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Journal articles on the topic 'Flooded area'
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1
Gonuguntla, Hemalatha, Khudoyberdi Abdivaitov, Mahalingam Bose, and Muzaffar Rakhmataliev. "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." InterCarto. InterGIS 26, no. 2 (2020): 421–35. http://dx.doi.org/10.35595/2414-9179-2020-2-26-421-435.
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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.
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Hutanu, Elena, Andrei Urzica, and Andrei Enea. "Evaluation of Damages Caused by Floods, Based on Satellite Images. Case Study: Jijia River, Slobozia-Dângeni Sector, July 2010." Present Environment and Sustainable Development 12, no. 2 (October 1, 2018): 135–46. http://dx.doi.org/10.2478/pesd-2018-0035.
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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.
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Jamali, A., and A. Abdul Rahman. "FLOOD MAPPING USING SYNTHETIC APERTURE RADAR: A CASE STUDY OF RAMSAR FLASH FLOOD." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W16 (October 1, 2019): 291–95. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w16-291-2019.
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Abstract. Disasters including flash floods, earthquakes, and landslides have huge economic and social losses besides their impact on environmental disruption. Studying environmental changes due to climate change can improve public and expert sector’s awareness and response towards future disastrous events. Synthetic Aperture Radar (SAR) data and Interferometric Synthetic Aperture Radar (InSAR) technologies are valuable tools for flood modeling and surface deformation modeling. This paper proposes an efficient approach to detect the flooded area changes using Sentinel-1A over Ramsar flood on 5th October 2018. For detection of the flooded area due to flash flood SARPROZ in MATLAB programming language is used and discussed. Flooded areas in Ramsar are detected based on the change detection modeling using normalized difference values of amplitude belonging to the master image (on 28th September 2018) and the slave image (on 10th October 2018).
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Moya, Luis, Yukio Endo, Genki Okada, Shunichi Koshimura, and Erick Mas. "Drawback in the Change Detection Approach: False Detection during the 2018 Western Japan Floods." Remote Sensing 11, no. 19 (October 5, 2019): 2320. http://dx.doi.org/10.3390/rs11192320.
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Synthetic aperture radar (SAR) images have been used to map flooded areas with great success. Flooded areas are often identified by detecting changes between a pair of images recorded before and after a certain flood. During the 2018 Western Japan Floods, the change detection method generated significant misclassifications for agricultural targets. To evaluate whether such a situation could be repeated in future events, this paper examines and identifies the causes of the misclassifications. We concluded that the errors occurred because of the following. (i) The use of only a single pair of SAR images from before and after the floods. (ii) The unawareness of the dynamics of the backscattering intensity through time in agricultural areas. (iii) The effect of the wavelength on agricultural targets. Furthermore, it is highly probable that such conditions might occur in future events. Our conclusions are supported by a field survey of 35 paddy fields located within the misclassified area and the analysis of Sentinel-1 time series data. In addition, in this paper, we propose a new parameter, which we named “conditional coherence”, that can be of help to overcome the referred issue. The new parameter is based on the physical mechanism of the backscattering on flooded and non-flooded agricultural targets. The performance of the conditional coherence as an input of discriminant functions to identify flooded and non-flooded agricultural targets is reported as well.
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Lee, Sunmin, Saro Lee, Moung-Jin Lee, and Hyung-Sup Jung. "Spatial Assessment of Urban Flood Susceptibility Using Data Mining and Geographic Information System (GIS) Tools." Sustainability 10, no. 3 (February 28, 2018): 648. http://dx.doi.org/10.3390/su10030648.
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Using geographic information system (GIS) tools and data-mining models, this study analyzed the relationships between flood areas and correlated hydrological factors to map the regional flood susceptibility of the Seoul metropolitan area in South Korea. We created a spatial database of data describing factors including topography, geology, soil, and land use. We used 2010 flood data for training and 2011 data for model validation. Frequency ratio (FR) and logistic regression (LR) models were applied to 2010 flood data to determine the relationships between the flooded area and its causal factors and to derive flood-susceptibility maps, which were substantiated using the area flooded in 2011 (not used for training). As a result of the accuracy validation, FR and LR model results were shown to have 79.61% and 79.05% accuracy, respectively. In terms of sustainability, floods affect water health as well as causing economic and social damage. These maps will provide useful information to decision makers for the implementation of flood-mitigation policies in priority areas in urban sustainable development and for flood prevention and management. In addition to this study, further analysis including data on economic and social activities, proximity to nature, and data on population and building density, will make it possible to improve sustainability.
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Tabacaru, Alexandru, Livia Nistor-Lopatenco, Iurie Bejan, and Alexandru Pantaz. "THE USE OF GEOGRAPHIC INFORMATION SYSTEM FOR FLOOD PREDICTIONS." Journal of Engineering Science XXVIII, no. 2 (June 2021): 112–19. http://dx.doi.org/10.52326/jes.utm.2021.28(2).09.
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The article examines the issue of using geographic information systems (GIS) and WEBGIS technologies to predict areas likely to be flooded. Probabilistic flood hazard maps (0.5%, 0.1% and 1% flood risks) were used, obtained from a model installation in an area subject to flood risk, in this case, the municipality of Ungheni in the Republic Moldova, which has been flooded in the past. The application of GIS technologies is necessary to prevent floods affecting households, infrastructure and to minimize its effects. For this purpose, were analyzed the previous floods that occurred in the region. Also were applied and overlaid thematic digital maps such as Land Use, river network, DTM, Delineation Methodology of water bodies which represents the transposition of the EU Water Framework Directive 2000/60/EC and at the end were uploaded on an ESRI Web GIS platform http://www.dbga.md/siga.html. The Coordinate system used here was WGS-84.
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Wakabayashi, H., K. Motohashi, T. Kitagami, B. Tjahjono, S. Dewayani, D. Hidayat, and C. Hongo. "FLOODED AREA EXTRACTION OF RICE PADDY FIELD IN INDONESIA USING SENTINEL-1 SAR DATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3/W7 (March 1, 2019): 73–76. http://dx.doi.org/10.5194/isprs-archives-xlii-3-w7-73-2019.
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<p><strong>Abstract.</strong> The objective of this study is to detect flooded area in rice paddy fields in Indonesia by using remotely sensed data. We used synthetic aperture radar (SAR) data for this purpose, because it is capable of getting high-resolution data in almost all-weather conditions. The paper gives a result of detecting flooded area occurred in our research sites located close to Bandung area, Tegalluar in Bojongsoang district, from the end of February to the beginning of March in 2018. The C-band SAR data acquired by Sentinel-1 were used for this analysis. We derived the gamma-naught threshold for dividing flood and non-flood areas by using a linear discriminant analysis. Discriminant accuracy reached 98% using VV polarization. By using the gamma-naught threshold and rice paddy field mask (GIS data), the rice paddy flooded area could be extracted with good accuracy.</p>
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Das, Indira, and Sujit Deka. "Impact of Flood on the Socio-Economic Conditions in the Southern Part of Kamrup District, Assam." Space and Culture, India 8, no. 4 (March 26, 2021): 106–19. http://dx.doi.org/10.20896/saci.v8i4.665.
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Flood causes extreme loss of infrastructure and human life; besides it also propagates the condition of poverty and unceasing marginalisation of the affected region from development. This study elucidates how flood contributes to the socio-economic conditions of the rural people living in the Southern part of the Kamrup district of Assam. It focusses on flood hazard zoning and flood vulnerability analyses that are delineated based on the data collected from the Moderate Resolution Imaging Spectroradiometer (MODIS) Near Real-Time (NRT) Global Flood Mapping Product Portal. Flood hazard zoning of the study area is done using Multi-Criteria evaluation method based on rainfall distribution, slope, drainage density, population density, soil type, elevation, flow accumulation, roads, and embankment utilising Cartosat DEM and IRS P6 LISS III data. The zones are identified as actively flooded, chronically flooded, and occasionally flooded zones, which affects 39.4 per cent, 12.9 per cent and 26.1 per cent population respectively covering 1189.2 sq. km, that is, 56.5 per cent area of the study region. The flood vulnerability assessment of the study area is done at village and ward level adapting geospatial assessment in a GIS environment. The findings of the research are generated through observations, key informant interviews with the rural population surveying 1420 number of households. It reveals that 200 villages are affected by floods every year that constitutes 76.6 per cent households and 78.4 per cent of the population of the study area.
