23.2.2.3 Flood Analysis, Flood Mapping, Flood Monitoring

Asante, K.O., Macuacua, R.D., Artan, G.A., Lietzow, R.W., Verdin, J.P.,
Developing a Flood Monitoring System From Remotely Sensed Data for the Limpopo Basin,
GeoRS(45), No. 6, June 2007, pp. 1709-1714.
IEEE DOI 0706
BibRef

Horritt, M.S., Mason, D.C., Cobby, D.M., Davenport, I.J., Bates, P.D.,
Waterline mapping in flooded vegetation from airborne SAR imagery,
RSE(85), No. 3, 30 May 2003, pp. 271-281.
Elsevier DOI 0309
BibRef

Mason, D.C., Horritt, M.S., Dall'Amico, J.T., Scott, T.R., Bates, P.D.,
Improving River Flood Extent Delineation From Synthetic Aperture Radar Using Airborne Laser Altimetry,
GeoRS(45), No. 12, December 2007, pp. 3932-3943.
IEEE DOI 0711
BibRef

Schumann, G., di Baldassarre, G., Bates, P.D.,
The Utility of Spaceborne Radar to Render Flood Inundation Maps Based on Multialgorithm Ensembles,
GeoRS(47), No. 8, August 2009, pp. 2801-2807.
IEEE DOI 0907
BibRef

Cruz, V.H.[Virginia Herrera], Müller, M.[Marc], Weise, C.[Christian],
Flood Extent Mapping Based on TerraSAR-X Data,
PFG(2010), No. 6, 2010, pp. 475-488.
WWW Link. 1211
BibRef

Mason, D.C., Davenport, I.J., Neal, J.C., Schumann, G.J.P., Bates, P.D.,
Near Real-Time Flood Detection in Urban and Rural Areas Using High-Resolution Synthetic Aperture Radar Images,
GeoRS(50), No. 8, August 2012, pp. 3041-3052.
IEEE DOI 1208
BibRef

Khatami, R., Mountrakis, G.,
Implications of Classification of Methodological Decisions in Flooding Analysis from Hurricane Katrina,
RS(4), No. 12, December 2012, pp. 3877-3891.
DOI Link 1211
BibRef

Faruolo, M., Coviello, I., Lacava, T., Pergola, N.[Nicola], Tramutoli, V.[Valerio],
A Multi-Sensor Exportable Approach for Automatic Flooded Areas Detection and Monitoring by a Composite Satellite Constellation,
GeoRS(51), No. 4, April 2013, pp. 2136-2149.
IEEE DOI 1304
BibRef

Giustarini, L., Hostache, R., Matgen, P., Schumann, G.J.P., Bates, P.D., Mason, D.C.,
A Change Detection Approach to Flood Mapping in Urban Areas Using TerraSAR-X,
GeoRS(51), No. 4, April 2013, pp. 2417-2430.
IEEE DOI 1304
BibRef

Kuenzer, C., Guo, H., Huth, J., Leinenkugel, P., Li, X., Dech, S.,
Flood Mapping and Flood Dynamics of the Mekong Delta: ENVISAT-ASAR-WSM Based Time Series Analyses,
RS(5), No. 2, February 2013, pp. 687-715.
DOI Link 1303
BibRef

Millán, V.E.G.[Virginia Elena García], Teuwsen, S.[Sebastian], Pakzad, K.[Kian],
GMES4Mining: Description of a Flooding Process in Mining Areas using spectral Indices on multi-temporal Landsat Imagery,
PFG(2013), No. 5, 2013, pp. 427-436.
DOI Link 1310
BibRef

Martinis, S.[Sandro], Twele, A.[André], Strobl, C.[Christian], Kersten, J.[Jens], Stein, E.[Enrico],
A Multi-Scale Flood Monitoring System Based on Fully Automatic MODIS and TerraSAR-X Processing Chains,
RS(5), No. 11, 2013, pp. 5598-5619.
DOI Link 1312
BibRef

Diakakis, M.[Michalis], Pallikarakis, A.[Aggelos], Katsetsiadou, K.[Katerina],
Using a Spatio-Temporal GIS Database to Monitor the Spatial Evolution of Urban Flooding Phenomena. The Case of Athens Metropolitan Area in Greece,
IJGI(3), No. 1, 2014, pp. 96-109.
DOI Link 1402
BibRef

Kuenzer, C.[Claudia], Guo, H.D.[Hua-Dong], Schlegel, I.[Inga], Tuan, V.Q.[Vo Quoc], Li, X.[Xinwu], Dech, S.[Stefan],
Varying Scale and Capability of Envisat ASAR-WSM, TerraSAR-X Scansar and TerraSAR-X Stripmap Data to Assess Urban Flood Situations: A Case Study of the Mekong Delta in Can Tho Province,
RS(5), No. 10, 2013, pp. 5122-5142.
DOI Link 1311
BibRef

Khan, S.I.[Sadiq I.], Hong, Y.[Yang], Gourley, J.J.[Jonathan J.], Khattak, M.U.[Muhammad Umar], de Groeve, T.[Tom],
Multi-Sensor Imaging and Space-Ground Cross-Validation for 2010 Flood along Indus River, Pakistan,
RS(6), No. 3, 2014, pp. 2393-2407.
DOI Link 1404
BibRef

Ticehurst, C.[Catherine], Guerschman, J.P.[Juan Pablo], Chen, Y.[Yun],
The Strengths and Limitations in Using the Daily MODIS Open Water Likelihood Algorithm for Identifying Flood Events,
RS(6), No. 12, 2014, pp. 11791-11809.
DOI Link 1412
BibRef

Iervolino, P., Guida, R., Iodice, A., Riccio, D.,
Flooding Water Depth Estimation With High-Resolution SAR,
GeoRS(53), No. 5, May 2015, pp. 2295-2307.
IEEE DOI 1502
floods BibRef

Li, L.[Linyi], Chen, Y.[Yun], Yu, X.[Xin], Liu, R.[Rui], Huang, C.[Chang],
Sub-pixel flood inundation mapping from multispectral remotely sensed images based on discrete particle swarm optimization,
PandRS(101), No. 1, 2015, pp. 10-21.
Elsevier DOI 1503
Flood inundation BibRef

Ireland, G.[Gareth], Volpi, M.[Michele], Petropoulos, G.P.[George P.],
Examining the Capability of Supervised Machine Learning Classifiers in Extracting Flooded Areas from Landsat TM Imagery: A Case Study from a Mediterranean Flood,
RS(7), No. 3, 2015, pp. 3372-3399.
DOI Link 1504
BibRef

Martinis, S.[Sandro], Kersten, J.[Jens], Twele, A.[André],
A fully automated TerraSAR-X based flood service,
PandRS(104), No. 1, 2015, pp. 203-212.
Elsevier DOI 1505
SAR BibRef

Zhang, P.[Peng], Lu, J.Z.[Jian-Zhong], Feng, L.[Lian], Chen, X.L.[Xiao-Ling], Zhang, L.[Li], Xiao, X.W.[Xiong-Wu], Liu, H.G.[Hong-Gao],
Hydrodynamic and Inundation Modeling of China's Largest Freshwater Lake Aided by Remote Sensing Data,
RS(7), No. 4, 2015, pp. 4858-4879.
DOI Link 1505
BibRef

Dao, P.D.[Phuong D.], Liou, Y.A.[Yuei-An],
Object-Based Flood Mapping and Affected Rice Field Estimation with Landsat 8 OLI and MODIS Data,
RS(7), No. 5, 2015, pp. 5077-5097.
DOI Link 1506
BibRef

Chapman, B.[Bruce], McDonald, K.[Kyle], Shimada, M.[Masanobu], Rosenqvist, A.[Ake], Schroeder, R.[Ronny], Hess, L.[Laura],
Mapping Regional Inundation with Spaceborne L-Band SAR,
RS(7), No. 5, 2015, pp. 5440-5470.
DOI Link 1506
BibRef

Chen, N.C.[Neng-Cheng], Du, W.Y.[Wen-Ying], Song, F.[Fan], Chen, Z.Q.[Ze-Qiang],
FLCNDEMF: An Event Metamodel for Flood Process Information Management under the Sensor Web Environment,
RS(7), No. 6, 2015, pp. 7231.
DOI Link 1507
BibRef

Xiao, C.J.[Chang-Jiang], Chen, N.C.[Neng-Cheng], Wang, X.L.[Xiao-Lei], Chen, Z.Q.[Ze-Qiang],
A Semantic Registry Method Using Sensor Metadata Ontology to Manage Heterogeneous Sensor Information in the Geospatial Sensor Web,
IJGI(5), No. 5, 2016, pp. 63.
DOI Link 1606
BibRef

Wang, C.[Chao], Chen, N.C.[Neng-Cheng], Wang, W.[Wei], Chen, Z.Q.[Ze-Qiang],
A Hydrological Sensor Web Ontology Based on the SSN Ontology: A Case Study for a Flood,
IJGI(7), No. 1, 2017, pp. xx-yy.
DOI Link 1801
BibRef

