sentinel 2

Abstract. In the process of spatial planning in Estonia the local municipalities are required to define the recurrent flooding zone along the inland waters that locate at their territory. Estonia is well known for its large floodplains that are annually covered by water. However, information about the spatial flood extent is scarce. A methodology for mapping the flooded area from Sentinel-1 and -2 imagery was developed and applied on data covering high water seasons in 2016–2019. Statistical information about flooded areas along the inland waters were compared with other available data sources related to wetlands i.e. map of wetlands in Estonian Topographic Database. Results showed that additional information about flood extent and duration retrieved from Sentinel-1 and Sentinel-2 the data can contribute to defining the recurrent flooding zone along the inland waters in process on spatial planning.

scholarly journals THE APPLICABILITY OF DUAL POLARIZED SENTINEL-1 SAR DATA FOR DETECTION OF FLOODED AREAS IN POL-E DOKHTAR, LORESTAN, IRAN

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 655-657
Author(s):  
N. Kianfar
Keyword(s):  
Microwave Remote Sensing ◽  
Optical Data ◽  
Flood Mapping ◽  
Flood Inundation ◽  
High Incidence ◽  
Dual Polarized ◽  
Low Incidence ◽  
Flooded Area ◽  
Flooded Areas ◽  
Sentinel 2

Abstract. The main source for acquiring enough information about the areas of flood for the purpose of quick mapping is Microwave remote sensing because of its capability of imaging even in serious conditions of weather. Sentinel-1 with HV polarization is way more practical than VV polarization for detecting the flooded area due to its sensivity to short ripples over the surface of the flood. Despite this privilege, at low incidence angles, the same difficulty is observed in HV polarization. In this research, the main focus is on extracting the flood inundation with dual polarized sentinel-1 data in high and low incidence angles. The extraction of backscatter values for flood surface in VV and also HV polarizations had been done. The backscatter from floodwater is high at low incidence angles and sometimes low at high incidence angles as is illustrated by Sentinel-1 HV polarized data. However, the alteration is marginal at those high and low incidence angles with using Sentinel-1 VV polarized data. A measurement between Sentinel-1 VV & HV datasets and Optical Sentinel-2 had been done. The extension of flood is higher when we use Sentinel-2 as opposed to VV & HV and also the flood extent from VV at low incidence angles is way lesser. Another observation is that even at diverse incidence angles, the combination of flood mapping from VV & HV have the ability to compare with optical data much better.

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