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Giordan, Daniele, Davide Notti, Alfredo Villa, Francesco Zucca, Fabiana Calò, Antonio Pepe, Furio Dutto, Paolo Pari, Marco Baldo, and Paolo Allasia. "Low cost, multiscale and multi-sensor application for flooded area mapping." Natural Hazards and Earth System Sciences 18, no. 5 (May 30, 2018): 1493–516. http://dx.doi.org/10.5194/nhess-18-1493-2018.
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Abstract. Flood mapping and estimation of the maximum water depth are essential elements for the first damage evaluation, civil protection intervention planning and detection of areas where remediation is needed. In this work, we present and discuss a methodology for mapping and quantifying flood severity over floodplains. The proposed methodology considers a multiscale and multi-sensor approach using free or low-cost data and sensors. We applied this method to the November 2016 Piedmont (northwestern Italy) flood. We first mapped the flooded areas at the basin scale using free satellite data from low- to medium-high-resolution from both the SAR (Sentinel-1, COSMO-Skymed) and multispectral sensors (MODIS, Sentinel-2). Using very- and ultra-high-resolution images from the low-cost aerial platform and remotely piloted aerial system, we refined the flooded zone and detected the most damaged sector. The presented method considers both urbanised and non-urbanised areas. Nadiral images have several limitations, in particular in urbanised areas, where the use of terrestrial images solved this limitation. Very- and ultra-high-resolution images were processed with structure from motion (SfM) for the realisation of 3-D models. These data, combined with an available digital terrain model, allowed us to obtain maps of the flooded area, maximum high water area and damaged infrastructures.
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Lacava, Teodosio, Emanuele Ciancia, Mariapia Faruolo, Nicola Pergola, Valeria Satriano, and Valerio Tramutoli. "On the Potential of RST-FLOOD on Visible Infrared Imaging Radiometer Suite Data for Flooded Areas Detection." Remote Sensing 11, no. 5 (March 12, 2019): 598. http://dx.doi.org/10.3390/rs11050598.
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Timely and continuous information about flood spatiotemporal evolution are fundamental to ensure an effective implementation of the relief and rescue operations in case of inundation events. In this framework, satellite remote sensing may provide a valuable contribution provided that robust data analysis methods are implemented and suitable data, in terms of spatial, spectral and temporal resolutions, are employed. In this paper, the Robust Satellite Techniques (RST) approach, a satellite-based differential approach, already applied at detecting flooded areas (and therefore christened RST-FLOOD) with good results on different polar orbiting optical sensors (i.e., Advanced Very High Resolution Radiometer – AVHRR – and Moderate Resolution Imaging Spectroradiometer – MODIS), has been fully implemented on time series of Suomi National Polar-orbiting Partnership (Suomi-NPP-SNPP) Visible Infrared Imaging Radiometer Suite (VIIRS) data. The flooding event affecting the Metaponto Plain in Basilicata and Puglia regions (southern Italy) in December 2013 was selected as a case study and investigated by analysing five years (only December month) of VIIRS Imagery bands at 375 m spatial resolution. The achieved results clearly indicate the potential of the proposed approach, especially when compared with a satellite-based high resolution map of flooded area, as well as with the official flood hazard map of the area and the outputs of a recent published VIIRS-based method. Both flood extent and dynamics have been recognized with good reliability during the investigated period, with only a residual 11.5% of possible false positives over an inundated area extent of about 73 km2. In addition, a flooded area of about 18 km2 was found outside the hazard map, suggesting it requires updating to better manage flood risk and prevent future damages. Finally, the achieved results indicate that medium-resolution optical data, if analysed with robust methodologies like RST-FLOOD, can be suitable for detecting and monitoring floods also in case of small hydrological basins.
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Mathur, Mayank, Yashi Agarwal, Shubham Pavitra Shah, and Lavanya K. "Detecting Safe Routes During Floods Using Deep Learning." International Journal of Big Data Intelligence and Applications 1, no. 1 (January 2020): 23–35. http://dx.doi.org/10.4018/ijbdia.2020010102.
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Floods are one of the most devastating and frequently occurring natural disasters throughout the world. Floods can cause blockage of roads and hence create trouble for civilians and authorities to navigate in the flooded area. This paper proposes an automated system that uses a road extraction algorithm to extract roads from satellite images to create a highlighted map of all the available roads during floods. The road extraction algorithm the authors developed uses U-net model architecture, a fully convolutional neural network, to extract roads from aerial images (satellite images and drone images). Convolutional Neural Network is robust to shadows and water streams, able to obtain the characteristics of roads adequately and most importantly, able to produce output quickly, which is necessary for flood evacuations and relief. The developed system can be deployed as an Application Programming Interface or stand-alone system, loaded on drones, which will provide the users with a map highlighting safe paths to traverse the flooded areas.
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Moussa, R., and C. Bocquillon. "Approximation zones of the Saint-Venant equations f flood routing with overbank flow." Hydrology and Earth System Sciences 4, no. 2 (June 30, 2000): 251–60. http://dx.doi.org/10.5194/hess-4-251-2000.
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Abstract. The classification of river waves as gravity, diffusion or kinematic waves, corresponds to different forms of the momentum equation in the Saint-Venant system. This paper aims to define approximation zones of the Saint-Venant equations for flood routing in natural channels with overbank flow in the flooded area. Using linear perturbation theory, the different terms in the Saint-equations were analysed as a function of the balance between friction and inertia. Then, using non-dimensionalised variables, flood waves were expressed as a function of three parameters: the Froude number of the steady uniform flow, a dimensionless wave, number of the unsteady component of the motion and the ratio between the flooded area zone width and the main channel width. Finally, different theoretical cases, corresponding to different flooded area zone widths were analysed and compared. Results show that, when the width of the flooded area increases, the domain of application of the diffusive wave and the inematic wave models is restricted. Keywords: Saint-Venant equations; river waves; overbank flow
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Rodriguez, D. A., F. Carriello, P. J. F. Fernandes, L. Garofolo Lopes, and J. L. Siqueira Júnior. "ASSESSMENT OF FLOODED AREAS PROJECTIONS AND FLOODS POTENTIAL IMPACTS APPLYING REMOTE SENSING IMAGERY AND DEMOGRAPHIC DATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B8 (June 22, 2016): 159–61. http://dx.doi.org/10.5194/isprsarchives-xli-b8-159-2016.
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Assessing vulnerability and potential impacts associated with extreme discharges requires an accurate topographic description in order to estimate the extension of flooded areas. However, in most populated regions, topographic data obtained by in-situ measurements is not available. In this case, digital elevation models derived from remote sensing date are usually applied. Moreover, this digital elevation models have intrinsic errors that introduce bigger uncertainty in results than the associated to hydrological projections. On the other hand, estimations of flooded areas through remote sensing images provide accurate information, which could be used for the construction of river level-flooded area relationships regarding vulnerability assessment. In this work, this approach is applied for the city of Porto Velho in the Brazilian Amazonia to assess potential vulnerability to floods associated with climate change projections. The approach is validated using census data, provided by the Brazilian Institute of Geography and Statistics, and information about socio-economical injuries associated to historical floods, provided by the Brazilian Civil Defence. Hydrological projections under climate change are carried out using several downscaling of climate projections as inputs in a hydrological model. Results show more accurate estimation of flood impacts than the obtained using digital elevation models derivate from remote sensing data. This reduces uncertainties in the assessment of vulnerability to floods associated with climate change in the region.
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Rodriguez, D. A., F. Carriello, P. J. F. Fernandes, L. Garofolo Lopes, and J. L. Siqueira Júnior. "ASSESSMENT OF FLOODED AREAS PROJECTIONS AND FLOODS POTENTIAL IMPACTS APPLYING REMOTE SENSING IMAGERY AND DEMOGRAPHIC DATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B8 (June 22, 2016): 159–61. http://dx.doi.org/10.5194/isprs-archives-xli-b8-159-2016.