Hu, Y.X.[Yan-Xia], Huang, J.L.[Jin-Liang], Du, Y.[Yun], Han, P.P.[Peng-Peng], Huang, W.[Wei],
Monitoring Spatial and Temporal Dynamics of Flood Regimes and Their Relation to Wetland Landscape Patterns in Dongting Lake from MODIS Time-Series Imagery,
RS(7), No. 6, 2015, pp. 7494.
DOI Link 1507
BibRef

Martinis, S.[Sandro], Rieke, C.[Christoph],
Backscatter Analysis Using Multi-Temporal and Multi-Frequency SAR Data in the Context of Flood Mapping at River Saale, Germany,
RS(7), No. 6, 2015, pp. 7732.
DOI Link 1507
BibRef

Kuenzer, C.[Claudia], Klein, I.[Igor], Ullmann, T.[Tobias], Georgiou, E.F.[Efi Foufoula], Baumhauer, R.[Roland], Dech, S.[Stefan],
Remote Sensing of River Delta Inundation: Exploiting the Potential of Coarse Spatial Resolution, Temporally-Dense MODIS Time Series,
RS(7), No. 7, 2015, pp. 8516.
DOI Link 1506
BibRef

Chignell, S.M.[Stephen M.], Anderson, R.S.[Ryan S.], Evangelista, P.H.[Paul H.], Laituri, M.J.[Melinda J.], Merritt, D.M.[David M.],
Multi-Temporal Independent Component Analysis and Landsat 8 for Delineating Maximum Extent of the 2013 Colorado Front Range Flood,
RS(7), No. 8, 2015, pp. 9822.
DOI Link 1509
BibRef

Chen, N.C.[Neng-Cheng], Zhou, L.J.[Lian-Jie], Chen, Z.Q.[Ze-Qiang],
A Sharable and Efficient Metadata Model for Heterogeneous Earth Observation Data Retrieval in Multi-Scale Flood Mapping,
RS(7), No. 8, 2015, pp. 9610.
DOI Link 1509
BibRef

Byun, Y.G.[Young-Gi], Han, Y.K.[You-Kyung], Chae, T.[Taebyeong],
Image Fusion-Based Change Detection for Flood Extent Extraction Using Bi-Temporal Very High-Resolution Satellite Images,
RS(7), No. 8, 2015, pp. 10347.
DOI Link 1509
BibRef

Feng, Q.L.[Quan-Long], Gong, J.H.[Jian-Hua], Liu, J.T.[Jian-Tao], Li, Y.[Yi],
Flood Mapping Based on Multiple Endmember Spectral Mixture Analysis and Random Forest Classifier: The Case of Yuyao, China,
RS(7), No. 9, 2015, pp. 12539.
DOI Link 1511

See also UAV Remote Sensing for Urban Vegetation Mapping Using Random Forest and Texture Analysis. BibRef

Giustarini, L.[Laura], Chini, M.[Marco], Hostache, R.[Renaud], Pappenberger, F.[Florian], Matgen, P.[Patrick],
Flood Hazard Mapping Combining Hydrodynamic Modeling and Multi Annual Remote Sensing data,
RS(7), No. 10, 2015, pp. 14200.
DOI Link 1511
BibRef

Gomes, T.L.[Thiago L.], Magalhães, S.V.G.[Salles V. G.], Andrade, M.V.A.[Marcus V. A.], Franklin, W.R.[W. Randolph], Pena, G.C.[Guilherme C.],
Efficiently computing the drainage network on massive terrains using external memory flooding process,
GeoInfo(19), No. 4, October 2015, pp. 671-692.
Springer DOI 1511
BibRef

Chung, H.W.[Hsiao-Wei], Liu, C.C.[Cheng-Chien], Cheng, I.F.[I-Fan], Lee, Y.R.[Yun-Ruei], Shieh, M.C.[Ming-Chang],
Rapid Response to a Typhoon-Induced Flood with an SAR-Derived Map of Inundated Areas: Case Study and Validation,
RS(7), No. 9, 2015, pp. 11954.
DOI Link 1511
BibRef

Jongman, B.[Brenden], Wagemaker, J.[Jurjen], Romero, B.R.[Beatriz Revilla], de Perez, E.C.[Erin Coughlan],
Early Flood Detection for Rapid Humanitarian Response: Harnessing Near Real-Time Satellite and Twitter Signals,
IJGI(4), No. 4, 2015, pp. 2246.
DOI Link 1511
BibRef

Reager, J.T.[John T.], Thomas, A.C.[Alys C.], Sproles, E.A.[Eric A.], Rodell, M.[Matthew], Beaudoing, H.K.[Hiroko K.], Li, B.L.[Bai-Ling], Famiglietti, J.S.[James S.],
Assimilation of GRACE Terrestrial Water Storage Observations into a Land Surface Model for the Assessment of Regional Flood Potential,
RS(7), No. 11, 2015, pp. 14663.
DOI Link 1512
BibRef

Malinowski, R.[Radoslaw], Groom, G.[Geoff], Schwanghart, W.[Wolfgang], Heckrath, G.[Goswin],
Detection and Delineation of Localized Flooding from WorldView-2 Multispectral Data,
RS(7), No. 11, 2015, pp. 14853.
DOI Link 1512
BibRef

Revilla-Romero, B.[Beatriz], Hirpa, F.A.[Feyera A.], del Pozo, J.T.[Jutta Thielen], Salamon, P.[Peter], Brakenridge, R.[Robert], Pappenberger, F.[Florian], de Groeve, T.[Tom],
On the Use of Global Flood Forecasts and Satellite-Derived Inundation Maps for Flood Monitoring in Data-Sparse Regions,
RS(7), No. 11, 2015, pp. 15702.
DOI Link 1512
BibRef

Wu, G.P.[Gui-Ping], Liu, Y.[Yuanbo],
Downscaling Surface Water Inundation from Coarse Data to Fine-Scale Resolution: Methodology and Accuracy Assessment,
RS(7), No. 12, 2015, pp. 15813.
DOI Link 1601
BibRef

Pulvirenti, L., Chini, M., Pierdicca, N., Boni, G.,
Use of SAR Data for Detecting Floodwater in Urban and Agricultural Areas: The Role of the Interferometric Coherence,
GeoRS(54), No. 3, March 2016, pp. 1532-1544.
IEEE DOI 1603
Backscatter BibRef

Boergens, E.[Eva], Dettmering, D.[Denise], Schwatke, C.[Christian], Seitz, F.[Florian],
Treating the Hooking Effect in Satellite Altimetry Data: A Case Study along the Mekong River and Its Tributaries,
RS(8), No. 2, 2016, pp. 91.
DOI Link 1603
Water level time series estimation using altimetry. BibRef

d'Addabbo, A., Refice, A., Pasquariello, G., Lovergine, F.P., Capolongo, D., Manfreda, S.,
A Bayesian Network for Flood Detection Combining SAR Imagery and Ancillary Data,
GeoRS(54), No. 6, June 2016, pp. 3612-3625.
IEEE DOI 1606
belief networks BibRef

Pradhan, B., Tehrany, M.S., Jebur, M.N.,
A New Semiautomated Detection Mapping of Flood Extent From TerraSAR-X Satellite Image Using Rule-Based Classification and Taguchi Optimization Techniques,
GeoRS(54), No. 7, July 2016, pp. 4331-4342.
IEEE DOI 1606
Earth BibRef

Zander, F.[Franziska], Kralisch, S.[Sven],
River Basin Information System: Open Environmental Data Management for Research and Decision Making,
IJGI(5), No. 7, 2016, pp. 123.
DOI Link 1608
BibRef

Li, L.Y.[Lin-Yi], Xu, T.B.[Ting-Bao], Chen, Y.[Yun],
Improved Urban Flooding Mapping from Remote Sensing Images Using Generalized Regression Neural Network-Based Super-Resolution Algorithm,
RS(8), No. 8, 2016, pp. 625.
DOI Link 1609
BibRef

Díaz-Delgado, R.[Ricardo], Aragonés, D.[David], Afán, I.[Isabel], Bustamante, J.[Javier],
Long-Term Monitoring of the Flooding Regime and Hydroperiod of Doñana Marshes with Landsat Time Series (1974-2014),
RS(8), No. 9, 2016, pp. 775.
DOI Link 1610
BibRef

Tamari, S.[Serge], Guerrero-Meza, V.[Vicente],
Flash Flood Monitoring with an Inclined Lidar Installed at a River Bank: Proof of Concept,
RS(8), No. 10, 2016, pp. 834.
DOI Link 1609
BibRef

Schinke, R.[Reinhard], Kaidel, A.[Anna], Golz, S.[Sebastian], Naumann, T.[Thomas], López-Gutiérrez, J.S.[José Santos], Garvin, S.[Stephen],
Analysing the Effects of Flood-Resilience Technologies in Urban Areas Using a Synthetic Model Approach,
IJGI(5), No. 11, 2016, pp. 202.
DOI Link 1612
BibRef