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Assessing vulnerability and potential impacts associated with extreme discharges requires an accurate topographic description in order to estimate the extension of flooded areas. However, in most populated regions, topographic data obtained by in-situ measurements is not available. In this case, digital elevation models derived from remote sensing date are usually applied. Moreover, this digital elevation models have intrinsic errors that introduce bigger uncertainty in results than the associated to hydrological projections. On the other hand, estimations of flooded areas through remote sensing images provide accurate information, which could be used for the construction of river level-flooded area relationships regarding vulnerability assessment. In this work, this approach is applied for the city of Porto Velho in the Brazilian Amazonia to assess potential vulnerability to floods associated with climate change projections. The approach is validated using census data, provided by the Brazilian Institute of Geography and Statistics, and information about socio-economical injuries associated to historical floods, provided by the Brazilian Civil Defence. Hydrological projections under climate change are carried out using several downscaling of climate projections as inputs in a hydrological model. Results show more accurate estimation of flood impacts than the obtained using digital elevation models derivate from remote sensing data. This reduces uncertainties in the assessment of vulnerability to floods associated with climate change in the region.
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Craciunescu, Vasile, Gheorghe Stancalie, Anisoara Irimescu, Simona Catana, Denis Mihailescu, Argentina Nertan, George Morcov, and Stefan Constantinescu. "MODIS-based multi-parametric platform for mapping of flood affected areas. Case study: 2006 Danube extreme flood in Romania." Journal of Hydrology and Hydromechanics 64, no. 4 (December 1, 2016): 329–36. http://dx.doi.org/10.1515/johh-2016-0040.
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Abstract Flooding remains the most widely distributed natural hazard in Europe, leading to significant economic and social impact. Earth observation data is presently capable of making fundamental contributions towards reducing the detrimental effects of extreme floods. Technological advance makes development of online services able to process high volumes of satellite data without the need of dedicated desktop software licenses possible. The main objective of the case study is to present and evaluate a methodology for mapping of flooded areas based on MODIS satellite images derived indices and using state-of-the-art geospatial web services. The methodology and the developed platform were tested with data for the historical flood event that affected the Danube floodplain in 2006 in Romania. The results proved that, despite the relative coarse resolution, MODIS data is very useful for mapping the development flooded area in large plain floods. Moreover it was shown, that the possibility to adapt and combine the existing global algorithms for flood detection to fit the local conditions is extremely important to obtain accurate results.
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Mohammadi, Ayub, Khalil Valizadeh Kamran, Sadra Karimzadeh, Himan Shahabi, and Nadhir Al-Ansari. "Flood Detection and Susceptibility Mapping Using Sentinel-1 Time Series, Alternating Decision Trees, and Bag-ADTree Models." Complexity 2020 (November 16, 2020): 1–21. http://dx.doi.org/10.1155/2020/4271376.
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Flooding is one of the most damaging natural hazards globally. During the past three years, floods have claimed hundreds of lives and millions of dollars of damage in Iran. In this study, we detected flood locations and mapped areas susceptible to floods using time series satellite data analysis as well as a new model of bagging ensemble-based alternating decision trees, namely, bag-ADTree. We used Sentinel-1 data for flood detection and time series analysis. We employed twelve conditioning parameters of elevation, normalized difference’s vegetation index, slope, topographic wetness index, aspect, curvature, stream power index, lithology, drainage density, proximities to river, soil type, and rainfall for mapping areas susceptible to floods. ADTree and bag-ADTree models were used for flood susceptibility mapping. We used software of Sentinel application platform, Waikato Environment for Knowledge Analysis, ArcGIS, and Statistical Package for the Social Sciences for preprocessing, processing, and postprocessing of the data. We extracted 199 locations as flooded areas, which were tested using a global positioning system to ensure that flooded areas were detected correctly. Root mean square error, accuracy, and the area under the ROC curve were used to validate the models. Findings showed that root mean square error was 0.31 and 0.3 for ADTree and bag-ADTree techniques, respectively. More findings illustrated that accuracy was obtained as 86.61 for bag-ADTree model, while it was 85.44 for ADTree method. Based on AUC, success and prediction rates were 0.736 and 0.786 for bag-ADTree algorithm, in order, while these proportions were 0.714 and 0.784 for ADTree. This study can be a good source of information for crisis management in the study area.
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AOYAMA, Sadayoshi, Yuuki UCHIDA, Masayuki HITOKOTO, Sadakazu MATSUMOTO, and Akihiko ITOU. "EXTRACTION OF FLOODED AREA BY SAR DATA AND FLOOD ANALYSIS." Journal of Japan Society of Civil Engineers, Ser. F3 (Civil Engineering Informatics) 73, no. 2 (2017): I_181—I_187. http://dx.doi.org/10.2208/jscejcei.73.i_181.
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Zúñiga, Emmanuel, and David A. Novelo-Casanova. "Hydrological hazard estimation for the municipality of Yautepec de Zaragoza, Morelos, Mexico." Hydrology 6, no. 3 (August 27, 2019): 77. http://dx.doi.org/10.3390/hydrology6030077.
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The hydrological hazard for the municipality of Yautepec de Zaragoza, State of Morelos, Mexico, is evaluated considering the overflow process of the rivers located in the Yautepec sub-basin. Different scenarios of hydrological hazard were generated to identify those areas with high flood potential using hydraulic modeling for three return periods (Rp) of 50, 100 and 500 years based on statistical analysis of the maximum annual discharge of the Yautepec hydrometric station. We used the Hec-Ras software and geographic information systems (GIS) to model the different flood scenarios. Our results indicate that 10% (1.5 km2) of the total urban area of the municipality will be flooded for a return period of 50 years. About 12% (1.8 km2) of the territory will be affected by flood for a Rp of 100 years. For a Rp of 500 years, approximately 13.5% (2.1 km2) of the municipality’s area will be flooded. Spatially, the central and southern regions of the municipality will be affected by flood heights greater than 1 m for Rp of 100 and 500 years. The northern zone will have heights of less than 0.50 m for Rp of 50 years. Our results can be used as a tool to prevent and reduce the impact of future floods in the municipality of Yautepec de Zaragoza.
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Wang, Huiliang, Hongfa Wang, Zening Wu, and Yihong Zhou. "Using Multi-Factor Analysis to Predict Urban Flood Depth Based on Naive Bayes." Water 13, no. 4 (February 7, 2021): 432. http://dx.doi.org/10.3390/w13040432.
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With global warming, the number of extreme weather events will increase. This scenario, combined with accelerating urbanization, increases the likelihood of urban flooding. Therefore, it is necessary to predict the characteristics of flooded areas caused by rainstorms, especially the flood depth. We applied the Naive Bayes theory to construct a model (NB model) to predict urban flood depth here in Zhengzhou. The model used 11 factors that affect the extent of flooding—rainfall, duration of rainfall, peak rainfall, the proportion of roads, woodlands, grasslands, water bodies and building, permeability, catchment area, and slope. The forecast depth of flooding from the NB model under different rainfall conditions was used to draw an urban inundation map by ArcGIS software. The results show that the probability and degree of urban flooding in Zhengzhou increases significantly after a return period of once every two years, and the flooded areas mainly occurred in older urban areas. The average root mean square error of prediction results was 0.062, which verifies the applicability and validity of our model in the depth prediction of urban floods. Our findings suggest the NB model as a feasible approach to predict urban flood depth.
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Zamboni Graosque, Jones, and Laurindo Antônio Guasselli. "Principal component analysis of C-SAR images for flood mapping – Santa Fé province, Argentina." Territorium, no. 27(II) (September 10, 2020): 41–48. http://dx.doi.org/10.14195/1647-7723_27-2_4.
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Flood events are phenomena associated with heavy rainfall. In Argentina, floods have high economic and social costs, including loss of human life. In this paper, principal component analysis (PCA) is used to map flood-prone areas along the Paraná river in Santa Fe, Argentina. The Sentinel-1B (S1B) images, sensor C-SAR with VH polarisation Interferometric type (IW) Ground Range Detected (GRD) with spatial resolution of 10 m, from 2016, were referenced and the PCA method was used to extract the four first principal components. The flood-affected images make it possible to accurately define the flooded area. In targets with dense vegetation, however, there is no pixel backscatter pattern. PC2 better highlighted the threshold of pixel intensity, with an accuracy of 70%, and 93% of the mapped area was shown to be flood-prone. Procedures to map floods remotely are pivotal because they can quickly obtain precise data on flood areas that may not be accessible for fieldwork or that have not yet been mapped in great detail.
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Zoka, Melpomeni, Emmanouil Psomiadis, and Nicholas Dercas. "The Complementary Use of Optical and SAR Data in Monitoring Flood Events and Their Effects." Proceedings 2, no. 11 (July 30, 2018): 644. http://dx.doi.org/10.3390/proceedings2110644.
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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.
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Bhattarai, Pawan, Prajwal Khanal, Prachanda Tiwari, Nischal Lamichhane, Prasanna Dhakal, Prakash Lamichhane, Niranjan Raj Panta, and Prashant Dahal. "Flood Inundation Mapping of Babai Basin using HEC-RAS & GIS." Journal of the Institute of Engineering 15, no. 2 (July 31, 2019): 32–44. http://dx.doi.org/10.3126/jie.v15i2.27639.
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The main objective of this research is to prepare inundation map of a section of Babai Basin and to find out the inundated areas for different return periods. In order to achieve the objectives, Geographic Information System (GIS) and HEC-RAS along with HEC-GeoRAS extension were used as tools. Coordinates were used as primary parameter and were obtained from survey to generate geometric data such as Triangular Irregular Networks (TIN), streamline, river bank and flow paths. After importing the geometry data into HEC-RAS, hydraulic modelling was applied by using flow data as main input. As a result, the watershed area of the Babai basin has been successfully modelled and map showing the flooded areas along the Babai basin has been delineated. The flooded area was geometrically overlaid on the topographic map to outline the affected areas. The area under the influence of the flood were assessed which shows that about 49% of total inundated areas comprises farming land. Also a sensitivity analysis was performed to predict the change in percentage of flooded areas when Maning’s parameter was increased by 10% and when kept same in both banks and channel. However, differences in figure of inundated areas are insignificant to variations made in Maning’s n.
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Psomiadis, Emmanouil, Konstantinos Soulis, Melpomeni Zoka, and Nicholas Dercas. "Synergistic Approach of Remote Sensing and GIS Techniques for Flash-Flood Monitoring and Damage Assessment in Thessaly Plain Area, Greece." Water 11, no. 3 (March 3, 2019): 448. http://dx.doi.org/10.3390/w11030448.
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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.
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Paraol, Cristina Martins, and Andresa Pescador. "O uso da integral definida no cálculo da área alagada da barragem do Rio Bonito." Revista Produção e Desenvolvimento 1, no. 3 (December 31, 2015): 114–30. http://dx.doi.org/10.32358/rpd.2015.v1.88.
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This paper presents an application of definite integral whose objective is to calculate the flooded area of Rio Bonito’s dam. Historical records show the importance of this dam to the region, it is responsible for contain the floods in "Banhado do Sombrio ", and the irrigation of rice fields. The dam format is far from a regular region whose area calculation would be easily found. We study definite integrals and curve fitting. These themes were used to aproximate the flooded area of Rio Bonito’s dam. To facilitate the calculations, we use of GeoGebra and graph softwares.
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Faridani, Farid, Sirus Bakhtiari, Alireza Faridhosseini, Micheal J. Gibson, Raziyeh Farmani, and Rosa Lasaponara. "Estimating Flood Characteristics Using Geomorphologic Flood Index with Regards to Rainfall Intensity-Duration-Frequency-Area Curves and CADDIES-2D Model in Three Iranian Basins." Sustainability 12, no. 18 (September 8, 2020): 7371. http://dx.doi.org/10.3390/su12187371.
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There is not enough data and computational power for conventional flood mapping methods in many parts of the world, thus fast and low-data-demanding methods are very useful in facing the disaster. This paper presents an innovative procedure for estimating flood extent and depth using only DEM SRTM 30 m and the Geomorphic Flood Index (GFI). The Geomorphologic Flood Assessment (GFA) tool which is the corresponding application of the GFI in QGIS is implemented to achieved the results in three basins in Iran. Moreover, the novel concept of Intensity-Duration-Frequency-Area (IDFA) curves is introduced to modify the GFI model by imposing a constraint on the maximum hydrologically contributing area of a basin. The GFA model implements the linear binary classification algorithm to classify a watershed into flooded and non-flooded areas using an optimized GFI threshold that minimizes the errors with a standard flood map of a small region in the study area. The standard hydraulic model envisaged for this study is the Cellular Automata Dual-DraInagE Simulation (CADDIES) 2D model which employs simple transition rules and a weight-based system rather than complex shallow water equations allowing fast flood modelling for large-scale problems. The results revealed that the floodplains generated by the GFI has a good agreement with the standard maps, especially in the fluvial rivers. However, the performance of the GFI decreases in the less steep and alluvial rivers. With some overestimation, the GFI model is also able to capture the general trend of water depth variations in comparison with the CADDIES-2D flood depth map. The modifications made in the GFI model, to confine the maximum precipitable area through implementing the IDFAs, improved the classification of flooded area and estimation of water depth in all study areas. Finally, the calibrated GFI thresholds were used to achieve the complete 100-year floodplain maps of the study areas.
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Yang, M., X. M. Geng, J. Grace, Y. F. Jia, Y. Z. Liu, S. W. Jiao, L. L. Shi, C. Lu, Y. Zhou, and G. C. Lei. "Responses of N<sub>2</sub>O flux to water level fluctuation and other environmental factors at littoral zone of Miyun Reservoir: a comparison with CH<sub>4</sub> fluxes." Biogeosciences Discussions 12, no. 7 (April 2, 2015): 5333–63. http://dx.doi.org/10.5194/bgd-12-5333-2015.
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Abstract. There have been only a few studies that allow us to estimate the contribution of newly-created reservoirs to greenhouse gas budgets. In particular, information is limited for understanding the spatiotemporal variation of N2O flux and the underlying mechanisms in the littoral zone where complex biochemical processes are induced by water level fluctuations. A study was carried out at five different water levels (deep water area, shallow water area, seasonally flooded area, control site for seasonally flooded area and non-flooded area) at the littoral zone of a temperate reservoir using the static chamber technique. Seasonal and spatial variations of N2O flux and environmental factors were monitored throughout the growing season including a flood event during summer rains. The N2O flux ranged from −2.29 to 182.47 μg m−2 h−1. Non-flooded dry land emitted more N2O than flooded land, no matter whether it was permanently or seasonally flooded. However, no significant difference was observed between seasonally flooded sites and their control sites. Wind speed, air temperature, soil water content, dissolved oxygen in water and soil nitrate influenced N2O flux significantly. In order to know the contrasting characteristics of N2O and CH4 fluxes in the littoral zone of the reservoir, results were compared with a previous study on CH4 emission carried out at the same sites and time with comparable methods. It showed that N2O flux and CH4 flux was influenced by distinct factors and in differing ways. This work highlights the complexity of N2O flux at the littoral zone. The different response ways of N2O and CH4 to environments implies the big challenge of greenhouse gas emission control through ecosystem management.
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Plaza, Tarik Godoy D., and Carla Galbiati. "Influence of Flood Pulse on Termite Diversity (INSECTA: ISOPTERA) in the Pantanal." Sociobiology 64, no. 3 (October 17, 2017): 310. http://dx.doi.org/10.13102/sociobiology.v64i3.1371.