Giustarini, L., Hostache, R., Kavetski, D., Chini, M., Corato, G., Schlaffer, S., Matgen, P.,
Probabilistic Flood Mapping Using Synthetic Aperture Radar Data,
GeoRS(54), No. 12, December 2016, pp. 6958-6969.
IEEE DOI 1612
floods BibRef

Landuyt, L.[Lisa], van Wesemael, A.[Alexandra], Schumann, G.J.P.[Guy J.P.], Hostache, R.[Renaud], Verhoest, N.E.C.[Niko E. C.], van Coillie, F.M.B.[Frieke M. B.],
Flood Mapping Based on Synthetic Aperture Radar: An Assessment of Established Approaches,
GeoRS(57), No. 2, February 2019, pp. 722-739.
IEEE DOI 1901
Synthetic aperture radar, Histograms, Standards, Floods, Active contours, Entropy, Urban areas, Active contours, thresholding BibRef

Singh, A.[Akansha], Singh, K.K.[Krishna Kant],
Satellite image classification using Genetic Algorithm trained radial basis function neural network, application to the detection of flooded areas,
JVCIR(42), No. 1, 2017, pp. 173-182.
Elsevier DOI 1701
Radial basis function BibRef

Nakmuenwai, P.[Pisut], Yamazaki, F.[Fumio], Liu, W.[Wen],
Automated Extraction of Inundated Areas from Multi-Temporal Dual-Polarization RADARSAT-2 Images of the 2011 Central Thailand Flood,
RS(9), No. 1, 2017, pp. xx-yy.
DOI Link 1702
BibRef
Earlier: A2, A3, Only:
Extraction Of Flooded Areas Due The 2015 Kanto-tohoku Heavy Rainfall In Japan Using Palsar-2 Images,
ISPRS16(B8: 179-183).
DOI Link 1610
BibRef

Xia, H.M.[Hao-Ming], Zhao, W.[Wei], Li, A.[Ainong], Bian, J.H.[Jin-Hu], Zhang, Z.J.[Zheng-Jian],
Subpixel Inundation Mapping Using Landsat-8 OLI and UAV Data for a Wetland Region on the Zoige Plateau, China,
RS(9), No. 1, 2017, pp. xx-yy.
DOI Link 1702
BibRef

Vanderhoof, M.K.[Melanie K.], Distler, H.E.[Hayley E.], Mendiola, D.T.G.[Di_Ana Teresa G.], Lang, M.[Megan],
Integrating Radarsat-2, Lidar, and Worldview-3 Imagery to Maximize Detection of Forested Inundation Extent in the Delmarva Peninsula, USA,
RS(9), No. 2, 2017, pp. xx-yy.
DOI Link 1703
BibRef

Olthof, I.[Ian],
Mapping Seasonal Inundation Frequency (1985-2016) along the St-John River, New Brunswick, Canada using the Landsat Archive,
RS(9), No. 2, 2017, pp. xx-yy.
DOI Link 1703
BibRef

Langhammer, J.[Jakub], Lendzioch, T.[Theodora], Mirijovský, J.[Jakub], Hartvich, F.[Filip],
UAV-Based Optical Granulometry as Tool for Detecting Changes in Structure of Flood Depositions,
RS(9), No. 3, 2017, pp. xx-yy.
DOI Link 1704
BibRef

Ban, H.J.[Hyun-Ju], Kwon, Y.J.[Young-Joo], Shin, H.[Hayan], Ryu, H.S.[Han-Sol], Hong, S.[Sungwook],
Flood Monitoring Using Satellite-Based RGB Composite Imagery and Refractive Index Retrieval in Visible and Near-Infrared Bands,
RS(9), No. 4, 2017, pp. xx-yy.
DOI Link 1705
BibRef

Liu, X.Y.[Xiao-Yi], Sahli, H.[Hichem], Meng, Y.[Yu], Huang, Q.Q.[Qing-Qing], Lin, L.[Lei],
Flood Inundation Mapping from Optical Satellite Images Using Spatiotemporal Context Learning and Modest AdaBoost,
RS(9), No. 6, 2017, pp. xx-yy.
DOI Link 1706
BibRef

Mao, J.[Jian], Wang, S.D.[Shan-Dong], Ni, J.H.[Jian-Hua], Xi, C.B.[Chang-Bai], Wang, J.C.[Jie-Chen],
Management System for Dam-Break Hazard Mapping in a Complex Basin Environment,
IJGI(6), No. 6, 2017, pp. xx-yy.
DOI Link 1706
BibRef

Bohorquez, P.[Patricio], del Moral-Erencia, J.D.[José David],
100 Years of Competition between Reduction in Channel Capacity and Streamflow during Floods in the Guadalquivir River (Southern Spain),
RS(9), No. 7, 2017, pp. xx-yy.
DOI Link 1708
BibRef

Horkaew, P.[Paramate], Puttinaovarat, S.[Supattra],
Entropy-Based Fusion of Water Indices and DSM Derivatives for Automatic Water Surfaces Extraction and Flood Monitoring,
IJGI(6), No. 10, 2017, pp. xx-yy.
DOI Link 1710
BibRef

Sun, Z.L.[Zhang-Li], Zhu, X.F.[Xiu-Fang], Pan, Y.Z.[Yao-Zhong], Zhang, J.S.[Jin-Shui],
Assessing Terrestrial Water Storage and Flood Potential Using GRACE Data in the Yangtze River Basin, China,
RS(9), No. 10, 2017, pp. xx-yy.
DOI Link 1711
BibRef

Zhou, H.[Hao], Luo, Z.C.[Zhi-Cai], Tangdamrongsub, N.[Natthachet], Wang, L.[Lunche], He, L.J.[Li-Jie], Xu, C.[Chuang], Li, Q.[Qiong],
Characterizing Drought and Flood Events over the Yangtze River Basin Using the HUST-Grace2016 Solution and Ancillary Data,
RS(9), No. 11, 2017, pp. xx-yy.
DOI Link 1712
BibRef

Zhou, H.[Hao], Luo, Z.C.[Zhi-Cai], Tangdamrongsub, N.[Natthachet], Zhou, Z.B.[Ze-Bing], He, L.J.[Li-Jie], Xu, C.[Chuang], Li, Q.[Qiong], Wu, Y.L.[Yun-Long],
Identifying Flood Events over the Poyang Lake Basin Using Multiple Satellite Remote Sensing Observations, Hydrological Models and In Situ Data,
RS(10), No. 5, 2018, pp. xx-yy.
DOI Link 1806
BibRef

Chini, M., Hostache, R., Giustarini, L., Matgen, P.,
A Hierarchical Split-Based Approach for Parametric Thresholding of SAR Images: Flood Inundation as a Test Case,
GeoRS(55), No. 12, December 2017, pp. 6975-6988.
IEEE DOI 1712
Backscatter, Distribution functions, Estimation, Histograms, Spatial resolution, Speckle, Synthetic aperture radar, synthetic aperture radar (SAR) BibRef

Tong, X.H.[Xiao-Hua], Luo, X.[Xin], Liu, S.G.[Shu-Guang], Xie, H.[Huan], Chao, W.[Wei], Liu, S.[Shuang], Liu, S.J.[Shi-Jie], Makhinov, A.N., Makhinova, A.F., Jiang, Y.Y.[Yu-Ying],
An approach for flood monitoring by the combined use of Landsat 8 optical imagery and COSMO-SkyMed radar imagery,
PandRS(136), 2018, pp. 144-153.
Elsevier DOI 1802
SAR, Water extraction, Support vector machine, Active contour, Inundation analysis BibRef

Feng, Y.[Yu], Sester, M.[Monika],
Extraction of Pluvial Flood Relevant Volunteered Geographic Information (VGI) by Deep Learning from User Generated Texts and Photos,
IJGI(7), No. 2, 2018, pp. xx-yy.
DOI Link 1802
BibRef

Boergens, E.[Eva], Nielsen, K.[Karina], Andersen, O.B.[Ole Baltazar], Dettmering, D.[Denise], Seitz, F.[Florian],
River Levels Derived with CryoSat-2 SAR Data Classification: A Case Study in the Mekong River Basin,
RS(9), No. 12, 2017, pp. xx-yy.
DOI Link 1802
BibRef

Yang, C.[Chao], Luo, J.[Jin], Hu, C.L.[Chu-Li], Tian, L.[Lu], Li, J.[Jie], Wang, K.[Ke],
An Observation Task Chain Representation Model for Disaster Process-Oriented Remote Sensing Satellite Sensor Planning: A Flood Water Monitoring Application,
RS(10), No. 3, 2018, pp. xx-yy.
DOI Link 1804
BibRef

Sghaier, M.O.[Moslem Ouled], Hammami, I.[Imen], Foucher, S.[Samuel], Lepage, R.[Richard],
Flood Extent Mapping from Time-Series SAR Images Based on Texture Analysis and Data Fusion,
RS(10), No. 2, 2018, pp. xx-yy.
DOI Link 1804
BibRef