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This research aimed to associate termite diversity to flood pulse by Paraguay River, and with savannas and pasture areas. The study was conducted nearby the town of Cáceres, in Pantanal - Mato Grosso, on six livestock farms subject to Paraguay River flood pulse. Types of land use sampled were native savanna and cultivated pasture. Flooded and dry plots were selected, both the savanna and the pasture in each sampling area. Termite richness and abundance was analysed based on the environments as an explanatory variable (FP – flooded pasture, DP – dry pasture, FS – flooded savanna, DS – dry savanna) through GLM; Tukey’s test was subsequently performed to determine whether land use and/or flood pulse can significantly affect the termite community. There were 37 termite species and 19 genera. Richness and abundance of termite species cannot be explain by flooding pulse, but were explained only by land use (pasture and savanna). The similarity analysis also identified that species composition was quite affected by flood in grazing areas, but this disturbance does not affect the savanna areas. In conclusion, flood pulse is not a determining factor for savannas or pasture termite richness, but change the composition of the termite fauna in the environment.
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Omama, Shinichi, Nobukazu Komoribayashi, Yoshihiro Inoue, Tomohiko Mase, Kuniaki Ogasawara, Yasuhiro Ishibashi, Masaki Ohsawa, et al. "Occurrence of Cerebrovascular Diseases Decreased after the Great East Japan Earthquake and Tsunami of 2011." Cerebrovascular Diseases Extra 10, no. 3 (October 8, 2020): 105–15. http://dx.doi.org/10.1159/000509869.
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<b><i>Background:</i></b> A temporary increase in the occurrence of cerebrovascular diseases (CVDs) after the Great East Japan Earthquake and Tsunami of 2011 was reported; however, no studies have been conducted to investigate long-term effects. We assessed the long-term impact of the disaster on the incidence of CVDs. <b><i>Methods:</i></b> Incidence data for CVDs from 2008 to 2017 were acquired from the population-based Stroke Registry with an inventory survey of Iwate Prefecture, Japan. Part of the coastal area in Iwate Prefecture was mildly flooded and the other part was severely flooded. Age-adjusted incidence rates of CVDs (according to the Japanese standard population) were calculated for each area. The relative risk (RR) of incidence based on the years before the disaster (2008–2010), adjusted by stratified age groups, was calculated for the year of the disaster (2011), and the years after the disaster (2012–2017) in each area. <b><i>Results:</i></b> The age-adjusted incidence rates gradually decreased in all areas, with the exception of a temporary increase among men who lived on the coast the year the disaster occurred. The adjusted RR in the disaster year were not significant in any area and those of the postdisaster years were 0.91 (95% CI 0.87–0.96) for all inland men, 0.93 (0.89–0.97) for all inland women, 0.85 (0.78–0.93) for all coastal men, 0.87 (0.81–0.94) for all coastal women, 0.88 (0.80–0.98) for men at mildly flooded coast, 0.82 (0.75–0.89) for women at mildly flooded coast, 0.79 (0.68–0.91) for men at severely flooded coast, and 0.98 (0.86–1.11) for women at severely flooded coast. <b><i>Conclusions:</i></b> The occurrence of CVDs in the flooded coastal areas did not increase in the year of the Great East Japan Earthquake and Tsunami; furthermore, it decreased for men according to the severity of flood damage in the subsequent years; this can be attributed to supportive activities for the tsunami victims and the migration of the population.
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L., T., W. V., D. C., W. C., and S. G. "CarryMe: Drone Delivery System for Flooded Area." International Journal of Computer Applications 180, no. 2 (December 15, 2017): 40–45. http://dx.doi.org/10.5120/ijca2017915956.
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Guozhong, Su, Yan Li, Liu Nan, and Liu Renyi. "Visualization and damage assessment for flooded area." Geo-spatial Information Science 7, no. 3 (January 2004): 180–86. http://dx.doi.org/10.1007/bf02826288.
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Alves, Maria Eduarda Pereira, Fernando Mainardi Fan, Vinicius Alencar Siqueira, and Leonardo Laipelt. "Flood mapping employing local, regional and global scale modeling methods for the Uruguay river." Revista Eletrônica em Gestão, Educação e Tecnologia Ambiental 24 (December 4, 2020): e22. http://dx.doi.org/10.5902/2236117062697.
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The delimitation of flooded areas is important information for natural disaster management, environmental impact prediction and for territorial planning. Flooding occurs when water levels overflow the limits of a river’s channel and seep into the floodplains. When they affect people, they are considered a natural disaster. The delimitation of a flooded area, in the occurrence of an extreme event, can be performed by using field techniques, such as mapping, surveying through the afflicted area or by taking aerial photographs. However, field survey is not a trivial task and not always does it allow for the attainment of the necessary data for a given project. For that purpose, there are various techniques that can be used to assess flood-spots. Some techniques are simpler, being based only on a Digital Elevation Model (DEM), and such is the case of the HAND model (Height Above Nearest Drainage), which has garnered plenty of fame recently in the process of applying delimitations to possibly flooded areas. Other techniques are more complex, like the use of hydrodynamic modeling. There are large-scale hydrologic-hydrodynamic models that simulate runoff generation and water transportation processes in the river basin from rainfall, basin, and meteorological data. This is the case of the large-scale distributed hydrological model called MGB (Modelo de Grandes Bacias), which has been developed and employed in these types of cases. However, there are no studies in the literature that compare the results produced by these multiple approaches using differing degrees of complexity and spatial scales. It was precisely to fill this gap in scientific literature that this work was developed. Featured here, for the first time, is the validation of the MGB model’s performance in two versions, one of regional scale and another of continental scale (MGB AS), in delimiting the flooded areas, compared to a satellite image of the inundation; and with two versions of the HAND model, one generated by a local study and the other by a global reference. The case study used in this validation was a major flood that occurred in the Uruguay River, near the town of Itaqui (Rio Grande do Sul), which borders Brazil and Argentina, in October 1997. The results show that the MGB model, both in the regional and the continental scales, could delimit the flooded area, with a few overestimations in the northern portion of the image. The HAND method at the local scale also allowed a mapping of the flooded area, with overestimates for more springhead-like areas in small tributaries. The HAND method at the global scale, on the other hand, proved to be inadequate for the purpose of delimiting flooded areas in this region. The leading cause is believed to be the small drainage area threshold linked to the utilized global HAND product. From the calculation of performance metrics, like hit rate, false alarm ratio and criticality index, Regional MGB was the one that most adequately expressed the extent of the flood observed in the Landsat 5 image when compared to the others, followed by MGB AS.
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Pulvirenti, Luca, Marco Chini, and Nazzareno Pierdicca. "InSAR Multitemporal Data over Persistent Scatterers to Detect Floodwater in Urban Areas: A Case Study in Beletweyne, Somalia." Remote Sensing 13, no. 1 (December 24, 2020): 37. http://dx.doi.org/10.3390/rs13010037.
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A stack of Sentinel-1 InSAR data in an urban area where flood events recurrently occur, namely Beletweyne town in Somalia, has been analyzed. From this analysis, a novel method to deal with the problem of flood mapping in urban areas has been derived. The approach assumes the availability of a map of persistent scatterers (PSs) inside the urban settlement and is based on the analysis of the temporal trend of the InSAR coherence and the spatial average of the exponential of the InSAR phase in each PS. Both interferometric products are expected to have high and stable values in the PSs; therefore, anomalous decreases may indicate that floodwater is present in an urban area. The stack of Sentinel-1 data has been divided into two subsets. The first one has been used as a calibration set to identify the PSs and determine, for each PS, reference values of the coherence and the spatial average of the exponential of the interferometric phase under standard non-flooded conditions. The other subset has been used for validation purposes. Flood maps produced by UNOSAT, analyzing very-high-resolution optical images of the floods that occurred in Beletweyne in April–May 2018, October–November 2019, and April–May 2020, have been used as reference data. In particular, the map of the April–May 2018 flood has been used for training purposes together with the subset of Sentinel-1 calibration data, whilst the other two maps have been used to validate the products generated by applying the proposed method. The main product is a binary map of flooded PSs that complements the floodwater map of rural/suburban areas produced by applying a well-consolidated algorithm based on intensity data. In addition, a flood severity map that labels the different districts of Beletweyne, as not, partially, or totally flooded has been generated to consolidate the validation. The results have confirmed the effectiveness of the proposed method.
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Papila, I., U. Alganci, and E. Sertel. "SENTINEL-1 BASED FLOOD MAPPING USING INTERFEROMETRIC COHERENCE AND INTENSITY CHANGE DETECTION APPROACH." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2020 (August 22, 2020): 1697–703. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2020-1697-2020.
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Abstract. This study presents a semi-automatic algorithm for mapping floods. Both Optical and Synthetic Aperture Radar (SAR) data are used to observe the flood that hit the Cukurova region of Adana (Turkey) in 2019. The performance of the interferometric coherence in complementing intensity component of SAR data is investigated for mapping the floods occurred in agricultural and urban environments. There was no ground truth data available from the flooded area, thus classification result of optical satellite image is used as a seed for the region growing algorithm that defines the classes according to a threshold value. The advantage of using both intensity and coherence change detection is verified with the results. The results have been evaluated through very high-resolution SPOT-6 optical image which acquired simultaneously with Sentinel-1B SAR image. The comparison with the SPOT-6 data results shows that the proposed approach can map flooded areas with acceptable accuracy using the SAR data from Sentinel-1 satellite mission. Highly affected agricultural areas along with the river line could be mapped both by optical and SAR analysis. Comparison of results from VV and VH polarization provided that cross-polarization VH has a very little effect on flood mapping. The proposed algorithm successfully distinguishes the classes among the affected region, especially in urban areas.
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Kurniawan, Agung. "Flooding Model as the Analysis of the Sea Level Increase as a Result of Global Warming in Coastal Area in Lampung." JURNAL GEOGRAFI 9, no. 2 (August 8, 2017): 109. http://dx.doi.org/10.24114/jg.v9i2.6465.
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The melting of ice layers, as a direct impact on global warming, is indicated from a lesser thickness of ice layers is specifically causing an increase on the sea level. Lampung, as a province that has an ecosistem of regional coast, can be estimated to submerge. Flood modelling can be done to know the estimated flood range. The model of the flooded region is taken from Shuttle Radar Topography Mission(SRTM) data, which is nomalized to get the visualisation of Digital Elevation Model (DEM). The purpose of this research is to know the estimated region of provincial coast of Lampung that is going to be flooded because of the raising of sea surface. This research uses flood inundation technique that uses one of the GIS mapping software. The result can be used as consideration to achieve policy in the building of regional coast. The regions that are flooded based on the scenario of the raising of two and three meter surface sea level are East Lampung Regency, West Lampung Regency, South Lampung Regency, Tanggamus Regency, Pesawaran Regency, and Bandar Lampung.
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Li, Jun Hui. "Technical Feasibility of Steam Flooding in Heavy Water Flooded Area." Advanced Materials Research 838-841 (November 2013): 2759–62. http://dx.doi.org/10.4028/www.scientific.net/amr.838-841.2759.
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Jin 45 heavy oil block in Liao he oil field has entered the late steam huff and puff period,Flooded serious,Average single well daily oil producing is 0.74t/d, Water recovery rate reaches as high as 260%, It is extremely urgent to convert to Steam flooding development mode ,but without corresponding theoretical basis in heavy water flooded area. Take two test well groups with scale out two well spacing as object of study, Use Petrel software for accurate geologic modeling, Bring into steam huff and puff history matching through CMG software, and then make a steam flooding feasibility prediction in heavy water flooded area. During the prediction, the huge edge water and bottom water body was set up around the model. The result of numerical simulation manifested that Water invasion rule give priority to bottom water coning, Edge water invasion is not large, Outside casing wall channeling formed water flooded in severe cases; Reservoir has been formed basically thermal union;Reservoir remaining oil saturation is 44.96%,Formation pressure is 2.91 MPaContinuous steam injection make the formation pressure increases, inhibit water cut increasing rate and water cut increasing rate, The serious water invasion problem could be effectively relieved; In the five years forecast after steam flooding, the cumulative recovery degree is 7.74%, the development effect is improved. It proved that Liao he oil field Jin 45 heavy oil heavy water flooded area turn steam flooding development is feasible. The study provides a theoretical basis for heavy flooded area of heavy oil reservoirs to turn to steam flooding development.
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Lynnyk, Iryna. "ANALYSIS OF HEATING PROCESSES OF URBANIZED TERRITORIES OF THE KHARKIV REGION AND MEASURES TO COMBAT THEM." Urban development and spatial planning, no. 77 (May 24, 2021): 287–96. http://dx.doi.org/10.32347/2076-815x.2021.77.287-296.
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Flooding of urbanized areas causes and activates dangerous geological pro-cesses, is a real threat to the safety of life of the population and the functioning of economic facilities. In this regard, the issues of studying the conditions for the devel-opment and spread of flooding on the territory of Ukraine are important and urgent. The article identifies the factors causing flooding of urbanized areas. The trends in the development of flooding in the Kharkiv region and the city of Kharkiv are deter-mined. In Ukraine, the flooded area is about 8 million hectares, and the number of flooded settlements is up to 5 thousand. The most flooded are Odessa, Nikolaev, Kherson regions. In the Kharkiv region, flooding is widespread in 39 cities and ur-ban-type settlements, and in 205 villages on an area of 200,8 km2, the affected area is 0,6 %. Flooding is observed in all districts of the region. The most flooded cities are Kharkiv, Barvenkovo, Valki, Izyum, Pervomaisky, the total flooded area was 185,7 km2, urban-type settlements Krasnopavlovka and Pechenegi, the total flooded area – 15,1 km2. The reasons for the flooding have been established. The consequences of flooding of urbanized territories are analyzed. Flooding leads to a deterioration in the condition of built-up areas and sanitary living conditions of people, an increase in morbidity, pollution of water and soil, waterlogging of significant areas of land, con-tributes to the development of negative physical and geological processes such as landslides, karst, etc., which can lead to subsidence of buildings and structures, and further to their destruction, deformations of underground engineering networks. Ana-lyzed measures to combat flooding, which can be divided into preventive and elimi-nation of already existing flooding. The activities that are proposed to be held in the city of Kharkov and the Kharkov region are outlined.
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De OLIVEIRA, Guilherme Garcia, Dejanira Luderitz SALDANHA, and Laurindo Antonio GUASSELLI. "MODELS FOR SPATIALIZATION AND FORECASTING OF FLOODED AREAS IN THE SÃO SEBASTIÃO DO CAÍ URBAN ZONE, RIO GRANDE DO SUL STATE, BRAZIL." Pesquisas em Geociências 38, no. 2 (August 31, 2011): 132. http://dx.doi.org/10.22456/1807-9806.26379.
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The study aims at developing models for the spatialization and forecasting of floods in the urban area of São Sebastião do Caí, RS, Brazil. For the calculation of return period (RP), and in order to analyze the seasonality of floods, streamflow data from the station located in the city were used. However, for the development of a mathematical model for flood forecasting, the time series of a station upstream was also used in order to perform a regression with the quotas recorded in both seasons. For the identification of flood plains, a digital terrain model was produced based on elevation data in scales between 1:2,000 and 1:10,000. The QuickBird satellite image (spatial resolution of 0.61 m) was used only for the spatialization of the land use and land cover reached by each flood scenario. Mapping and 3D simulation of the areas affected by flooding were obtained for RP of 2, 5, 10 and 30 years. The following results are most significant: i) the river water level rises between 9.28 m and 11.98 m for RP of 2 to 30 years; ii) along the historical series, 75% of floods have occurred between June and October; iii) the mathematical model for flood forecasting showed an average error of 0.72 m, and the accuracy varies between 0.62 m and 1.84 m, according to the expected magnitude; iv) it was observed that 93 hectares of urban area in São Sebastião do Caí are hit by floods with a RP of 30 years (23% of the urban area); v) modelling of a recent flood event dated of 24/09/2007 has resulted in similar values for the simulated and observed flooded area.
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Hosseiny, B., N. Ghasemian, and J. Amini. "A CONVOLUTIONAL NEURAL NETWORK FOR FLOOD MAPPING USING SENTINEL-1 AND SRTM DEM DATA: CASE STUDY IN POLDOKHTAR-IRAN." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W18 (October 18, 2019): 527–33. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w18-527-2019.