Yi, L.[Lu], Zhang, W.[Wanchang], Wang, K.[Kai],
Evaluation of Heavy Precipitation Simulated by the WRF Model Using 4D-Var Data Assimilation with TRMM 3B42 and GPM IMERG over the Huaihe River Basin, China,
RS(10), No. 4, 2018, pp. xx-yy.
DOI Link 1805
BibRef

Martinis, S.[Sandro], Plank, S.[Simon], Cwik, K.[Kamila],
The Use of Sentinel-1 Time-Series Data to Improve Flood Monitoring in Arid Areas,
RS(10), No. 4, 2018, pp. xx-yy.
DOI Link 1805
BibRef

Li, X.H.[Xiao-Hui], Han, G.Q.[Guo-Qi], Yang, J.S.[Jing-Song], Chen, D.[Dake], Zheng, G.[Gang], Chen, N.[Nan],
Using Satellite Altimetry to Calibrate the Simulation of Typhoon Seth Storm Surge off Southeast China,
RS(10), No. 4, 2018, pp. xx-yy.
DOI Link 1805
BibRef

Amitrano, D., di Martino, G., Iodice, A., Riccio, D., Ruello, G.,
Unsupervised Rapid Flood Mapping Using Sentinel-1 GRD SAR Images,
GeoRS(56), No. 6, June 2018, pp. 3290-3299.
IEEE DOI 1806
Feeds, Floods, Fuzzy systems, Indexes, Spatial resolution, Synthetic aperture radar, Classification, co-occurrence texture, synthetic aperture radar (SAR) BibRef

Amitrano, D., di Martino, G., Iodice, A., Mitidieri, F., Papa, M.N., Riccio, D., Ruello, G.,
Mapping small reservoirs in semi-arid regions using multitemporal SAR: Methods and applications,
MultiTemp17(1-4)
IEEE DOI 1712
hydrological techniques, remote sensing, reservoirs, synthetic aperture radar, area measurements, innovative method, BibRef

Li, J.G.[Jia-Guang], Yang, X.C.[Xiu-Cheng], Maffei, C.[Carmine], Tooth, S.[Stephen], Yao, G.Q.[Guang-Qing],
Applying Independent Component Analysis on Sentinel-2 Imagery to Characterize Geomorphological Responses to an Extreme Flood Event near the Non-Vegetated Río Colorado Terminus, Salar de Uyuni, Bolivia,
RS(10), No. 5, 2018, pp. xx-yy.
DOI Link 1806
BibRef

Kordelas, G.A.[Georgios A.], Manakos, I.[Ioannis], Aragonés, D.[David], Díaz-Delgado, R.[Ricardo], Bustamante, J.[Javier],
Fast and Automatic Data-Driven Thresholding for Inundation Mapping with Sentinel-2 Data,
RS(10), No. 6, 2018, pp. xx-yy.
DOI Link 1806
BibRef

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IEEE DOI 1808
data acquisition, floods, hydrological techniques, probability, remote sensing, enhancing near real-time imagery, remote sensing BibRef

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The Use of Unmanned Aerial Vehicles to Estimate Direct Tangible Losses to Residential Properties from Flood Events: A Case Study of Cockermouth Following the Desmond Storm,
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DOI Link 1811
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DOI Link 1812
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Chaabani, C.[Chayma], Chini, M.[Marco], Abdelfattah, R.[Riadh], Hostache, R.[Renaud], Chokmani, K.[Karem],
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Liu, J.[Jie], Xu, Z.W.[Zhi-Wei], Chen, F.[Fulong], Chen, F.[Fang], Zhang, L.[Lu],
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Wang, Y.[Yi], Hong, H.Y.[Hao-Yuan], Chen, W.[Wei], Li, S.J.[Shao-Jun], Pamucar, D.[Dragan], Gigovic, L.[Ljubomir], Drobnjak, S.[Siniša], Bui, D.T.[Dieu Tien], Duan, H.[Hexiang],
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IEEE DOI 1901
Rivers, Satellites, Discharges (electric), Input variables, Satellite broadcasting, Forecasting, Fault diagnosis, remote sensing BibRef

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Lin, L.[Li], Di, L.P.[Li-Ping], Tang, J.[Junmei], Yu, E.[Eugene], Zhang, C.[Chen], Rahman, M.S.[Md. Shahinoor], Shrestha, R.[Ranjay], Kang, L.J.[Ling-Jun],
Improvement and Validation of NASA/MODIS NRT Global Flood Mapping,
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Jiang, J.C.[Jing-Chao], Liu, J.Z.[Jun-Zhi], Cheng, C.X.[Chang-Xiu], Huang, J.Z.[Jing-Zhou], Xue, A.[Anke],
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Jiang, J.C.[Jing-Chao], Qin, C.Z.[Cheng-Zhi], Yu, J.[Juan], Cheng, C.X.[Chang-Xiu], Liu, J.Z.[Jun-Zhi], Huang, J.Z.[Jing-Zhou],
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On the Potential of RST-FLOOD on Visible Infrared Imaging Radiometer Suite Data for Flooded Areas Detection,
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Bhattacharya, B.[Biswa], Mazzoleni, M.[Maurizio], Ugay, R.[Reyne],
Flood Inundation Mapping of the Sparsely Gauged Large-Scale Brahmaputra Basin Using Remote Sensing Products,
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Jacquinod, F.[Florence], Bonaccorsi, J.[Julia],
Studying Social Uses of 3D Geovisualizations: Lessons Learned from Action-Research Projects in the Field of Flood Mitigation Planning,
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Jones, J.W.[John W.],
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Elsevier DOI 1904
Flood detection, Convolutional neural networks, Natural disasters, Social media, Satellite imagery, Multimedia indexing and retrieval BibRef

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Inundation Extent Mapping by Synthetic Aperture Radar: A Review,
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Li, Y.[Yu], Martinis, S.[Sandro], Wieland, M.[Marc],
Urban flood mapping with an active self-learning convolutional neural network based on TerraSAR-X intensity and interferometric coherence,
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Elsevier DOI 1905
Urban flooding, Multi-temporal SAR, Interferometric coherence, Active learning, Self-learning, Convolution neural network BibRef

Zou, F.[Fang], Tenzer, R.[Robert], Jin, S.G.[Shuang-Gen],
Water Storage Variations in Tibet from GRACE, ICESat, and Hydrological Data,
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Visualization of Flooding Using Adaptive Spatial Resolution,
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Wang, Y.[Yanmei], Zhang, C.C.[Cheng-Cai], Zhang, Y.S.[Yi-Sheng], Huang, H.[He], Feng, L.T.[Ling-Tong],
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Hoang, T.V.[Thanh Van], Chou, T.Y.[Tien Yin], Nguyen, N.T.[Ngoc Thach], Fang, Y.M.[Yao Min], Yeh, M.L.[Mei Ling], Nguyen, Q.H.[Quoc Huy], Nguyen, X.L.[Xuan Linh],
A Robust Early Warning System for Preventing Flash Floods in Mountainous Area in Vietnam,
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Multi-Index Image Differencing Method (MINDED) for Flood Extent Estimations,
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Bui, D.T.[Duie Tien], Khosravi, K.[Khabat], Shahabi, H.[Himan], Daggupati, P.[Prasad], Adamowski, J.F.[Jan F.], Melesse, A.M.[Assefa M.], Pham, B.T.[Binh Thai], Pourghasemi, H.R.[Hamid Reza], Mahmoudi, M.[Mehrnoosh], Bahrami, S.[Sepideh], Pradhan, B.[Biswajeet], Shirzadi, A.[Ataollah], Chapi, K.[Kamran], Lee, S.[Saro],
Flood Spatial Modeling in Northern Iran Using Remote Sensing and GIS: A Comparison between Evidential Belief Functions and Its Ensemble with a Multivariate Logistic Regression Model,
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Operational Flood Mapping Using Multi-Temporal Sentinel-1 SAR Images: A Case Study from Bangladesh,
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Albano, R.[Raffaele], Mancusi, L.[Leonardo], Adamowski, J.[Jan], Cantisani, A.[Andrea], Sole, A.[Aurelia],
A GIS Tool for Mapping Dam-Break Flood Hazards in Italy,
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Lin, Y.N.[Yunung Nina], Yun, S.H.[Sang-Ho], Bhardwaj, A.[Alok], Hill, E.M.[Emma M.],
Urban Flood Detection with Sentinel-1 Multi-Temporal Synthetic Aperture Radar (SAR) Observations in a Bayesian Framework: A Case Study for Hurricane Matthew,
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Object-Based Flood Analysis Using a Graph-Based Representation,
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Mahdavi, S.[Sahel], Salehi, B.[Bahram], Huang, W.M.[Wei-Min], Amani, M.[Meisam], Brisco, B.[Brian],
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She, S.Y.[Shi-Ying], Zhong, H.Y.[Hao-Yu], Fang, Z.X.[Zhi-Xiang], Zheng, M.[Meng], Zhou, Y.[Yan],
Extracting Flooded Roads by Fusing GPS Trajectories and Road Network,
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Eivazy, H.[Hooshang], Malek, M.R.[Mohammad Reza],
Flood Management in Aqala through an Agent-Based Solution and Crowdsourcing Services in an Enterprise Geospatial Information System,
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Heritage, G.[George], Entwistle, N.[Neil],
Drone Based Quantification of Channel Response to an Extreme Flood for a Piedmont Stream,
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Li, Y.[Yu], Martinis, S.[Sandro], Wieland, M.[Marc], Schlaffer, S.[Stefan], Natsuaki, R.[Ryo],
Urban Flood Mapping Using SAR Intensity and Interferometric Coherence via Bayesian Network Fusion,
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Wieland, M.[Marc], Martinis, S.[Sandro],
A Modular Processing Chain for Automated Flood Monitoring from Multi-Spectral Satellite Data,
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Sarker, C.[Chandrama], Mejias, L.[Luis], Maire, F.[Frederic], Woodley, A.[Alan],
Flood Mapping with Convolutional Neural Networks Using Spatio-Contextual Pixel Information,
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Moya, L.[Luis], Endo, Y.[Yukio], Okada, G.[Genki], Koshimura, S.[Shunichi], Mas, E.[Erick],
Drawback in the Change Detection Approach: False Detection during the 2018 Western Japan Floods,
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Kordelas, G.A.[Georgios A.], Manakos, I.[Ioannis], Lefebvre, G.[Gaëtan], Poulin, B.[Brigitte],
Automatic Inundation Mapping Using Sentinel-2 Data Applicable to Both Camargue and Doñana Biosphere Reserves,
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Huang, C.[Chang], Chen, Y.[Yun], Zhang, S.Q.[Shi-Qiang], Li, L.[Linyi], Shui, J.F.[Jun-Feng], Liu, Q.[Qihang],
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Liang, J.Y.[Jia-Yong], Liu, D.S.[De-Sheng],
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Flood mapping, Water delineation, Sentinel-1, SAR, Backscatter distribution, Thresholding BibRef