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Abstract. Flood contributes a key role in devastating natural and man-made areas. Floods usually are occurred when there is a considerable number of clouds in the sky making optic data useless. Synthetic aperture radar (SAR) images can be a valuable data source in earth observation tasks. The most important characteristic of the radar image is its ability to penetrate the cloud and dust. Therefore, monitoring earth in cloudy or rainy weather can be available by this kind of dataset. In the last few years by improving machine learning methods and development of convolutional neural networks in remote sensing applications we are facing with extremely high improvement in classification tasks. In this paper, we use dual-polarized VV and VH backscatter values of Sentinel-1 and Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) dataset in a proposed convolutional neural network to generate a land cover map of a flooded area before and after happening. Obtained classification results vary between 93.3% to 98.5% for different training sizes. By comparing the generated classified maps, flooded areas of each class can be extracted.
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Mozgovoy, Dmytro. "Satellite monitoring of flods by C-band radar data." Ukrainian journal of remote sensing, no. 16 (April 10, 2018): 4–12. http://dx.doi.org/10.36023/ujrs.2018.16.117.
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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.
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Jun, Jung Nam, Doo Chun Seo, and Hyo Suk Lim. "A Flood Disaster Area Extraction Using KOMPSAT-1 EOC Satellite Image Data." Key Engineering Materials 277-279 (January 2005): 809–15. http://dx.doi.org/10.4028/www.scientific.net/kem.277-279.809.
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The main objective of this study is to observe and extract relevant geographical information of areas afflicted with floods using KOMPSAT-1 EOC image data. The satellite images taken on September 2, 2002 of the downstream of the river of Nakdong in the province of South Gyeongsang afflicted with floods at that time are used for the purpose of demonstration. To extract information which is the boundary lines and area in flood disaster area should be made to the ortho-image with characteristic of map. The generation of ortho-images involve sensor modeling using control points and DEM to restore a geometric relation of a satellite, its images and ground of which images are provided by the satellite. Candidate areas for edge extraction are selected based on ortho-corrected images through edge preserving smoothing method, high-pass filter and Prewitt operator. Based on the generated candidate areas, edges are extracted by use of edge extracting algorithm. The resultant extracted edges enable the overall status of flooded areas to be promptly grasped. This paper demonstrates such scope of utilization of satellite data for investigation and recovery of areas damaged by natural disasters.
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Winckler, Lilian Terezinha, Angélica Konradt Güths, and Pâmela Rodrigues Gayer. "Benthic macroinvertebrates and degradation of phytomass as indicators of ecosystem functions in flooded rice cropping." Pesquisa Agropecuária Brasileira 52, no. 4 (April 2017): 261–70. http://dx.doi.org/10.1590/s0100-204x2017000300006.
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Abstract: The objective of this work was to evaluate the ecosystem functions of a natural wetland and of artificially flooded rice areas, managed under organic and conventional systems, by phytomass degradation and by the colonization of this material by benthic macroinvertebrates. The experiment was carried out in a natural wetland area, and in two flooded rice areas managed under organic and conventional systems. Twenty-five decomposition bags filled with 10 g of dry vegetation were installed in each site. At 14, 28, 42, 56, and 70 days after the beginning of the experiment, five bags from each site were collected. Macroinvertebrates were identified and classified by functional trophic group. The number of species of benthic macroinvertebrates increased: natural wetland > organic system > conventional system. The Chironomidae group was present in all areas, confirming its food plasticity and adaptability to different substrates and environmental stress situations. The Amphipoda group was present only in the artificially flooded rice area, and the Acari, only in the natural wetland. The diversity of species in the natural wetland area was higher than in the artificially flooded rice area. Nutrient cycling, provided by phytomass decomposition, is affected by the management system, and the delay in this process causes a reduction of the ecosystem functions in the conventional system.
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Liu, Jie, Zhiwei Xu, Fulong Chen, Fang Chen, and Lu Zhang. "Flood Hazard Mapping and Assessment on the Angkor World Heritage Site, Cambodia." Remote Sensing 11, no. 1 (January 8, 2019): 98. http://dx.doi.org/10.3390/rs11010098.
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World Heritage sites in general are exposed to the impacts of natural hazards, which threaten their integrity and may compromise their value. Floods are a severe threat to the Angkor World Heritage site. Studies of regional floods and flood hazard zoning have played an increasingly important role in ensuring sustainability of the Angkor site. This study developed a flood hazard index (FHI) model based on a geographic information system (GIS) and used synthetic aperture radar (SAR) data to extract historical floods at Angkor from 2007 to 2013. Four indices (flood affected frequency, absolute elevation, elevation standard deviation, drainage density) were used to identify flood-prone areas. The Analytic Hierarchy Process (AHP) and the Delphi method were employed to determine the weight of each index. The weighted indices were then used to develop a distribution map of flood hazards at Angkor. The results show that 9 monuments are at risk by potential floods among the 52 components of the Angkor monuments. The high hazard and moderate-to-high hazard areas in the core zone are mainly located surrounding the West Baray but will not bring direct risk impact on the monuments located in the core archaeological zone. The moderate hazard areas are located on both sides of the Siem Reap and Roluos rivers and in the flooded area of the Tonle Sap Lake in the core archaeological zone. These areas cover 19.4 km2, accounting for 9.13% of the total area of the core zone. This moderate hazard zone poses a greater flood threat to the core zone and must be given higher attention. The buffer zone is a small area with fewer sites. As such, flooding has a low impact on the buffer zone. The methods used in this study can be applied to flood hazard assessments of other heritage sites in Southeast Asia.
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Bianchini, Edmilson, José A. Pimenta, and Flavio A. M. dos Santos. "Spatial and temporal variation in the canopy cover in a tropical semi-deciduous forest." Brazilian Archives of Biology and Technology 44, no. 3 (September 2001): 269–76. http://dx.doi.org/10.1590/s1516-89132001000300008.
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This study was developed in the Mata dos Godoy State Park (23° 27’S, 51° 15’W) South Brazil which present great environmental heterogeneity when its north portion (ridge) is compared with the southern portion (valley), where there are some flooded areas. The forest formation is classified as tropical semi-deciduous forest. Spatial and temporal variations in the degree of the canopy cover were compared at flooded and unflooded sites. The measures were taken seasonally in 100m² plots using a spherical densiometer from spring 1995 to winter 1996. The flooded area was more open and lighter and had a greater spatial and temporal variation in the canopy cover than the unflooded areas. The greater heterogeneity in the flooded area could be due to structural characteristics of the canopy (greater spacing between individual trees, lower canopy and less stratified canopy), more frequent natural disturbances and a greater degree of deciduousness. These causes seemed to be related to the presence of the river and flooding.
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Brigita, Stevani, and Martua Sihaloho. "Livelihood Strategy, Vulnerability, and Resilience of Farmer Household in Flooded Area." Jurnal Sains Komunikasi dan Pengembangan Masyarakat [JSKPM] 2, no. 2 (April 13, 2018): 239. http://dx.doi.org/10.29244/jskpm.2.2.239-254.
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Flooding is a natural disaster that provides various impacts on life, especially for the survival of farm households. Farmers in doing the farming certainly depends on the nature and weather. Floods certainly have an impact because it can make the crops decline even to the occurrence of crop failure. Facing such circumstances requires farmers' households to determine the livelihood structures undertaken and demand that farm households determine how to conduct livelihood strategies in order to maintain and improve existing livelihoods. A livelihood strategy is a person's or a group's way of meeting their needs or achieving an improvement in life. The livelihood strategies undertaken will affect the vulnerability of a household and have a relationship with the resilience of the farm household in the event of a flood disaster. Livelihood structures and livelihood strategies of farm households living in flooded areas may be different from those in other areas not experiencing crisis or flood disaster. The purpose of this research is to analyze the strategy, vulnerability and resilience of household livelihoods of farmers in flood-prone areas.Keywords : farm household, livelihood strategy, resilience, vulnerability---------------------- ABSTRAK Banjir merupakan suatu bencana alam yang memberikan berbagai dampak terhadap kehidupan, khususnya bagi keberlangsungan hidup rumahtangga petani. Petani dalam melakukan usahataninya tentunya sangat bergantung dengan keadaan alam dan cuaca sekitar. Bencana banjir tentunya memberi dampak karena dapat membuat hasil panen menurun bahkan sampai terjadinya gagal panen. Menghadapi keadaan tersebut menuntut rumahtangga petani untuk menentukan struktur nafkah yang dilakukan dan menuntut rumahtangga petani menentukan bagaimana melakukan strategi nafkah dalam upaya mempertahankan dan meningkatkan sumber nafkah yang ada. Strategi nafkah adalah cara seseorang atau kelompok untuk memenuhi kebutuhan mereka atau mencapai peningkatan hidup. Strategi nafkah yang dilakukan akan berpengaruh terhadap kerentanan suatu rumahtangga dan memiliki hubungan dengan ketahanan (resiliensi) rumahtangga petani dalam menghadapi situasi bencana banjir. Struktur nafkah dan strategi nafkah rumahtangga petani yang tinggal di kawasan terpapar banjir dapat saja berbeda dengan wilayah lain yang tidak mengalami situasi krisis atau bencana banjir. Tujuan dari penelitian ini adalah untuk menganalisis strategi, kerentanan dan resiliensi nafkah rumahtangga petani di wilayah rawan bencana banjir.Kata Kunci : kerentanan, resiliensi, rumahtangga petani, strategi nafkah
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Dantas, Ana Alice Rodrigues, and Adriano Rolim Paz. "Use of HAND terrain descriptor for estimating flood-prone areas in river basins." Revista Brasileira de Ciências Ambientais 56, no. 3 (2021): 501–16. http://dx.doi.org/10.5327/z21769478892.
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The flood hazard mapping in a river basin is crucial for flooding risk management, mitigation strategies, and flood forecasting and warning systems, among other benefits. One approach for this mapping is based on the HAND (Height Above Nearest Drainage) terrain descriptor, directly derived from the Digital Elevation Model (DEM), in which each pixel represents the elevation difference of this point in relation to the river drainage network to which it is connected. Considering the Mamanguape river basin (3,522.7 km²; state of Paraíba, Brazil) as the study location, the present research applied this method and verified it as for five aspects: consideration of a spatially variable minimum drainage area for denoting the river drainage initiation; the impact of considering a depressionless DEM; evaluation of hydrostatic condition; effect of incorporating an existing river vector network; and comparative analysis of basin morphology regarding longitudinal river profiles. According to the results, adopting a uniform minimum drainage area for the river network initiation is a simplification that should be avoided, using a spatially variable approach, which influences the amount and spatial distribution of flooded areas. Additionally, considering the depressionless DEM leads to higher values of HAND and to a smaller flooded area (difference ranging between 3% and 99%), when compared with the use of DEM with depression, despite 3.1% of the pixels representing depressions. The use of the depressionless DEM is recommended, whereas the DEM pre-processing by incorporating a vector network (stream burning) generates dubious results regarding the relation between HAND and the morphological pattern presented in the DEM. Moreover, the estimation of flooded areas based on HAND does not guarantee the hydrostatic condition, but this disagreement comprises a negligible area for practical purposes.
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Ivanov, Milen, and Yavor Yankov. "Determination of Potеntial Floodings through Geoinformation Technology." Scientific Bulletin 21, no. 1 (June 1, 2016): 8–13. http://dx.doi.org/10.1515/bsaft-2016-0030.
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Abstract The opportunity of researching and defining flooded areas using digital landscape model, hydrological analysis through specialized software and data processing in the GIS, is being unveiled. Multiple methods of defining flooded areas on the basis of result processing of transverse profiles of a specific area of the Rositsa River near the city of Sevlievo, are developed.
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Toshiharu, K., and C. Narantsetseg. "LONG TERM CHANGES IN FLOODING AROUND GIFU CITY." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3/W8 (August 23, 2019): 421–27. http://dx.doi.org/10.5194/isprs-archives-xlii-3-w8-421-2019.
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<p><strong>Abstract.</strong> Heavy rainfall within a short period and consequent high river discharge are results in floods which subsequently creates huge infrastructure problems for areas, such huge economic deficits in production as well as damages to existing property and goods, even loss of human lives. In about hundred years ago the flat-land around the Kiso Three Rivers system (the catchment areas of the Kiso River, Nagara River, and Ibi River are called <q>the Kiso Three River system</q>) included Gifu City, Gifu Prefecture of Japan, was frequently damaged by inundation after heavy rainfall. Our research aims to evaluate flood risk changes by river improvement in the Kiso Three River system fin the past hundred years. For that reason, we simulated in several times on flood inundation in the large, medium and low scale case in the urban area of Gifu city with 2D flood inundation model, and compared the distribution of flood depth. The results, the flood inundation area in urban area for small scale flood disaster dramatically is reduced from 3.82 km<sup>2</sup> in the past time to 0.48 km<sup>2</sup> in the current time with the progress of river infrastructure improvement. However flooded area in urban area for large and middle scale disaster show the almost same. It is suggested that flood risks in urban area are dramatically improved for only small disaster.</p>
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Bathrellos, George, Hariklia Skilodimou, Konstantinos Soukis, and Efterpi Koskeridou. "Temporal and Spatial Analysis of Flood Occurrences in the Drainage Basin of Pinios River (Thessaly, Central Greece)." Land 7, no. 3 (September 11, 2018): 106. http://dx.doi.org/10.3390/land7030106.
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Historic data and old topographic maps include information on historical floods and paleo-floods. This paper aims at identifying the flood hazard by using historic data in the drainage basin of Pinios (Peneus) River, in Thessaly, central Greece. For this purpose, a catalogue of historical flood events that occurred between 1979 and 2010 and old topographic maps of 1881 were used. Moreover, geomorphic parameters such as elevation, slope, aspect and slope curvature were taken into account. The data were combined with the Geographical Information System to analyze the temporal and spatial distribution of flood events. The results show that a total number of 146 flood events were recorded in the study area. The number of flood events reaches its maximum value in the year 1994, while October contains the most flood events. The flood occurrences increased during the period 1990–2010. The flooded area reaches its maximum value in the year 1987, and November is the month with the most records. The type of damages with the most records is for rural land use. Regarding the class of damages, no human casualties were recorded during the studied period. The annual and monthly distribution of the very high category reaches the maximum values, respectively, in the year 2005 and in June. The analysis of the spatial distribution of the floods proves that most of the occurrences are recorded in the southern part of the study area. There is a certain amount of clustering of flood events in the areas of former marshes and lakes along with the lowest and flattest parts of the study area. These areas are located in the central, southern, south-eastern and coastal part of the study area and create favorable conditions for flooding. The proposed method estimates the localization of sites prone to flood, and it may be used for flood hazard assessment mapping and for flood risk management.
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Zhang, Guang-hui, Jin-yun Pu, and Shao-hua Mao. "Research of the Flooded Time and Vent Area of All Flooded High Expansion Foam System." Procedia Engineering 211 (2018): 996–1003. http://dx.doi.org/10.1016/j.proeng.2017.12.102.
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Hidayah, Zainul, Luhur Mukti Prayogo, and Maulinna Kusumo Wardhani. "Sea level rise impact modelling on small islands: case study gili raja island of east java." MATEC Web of Conferences 177 (2018): 01017. http://dx.doi.org/10.1051/matecconf/201817701017.
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Coastal regions and small islands are areas that will be adversely affected by the phenomenon of sea level rise globally. In general, Sea Level Rise (SLR) will result in coastal impacts as follows: increased frequency and intensity of floods, changes in ocean currents and widespread intrusion of sea water. This research was conducted in Gili Raja Island of Sumenep Madura. Objectives of this research were to demonstrate the ability of combining remote sensing and GIS method to determine the impact of SLR on a small island and to model its scale using different scenario. GIS based run-up model were performed to estimate and predict the impact of SLR to the island’s area. Three water level scenario (0.5 m, 1.0 m and 1.5 m) were applied. The results showed that in the first scenario 8.73% of the island was flooded by sea water, furthermore in two other scenario the flooded area was increase significantly (15.88% and 22.38%).