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Xiong, J.[Junnan], Pang, Q.[Quan], Fan, C.K.[Chun-Kun], Cheng, W.M.[Wei-Ming], Ye, C.C.[Chong-Chong], Zhao, Y.L.[Yun-Liang], He, Y.R.[Yuan-Rong], Cao, Y.F.[Yi-Fan],
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Rättich, M.[Michaela], Martinis, S.[Sandro], Wieland, M.[Marc],
Automatic Flood Duration Estimation Based on Multi-Sensor Satellite Data,
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Lin, Y.T.[Yan-Ting], Yang, M.D.[Ming-Der], Han, J.Y.[Jen-Yu], Su, Y.F.[Yuan-Fong], Jang, J.H.[Jiun-Huei],
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Hultquist, C.[Carolynne], Cervone, G.[Guido],
Integration of Crowdsourced Images, USGS Networks, Remote Sensing, and a Model to Assess Flood Depth during Hurricane Florence,
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Aristizabal, F.[Fernando], Judge, J.[Jasmeet], Monsivais-Huertero, A.[Alejandro],
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Inman, V.L.[Victoria L.], Lyons, M.B.[Mitchell B.],
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Rosenqvist, J.[Jessica], Rosenqvist, A.[Ake], Jensen, K.[Katherine], McDonald, K.[Kyle],
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Laborczi, A.[Annamária], Bozán, C.[Csaba], Körösparti, J.[János], Szatmári, G.[Gábor], Kajári, B.[Balázs], Túri, N.[Norbert], Kerezsi, G.[György], Pásztor, L.[László],
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Forbes, B.T.[Brandon T.], DeBenedetto, G.P.[Geoffrey P.], Dickinson, J.E.[Jesse E.], Bunch, C.E.[Claire E.], Fitzpatrick, F.A.[Faith A.],
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Yang, S.T.[Sheng-Tian], Li, C.J.[Chao-Jun], Lou, H.Z.[He-Zhen], Wang, P.F.[Peng-Fei], Wang, J.[Juan], Ren, X.Y.[Xiao-Yu],
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Kim, Y.[Yunjee], Lee, M.J.[Moung-Jin],
Rapid Change Detection of Flood Affected Area after Collapse of the Laos Xe-Pian Xe-Namnoy Dam Using Sentinel-1 GRD Data,
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Huang, M.M.[Min-Min], Jin, S.G.[Shuang-Gen],
Rapid Flood Mapping and Evaluation with a Supervised Classifier and Change Detection in Shouguang Using Sentinel-1 SAR and Sentinel-2 Optical Data,
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Debusscher, B.[Bos], Landuyt, L.[Lisa], van Coillie, F.[Frieke],
A Visualization Tool for Flood Dynamics Monitoring Using a Graph-Based Approach,
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Singha, M.[Mrinal], Dong, J.W.[Jin-Wei], Sarmah, S.[Sangeeta], You, N.[Nanshan], Zhou, Y.[Yan], Zhang, G.[Geli], Doughty, R.[Russell], Xiao, X.M.[Xiang-Ming],
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Elsevier DOI 2007
Flood, Sentinel-1 SAR, Google Earth Engine, Bangladesh, Sentinel-2 BibRef

Zhang, Y.[Ying], Crawford, P.[Peter],
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Moya, L.[Luis], Mas, E.[Erick], Koshimura, S.[Shunichi],
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Ichim, L.[Loretta], Popescu, D.[Dan],
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Islam, K.A.[Kazi Aminul], Uddin, M.S.[Mohammad Shahab], Kwan, C.[Chiman], Li, J.[Jiang],
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Chaudhary, P., d'Aronco, S., Leitão, J.P., Schindler, K., Wegner, J.D.,
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Object detection, Deep learning, Image segmentation, Flood estimation, Learning to rank, Flood detection BibRef

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Spyrou, C.[Christos], Varlas, G.[George], Pappa, A.[Aikaterini], Mentzafou, A.[Angeliki], Katsafados, P.[Petros], Papadopoulos, A.[Anastasios], Anagnostou, M.N.[Marios N.], Kalogiros, J.[John],
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Ma, Y.[Yu], Chen, H.[Haonan], Ni, G.[Guangheng], Chandrasekar, V., Gou, Y.[Yabin], Zhang, W.J.[Wen-Juan],
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Ohki, M.[Masato], Yamamoto, K.[Kosuke], Tadono, T.[Takeo], Yoshimura, K.[Kei],
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Unnithan, S.L.K.[S L Kesav], Biswal, B.[Basudev], Rüdiger, C.[Christoph],
Flood Inundation Mapping by Combining GNSS-R Signals with Topographical Information,
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Li, S.[Sanmei], Goldberg, M.D.[Mitchell D.], Sjoberg, W.[William], Zhou, L.[Lihang], Nandi, S.[Sreela], Chowdhury, N.[Nazmi], Straka, W.[William], Yang, T.[Tianshu], Sun, D.L.[Dong-Lian],
Assessment of the Catastrophic Asia Floods and Potentially Affected Population in Summer 2020 Using VIIRS Flood Products,
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Arabameri, A.[Alireza], Saha, S.I.[Sun-Il], Mukherjee, K.[Kaustuv], Blaschke, T.[Thomas], Chen, W.[Wei], Ngo, P.T.T.[Phuong Thao Thi], Band, S.S.[Shahab S.],
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Elsevier DOI 2011
Flood severity mapping, Social media, Crowdsourcing, Volunteered geographic information, Hurricane Harvey BibRef

Landuyt, L.[Lisa], Verhoest, N.E.C.[Niko E. C.], van Coillie, F.M.B.[Frieke M. B.],
Flood Mapping in Vegetated Areas Using an Unsupervised Clustering Approach on Sentinel-1 and -2 Imagery,
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DOI Link 2011
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Cigna, F.[Francesca], Xie, H.J.[Hong-Jie],
Imaging Floods and Glacier Geohazards with Remote Sensing,
RS(12), No. 23, 2020, pp. xx-yy.
DOI Link 2012
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Pulvirenti, L.[Luca], Chini, M.[Marco], Pierdicca, N.[Nazzareno],
InSAR Multitemporal Data over Persistent Scatterers to Detect Floodwater in Urban Areas: A Case Study in Beletweyne, Somalia,
RS(13), No. 1, 2021, pp. xx-yy.
DOI Link 2101
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Munir, B.A.[Bilal Ahmad], Ahmad, S.R.[Sajid Rashid], Rehan, R.[Raja],
Torrential Flood Water Management: Rainwater Harvesting through Relation Based Dam Suitability Analysis and Quantification of Erosion Potential,
IJGI(10), No. 1, 2021, pp. xx-yy.
DOI Link 2101
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Qiu, J.L.[Jun-Liang], Cao, B.[Bowen], Park, E.[Edward], Yang, X.K.[Xian-Kun], Zhang, W.X.[Wen-Xin], Tarolli, P.[Paolo],
Flood Monitoring in Rural Areas of the Pearl River Basin (China) Using Sentinel-1 SAR,
RS(13), No. 7, 2021, pp. xx-yy.
DOI Link 2104
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Pulvirenti, L.[Luca], Squicciarino, G.[Giuseppe], Fiori, E.[Elisabetta], Ferraris, L.[Luca], Puca, S.[Silvia],
A Tool for Pre-Operational Daily Mapping of Floods and Permanent Water Using Sentinel-1 Data,
RS(13), No. 7, 2021, pp. xx-yy.
DOI Link 2104
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Kitajima, N.[Natsumi], Seto, R.[Rie], Yamazaki, D.[Dai], Zhou, X.D.[Xu-Dong], Ma, W.C.[Wen-Chao], Kanae, S.[Shinjiro],
Potential of a SAR Small-Satellite Constellation for Rapid Monitoring of Flood Extent,
RS(13), No. 10, 2021, pp. xx-yy.
DOI Link 2105
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Wania, A.[Annett], Joubert-Boitat, I.[Inès], Dottori, F.[Francesco], Kalas, M.[Milan], Salamon, P.[Peter],
Increasing Timeliness of Satellite-Based Flood Mapping Using Early Warning Systems in the Copernicus Emergency Management Service,
RS(13), No. 11, 2021, pp. xx-yy.
DOI Link 2106
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Zhu, Z.H.[Zhi-Hua], Yang, Y.Y.[Yue-Ying], Cai, Y.P.[Yan-Peng], Yang, Z.F.[Zhi-Feng],
Urban Flood Analysis in Ungauged Drainage Basin Using Short-Term and High-Resolution Remotely Sensed Rainfall Records,
RS(13), No. 11, 2021, pp. xx-yy.
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Yang, Z.K.[Zhong-Kang], Wei, J.[Jinbing], Deng, J.H.[Jian-Hui], Gao, Y.J.[Yun-Jian], Zhao, S.Y.[Si-Yuan], He, Z.L.[Zhi-Liang],
Mapping Outburst Floods Using a Collaborative Learning Method Based on Temporally Dense Optical and SAR Data: A Case Study with the Baige Landslide Dam on the Jinsha River, Tibet,
RS(13), No. 11, 2021, pp. xx-yy.
DOI Link 2106
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Bai, Y.B.[Yan-Bing], Wu, W.Q.[Wen-Qi], Yang, Z.X.[Zheng-Xin], Yu, J.Z.[Jin-Ze], Zhao, B.[Bo], Liu, X.[Xing], Yang, H.[Hanfang], Mas, E.[Erick], Koshimura, S.[Shunichi],
Enhancement of Detecting Permanent Water and Temporary Water in Flood Disasters by Fusing Sentinel-1 and Sentinel-2 Imagery Using Deep Learning Algorithms: Demonstration of Sen1Floods11 Benchmark Datasets,
RS(13), No. 11, 2021, pp. xx-yy.
DOI Link 2106
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Tariq, A.[Aqil], Shu, H.[Hong], Kuriqi, A.[Alban], Siddiqui, S.[Saima], Gagnon, A.S.[Alexandre S.], Lu, L.L.[Lin-Lin], Linh, N.T.T.[Nguyen Thi Thuy], Pham, Q.B.[Quoc Bao],
Characterization of the 2014 Indus River Flood Using Hydraulic Simulations and Satellite Images,
RS(13), No. 11, 2021, pp. xx-yy.
DOI Link 2106
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Brill, F.[Fabio], Schlaffer, S.[Stefan], Martinis, S.[Sandro], Schröter, K.[Kai], Kreibich, H.[Heidi],
Extrapolating Satellite-Based Flood Masks by One-Class Classification: A Test Case in Houston,
RS(13), No. 11, 2021, pp. xx-yy.
DOI Link 2106
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Akiva, P.[Peri], Purri, M.[Matthew], Dana, K.[Kristin], Tellman, B.[Beth], Anderson, T.[Tyler],
H2O-Net: Self-Supervised Flood Segmentation via Adversarial Domain Adaptation and Label Refinement,
WACV21(111-122)
IEEE DOI 2106
Training, Image segmentation, Adaptation models, Time-frequency analysis, Satellites, Image resolution, Annotations BibRef

Katiyar, V.[Vaibhav], Tamkuan, N.[Nopphawan], Nagai, M.[Masahiko],
Near-Real-Time Flood Mapping Using Off-the-Shelf Models with SAR Imagery and Deep Learning,
RS(13), No. 12, 2021, pp. xx-yy.
DOI Link 2106
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Jiang, X.[Xin], Liang, S.J.[Shi-Jing], He, X.Y.[Xin-Yue], Ziegler, A.D.[Alan D.], Lin, P.R.[Pei-Rong], Pan, M.[Ming], Wang, D.S.[Da-Shan], Zou, J.Y.[Jun-Yu], Hao, D.L.[Da-Lei], Mao, G.Q.[Gan-Quan], Zeng, Y.L.[Ye-Lu], Yin, J.[Jie], Feng, L.[Lian], Miao, C.Y.[Chi-Yuan], Wood, E.F.[Eric F.], Zeng, Z.Z.[Zhen-Zhong],
Rapid and large-scale mapping of flood inundation via integrating spaceborne synthetic aperture radar imagery with unsupervised deep learning,
PandRS(178), 2021, pp. 36-50.
Elsevier DOI 2108
Flood inundation, Sentinel-1, Unsupervised machine learning, Google Earth Engine, Disaster assessment BibRef

Wang, S.J.[Shi-Jin], Yang, Y.D.[Yuan-De], Gong, W.Y.[Wen-Yu], Che, Y.J.[Yan-Jun], Ma, X.G.[Xing-Gang], Xie, J.[Jia],
Reason Analysis of the Jiwenco Glacial Lake Outburst Flood (GLOF) and Potential Hazard on the Qinghai-Tibetan Plateau,
RS(13), No. 16, 2021, pp. xx-yy.
DOI Link 2109
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Konapala, G.[Goutam], Kumar, S.V.[Sujay V.], Ahmad, S.K.[Shahryar Khalique],
Exploring Sentinel-1 and Sentinel-2 diversity for flood inundation mapping using deep learning,
PandRS(180), 2021, pp. 163-173.
Elsevier DOI 2109
Flood inundation mapping, Deep learning, Segmentation, Hydrology BibRef

Vojtek, M.[Matej], Vojteková, J.[Jana], Pham, Q.B.[Quoc Bao],
GIS-Based Spatial and Multi-Criteria Assessment of Riverine Flood Potential: A Case Study of the Nitra River Basin, Slovakia,
IJGI(10), No. 9, 2021, pp. xx-yy.
DOI Link 2109
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Ali, S.[Sikandar], Cheema, M.J.M.[Muhammad Jehanzeb Masud], Waqas, M.M.[Muhammad Mohsin], Waseem, M.[Muhammad], Leta, M.K.[Megersa Kebede], Qamar, M.U.[Muhammad Uzair], Awan, U.K.[Usman Khalid], Bilal, M.[Muhammad], ur Rahman, M.H.[Muhammad Habib],
Flood Mitigation in the Transboundary Chenab River Basin: A Basin-Wise Approach from Flood Forecasting to Management,
RS(13), No. 19, 2021, pp. xx-yy.
DOI Link 2110
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Liu, Z.[Zhen], Jr, R.G.P.[Robert Gilmore Pontius],
The Total Operating Characteristic from Stratified Random Sampling with an Application to Flood Mapping,
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Nagai, H.[Hiroto], Abe, T.[Takahiro], Ohki, M.[Masato],
SAR-Based Flood Monitoring for Flatland with Frequently Fluctuating Water Surfaces: Proposal for the Normalized Backscatter Amplitude Difference Index (NoBADI),
RS(13), No. 20, 2021, pp. xx-yy.
DOI Link 2110
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Le Moine, N.[Nicolas], Mahdade, M.[Mounir],
A Preliminary Assessment of a Newly-Defined Multispectral Hue Space for Retrieving River Depth with Optical Imagery and In Situ Calibration Data,
RS(13), No. 21, 2021, pp. xx-yy.
DOI Link 2112
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Pertiwi, A.P.[Avi Putri], Roth, A.[Achim], Schaffhauser, T.[Timo], Bhola, P.K.[Punit Kumar], Reuß, F.[Felix], Stettner, S.[Samuel], Kuenzer, C.[Claudia], Disse, M.[Markus],
Monitoring the Spring Flood in Lena Delta with Hydrodynamic Modeling Based on SAR Satellite Products,
RS(13), No. 22, 2021, pp. xx-yy.
DOI Link 2112
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Yang, W.T.[Wen-Tao], Gao, F.[Fan], Xu, T.[Tianhe], Wang, N.Z.[Na-Zi], Tu, J.S.[Jin-Sheng], Jing, L.[Lili], Kong, Y.H.[Ya-Hui],
Daily Flood Monitoring Based on Spaceborne GNSS-R Data: A Case Study on Henan, China,
RS(13), No. 22, 2021, pp. xx-yy.
DOI Link 2112
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Falck, A.[Aline], Tomasella, J.[Javier], Papa, F.[Fabrice],
Assessing the Potential of Upcoming Satellite Altimeter Missions in Operational Flood Forecasting Systems,
RS(13), No. 21, 2021, pp. xx-yy.
DOI Link 2112
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Chen, S.[Shujie], Huang, W.L.[Wen-Li], Chen, Y.[Yumin], Feng, M.[Mei],
An Adaptive Thresholding Approach toward Rapid Flood Coverage Extraction from Sentinel-1 SAR Imagery,
RS(13), No. 23, 2021, pp. xx-yy.
DOI Link 2112
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Sipelgas, L.[Liis], Aavaste, A.[Age], Uiboupin, R.[Rivo],
Mapping Flood Extent and Frequency from Sentinel-1 Imagery during the Extremely Warm Winter of 2020 in Boreal Floodplains and Forests,
RS(13), No. 23, 2021, pp. xx-yy.
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Kim, J.[Junwoo], Kim, H.[Hwisong], Jeon, H.Y.[Hyung-Yun], Jeong, S.H.[Seung-Hwan], Song, J.[Juyoung], Vadivel, S.K.P.[Suresh Krishnan Palanisamy], Kim, D.J.[Duk-Jin],
Synergistic Use of Geospatial Data for Water Body Extraction from Sentinel-1 Images for Operational Flood Monitoring across Southeast Asia Using Deep Neural Networks,
RS(13), No. 23, 2021, pp. xx-yy.
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Yokoya, N.[Naoto], Yamanoi, K.[Kazuki], He, W.[Wei], Baier, G.[Gerald], Adriano, B.[Bruno], Miura, H.[Hiroyuki], Oishi, S.[Satoru],
Breaking Limits of Remote Sensing by Deep Learning From Simulated Data for Flood and Debris-Flow Mapping,
GeoRS(60), 2022, pp. 1-15.
IEEE DOI 2112
Remote sensing, Strain, Floods, Data models, Training data, Optical sensors, Optical imaging, numerical simulation BibRef

Zhang, S.C.[Shuang-Cheng], Ma, Z.M.[Zhong-Min], Li, Z.H.[Zhen-Hong], Zhang, P.F.[Peng-Fei], Liu, Q.[Qi], Nan, Y.[Yang], Zhang, J.J.[Jing-Jiang], Hu, S.W.[Sheng-Wei], Feng, Y.X.[Yu-Xuan], Zhao, H.[Hebin],
Using CYGNSS Data to Map Flood Inundation during the 2021 Extreme Precipitation in Henan Province, China,
RS(13), No. 24, 2021, pp. xx-yy.
DOI Link 2112
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Zhang, L.C.[Lian-Chong], Xia, J.[Junshi],
Flood Detection Using Multiple Chinese Satellite Datasets during 2020 China Summer Floods,
RS(14), No. 1, 2022, pp. xx-yy.
DOI Link 2201
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Hernández, D.[Daniel], Cecilia, J.M.[José M.], Cano, J.C.[Juan-Carlos], Calafate, C.T.[Carlos T.],
Flood Detection Using Real-Time Image Segmentation from Unmanned Aerial Vehicles on Edge-Computing Platform,
RS(14), No. 1, 2022, pp. xx-yy.
DOI Link 2201
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Yoon, S.S.[Seong-Sim], Lim, S.H.[Sang-Hun],
Analyzing the Application of X-Band Radar for Improving Rainfall Observation and Flood Forecasting in Yeongdong, South Korea,
RS(14), No. 1, 2022, pp. xx-yy.
DOI Link 2201
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Ulloa, N.I.[Noel Ivan], Yun, S.H.[Sang-Ho], Chiang, S.H.[Shou-Hao], Furuta, R.[Ryoichi],
Sentinel-1 Spatiotemporal Simulation Using Convolutional LSTM for Flood Mapping,
RS(14), No. 2, 2022, pp. xx-yy.
DOI Link 2201
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Elkhrachy, I.[Ismail],
Flash Flood Water Depth Estimation Using SAR Images, Digital Elevation Models, and Machine Learning Algorithms,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link 2202
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Tulbure, M.G.[Mirela G.], Broich, M.[Mark], Perin, V.[Vinicius], Gaines, M.[Mollie], Ju, J.C.[Jun-Chang], Stehman, S.V.[Stephen V.], Pavelsky, T.[Tamlin], Masek, J.G.[Jeffrey G.], Yin, S.[Simon], Mai, J.[Joachim], Betbeder-Matibet, L.[Luc],
Can we detect more ephemeral floods with higher density harmonized Landsat Sentinel 2 data compared to Landsat 8 alone?,
PandRS(185), 2022, pp. 232-246.
Elsevier DOI 2202
Flooding, Ephemeral floods, Landsat, Sentinel 2, Analysis ready data, Harmonized data, Drylands BibRef

Colosio, P.[Paolo], Tedesco, M.[Marco], Tellman, E.[Elizabeth],
Flood Monitoring Using Enhanced Resolution Passive Microwave Data: A Test Case over Bangladesh,
RS(14), No. 5, 2022, pp. xx-yy.
DOI Link 2203
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Ammirati, L.[Lorenzo], Chirico, R.[Rita], di Martire, D.[Diego], Mondillo, N.[Nicola],
Application of Multispectral Remote Sensing for Mapping Flood-Affected Zones in the Brumadinho Mining District (Minas Gerais, Brasil),
RS(14), No. 6, 2022, pp. xx-yy.
DOI Link 2204
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Bellido-Leiva, F.J.[Francisco J.], Lusardi, R.A.[Robert A.], Lund, J.R.[Jay R.],
Quantification of Off-Channel Inundated Habitat for Pacific Chinook Salmon (Oncorhynchus tshawytscha) along the Sacramento River, California, Using Remote Sensing Imagery,
RS(14), No. 6, 2022, pp. xx-yy.
DOI Link 2204
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Tiampo, K.F.[Kristy F.], Huang, L.[Lingcao], Simmons, C.[Conor], Woods, C.[Clay], Glasscoe, M.T.[Margaret T.],
Detection of Flood Extent Using Sentinel-1A/B Synthetic Aperture Radar: An Application for Hurricane Harvey, Houston, TX,
RS(14), No. 9, 2022, pp. xx-yy.
DOI Link 2205
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Tew, Y.L.[Yi Lin], Tan, M.L.[Mou Leong], Juneng, L.[Liew], Chun, K.P.[Kwok Pan], bin Hassan, M.H.[Mohamad Hafiz], bin Osman, S.[Sazali], Samat, N.[Narimah], Chang, C.K.[Chun Kiat], Kabir, M.H.[Muhammad Humayun],
Rapid Extreme Tropical Precipitation and Flood Inundation Mapping Framework (RETRACE): Initial Testing for the 2021-2022 Malaysia Flood,
IJGI(11), No. 7, 2022, pp. xx-yy.
DOI Link 2208
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Yang, Z.L.[Zheng-Li], Yuan, X.Y.[Xin-Yue], Liu, C.[Chao], Nie, R.H.[Rui-Hua], Liu, T.G.[Tie-Gang], Dai, X.A.[Xiao-Ai], Ma, L.[Lei], Tang, M.[Min], Xu, Y.[Yina], Lu, H.[Heng],
Meta-Analysis and Visualization of the Literature on Early Identification of Flash Floods,
RS(14), No. 14, 2022, pp. xx-yy.
DOI Link 2208
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Wang, Z.R.[Zi-Rui], Xie, F.[Fei], Ling, F.[Feng], Du, Y.[Yun],
Monitoring Surface Water Inundation of Poyang Lake and Dongting Lake in China Using Sentinel-1 SAR Images,
RS(14), No. 14, 2022, pp. xx-yy.
DOI Link 2208
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Huang, M.[Minmin], Jin, S.G.[Shuang-Gen],
Backscatter Characteristics Analysis for Flood Mapping Using Multi-Temporal Sentinel-1 Images,
RS(14), No. 15, 2022, pp. xx-yy.
DOI Link 2208
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Foroughnia, F.[Fatemeh], Alfieri, S.M.[Silvia Maria], Menenti, M.[Massimo], Lindenbergh, R.[Roderik],
Evaluation of SAR and Optical Data for Flood Delineation Using Supervised and Unsupervised Classification,
RS(14), No. 15, 2022, pp. xx-yy.
DOI Link 2208
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Qiu, J.[Juan], Han, D.F.[Dong-Feng], Li, R.[Rendong], Xiao, Y.[Ying], Zhu, H.[Hong], Xia, J.[Jing], Jiang, J.[Jie], Han, Y.F.[Yi-Fei], Shao, Q.H.[Qi-Hui], Yan, Y.[Yi], Li, X.D.[Xiao-Dong],
Satellite Imagery-Based Identification of High-Risk Areas of Schistosome Intermediate Snail Hosts Spread after Flood,
RS(14), No. 15, 2022, pp. xx-yy.
DOI Link 2208
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Bauer-Marschallinger, B.[Bernhard], Cao, S.[Senmao], Tupas, M.E.[Mark Edwin], Roth, F.[Florian], Navacchi, C.[Claudio], Melzer, T.[Thomas], Freeman, V.[Vahid], Wagner, W.[Wolfgang],
Satellite-Based Flood Mapping through Bayesian Inference from a Sentinel-1 SAR Datacube,
RS(14), No. 15, 2022, pp. xx-yy.
DOI Link 2208
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Navacchi, C.[Claudio], Cao, S.[Senmao], Bauer-Marschallinger, B.[Bernhard], Snoeij, P.[Paul], Small, D.[David], Wagner, W.[Wolfgang],
Utilising Sentinel-1's orbital stability for efficient pre-processing of sigma nought backscatter,
PandRS(192), 2022, pp. 130-141.
Elsevier DOI 2209
Sentinel-1, Synthetic Aperture Radar (SAR), Ground Range Detected (GRD), Georeferencing, Orbital tube BibRef

Atefi, M.R.[Mujeeb Rahman], Miura, H.[Hiroyuki],
Detection of Flash Flood Inundated Areas Using Relative Difference in NDVI from Sentinel-2 Images: A Case Study of the August 2020 Event in Charikar, Afghanistan,
RS(14), No. 15, 2022, pp. xx-yy.
DOI Link 2208
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Hamunyela, E.[Eliakim], Hipondoka, M.[Martin], Persendt, F.[Frans], Sevelia-Nghiyalwa, H.[Hilma], Thomas, C.[Chris], Matengu, K.[Kenneth],
Spatio-temporal characterization of surface water dynamics with Landsat in endorheic Cuvelai-Etosha Basin (1990-2021),
PandRS(191), 2022, pp. 68-84.
Elsevier DOI 2208
Surface water, Landsat, Cuvelai-Etosha, Endorheic basin, Flooding, Angola, Namibia BibRef

Gu, L.[Lei], Gu, Z.Y.[Zi-Ye], Guo, Q.[Qiang], Fang, W.[Wei], Zhang, Q.Y.[Qian-Yi], Sun, H.W.[Huai-Wei], Yin, J.[Jiabo], Zhou, J.Z.[Jian-Zhong],
Can Satellite and Atmospheric Reanalysis Products Capture Compound Moist Heat Stress-Floods?,
RS(14), No. 18, 2022, pp. xx-yy.
DOI Link 2209
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Li, S.[Sanmei], Sun, D.L.[Dong-Lian], Goldberg, M.D.[Mitchell D.], Kalluri, S.[Satya], Sjoberg, B.[Bill], Lindsey, D.[Dan], Hoffman, J.P.[Jay P.], DeWeese, M.[Mike], Connelly, B.[Brian], Mckee, P.[Paul], Lander, K.[Kris],
A downscaling model for derivation of 3-D flood products from VIIRS imagery and SRTM/DEM,
PandRS(192), 2022, pp. 279-298.
Elsevier DOI 2209
VIIRS, Water Fraction, Downscaling Model, 3-D Flood Products, SRTM/DEM BibRef

Zhang, L.G.[Li-Gang], Hu, Q.[Qiao], Tang, Z.H.[Zheng-Hong],
Using Sentinel-2 Imagery and Machine Learning Algorithms to Assess the Inundation Status of Nebraska Conservation Easements during 2018-2021,
RS(14), No. 17, 2022, pp. xx-yy.
DOI Link 2209
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Song, D.M.[Dong-Mei], Zhang, Q.Q.[Qi-Qi], Wang, B.[Bin], Yin, C.[Cong], Xia, J.M.[Jun-Ming],
A Novel Dual-Branch Neural Network Model for Flood Monitoring in South Asia Based on CYGNSS Data,
RS(14), No. 20, 2022, pp. xx-yy.
DOI Link 2211
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Wu, H.[Han], Song, H.[Huina], Huang, J.H.[Jian-Hua], Zhong, H.[Hua], Zhan, R.H.[Rong-Hui], Teng, X.Y.[Xu-Yang], Qiu, Z.Y.[Zhao-Yang], He, M.[Meilin], Cao, J.Y.[Jia-Yi],
Flood Detection in Dual-Polarization SAR Images Based on Multi-Scale Deeplab Model,
RS(14), No. 20, 2022, pp. xx-yy.
DOI Link 2211
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Tran, K.H.[Khuong H.], Menenti, M.[Massimo], Jia, L.[Li],
Surface Water Mapping and Flood Monitoring in the Mekong Delta Using Sentinel-1 SAR Time Series and Otsu Threshold,
RS(14), No. 22, 2022, pp. xx-yy.
DOI Link 2212
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Lv, S.[Suna], Meng, L.S.[Ling-Sheng], Edwing, D.[Deanna], Xue, S.[Sihan], Geng, X.[Xupu], Yan, X.H.[Xiao-Hai],
High-Performance Segmentation for Flood Mapping of HISEA-1 SAR Remote Sensing Images,
RS(14), No. 21, 2022, pp. xx-yy.
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Albertini, C.[Cinzia], Gioia, A.[Andrea], Iacobellis, V.[Vito], Manfreda, S.[Salvatore],
Detection of Surface Water and Floods with Multispectral Satellites,
RS(14), No. 23, 2022, pp. xx-yy.
DOI Link 2212
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Baghermanesh, S.S.[Shadi Sadat], Jabari, S.[Shabnam], McGrath, H.[Heather],
Urban Flood Detection Using TerraSAR-X and SAR Simulated Reflectivity Maps,
RS(14), No. 23, 2022, pp. xx-yy.
DOI Link 2212
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Kim, J.[Junwoo], Kim, H.[Hwisong], Kim, D.J.[Duk-Jin], Song, J.[Juyoung], Li, C.L.[Cheng-Lei],
Deep Learning-Based Flood Area Extraction for Fully Automated and Persistent Flood Monitoring Using Cloud Computing,
RS(14), No. 24, 2022, pp. xx-yy.
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Salem, A.[Abdella], Hashemi-Beni, L.[Leila],
Inundated Vegetation Mapping Using SAR Data: A Comparison of Polarization Configurations of UAVSAR L-Band and Sentinel C-Band,
RS(14), No. 24, 2022, pp. xx-yy.
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Brazda, S.[Steven], Šraj, M.[Mojca], Bezak, N.[Nejc],
Classification of Floods in Europe and North America with Focus on Compound Events,
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DOI Link 2301
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Vavassori, A.[Alberto], Carrion, D.[Daniela], Zaragozi, B.[Benito], Migliaccio, F.[Federica],
VGI and Satellite Imagery Integration for Crisis Mapping of Flood Events,
IJGI(11), No. 12, 2022, pp. xx-yy.
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Li, M.[Mingke], McGrath, H.[Heather], Stefanakis, E.[Emmanuel],
Multi-Scale Flood Mapping under Climate Change Scenarios in Hexagonal Discrete Global Grids,
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Gokon, H.[Hideomi], Endo, F.[Fuyuki], Koshimura, S.[Shunichi],
Detecting Urban Floods with Small and Large Scale Analysis of ALOS-2/PALSAR-2 Data,
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DOI Link 2301
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Wei, H.H.[Hao-Han], Yu, T.N.[Tong-Ning], Tu, J.S.[Jin-Sheng], Ke, F.[Fuyang],
Detection and Evaluation of Flood Inundation Using CYGNSS Data during Extreme Precipitation in 2022 in Guangdong Province, China,
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Lyu, J.Q.[Ji-Qiang], Yin, S.S.[Shan-Shan], Sun, Y.T.[Yu-Tong], Wang, K.X.[Ke-Xin], Luo, P.P.[Ping-Ping], Meng, X.L.[Xiao-Lan],
Flood Runoff Simulation under Changing Environment, Based on Multiple Satellite Data in the Jinghe River Basin of the Loess Plateau, China,
RS(15), No. 3, 2023, pp. xx-yy.
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Burshtynska, K.[Khrystyna], Kokhan, S.[Svitlana], Pfeifer, N.[Norbert], Halochkin, M.[Maksym], Zayats, I.[Iryna],
Hydrological Modeling for Determining Flooded Land from Unmanned Aerial Vehicle Images: Case Study at the Dniester River,
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Kimijima, S.[Satomi], Nagai, M.[Masahiko],
High Spatiotemporal Flood Monitoring Associated with Rapid Lake Shrinkage Using Planet Smallsat and Sentinel-1 Data,
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Flood Monitoring in the Middle and Lower Basin of the Yangtze River Using Google Earth Engine and Machine Learning Methods,
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Zhao, Z.G.[Zhong-Guo], Hu, C.L.[Chu-Li], Wang, K.[Ke], Zhang, Y.X.[Yi-Xiao], Xu, Z.Y.[Zhang-Yan], Ding, X.[Xuan],
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Applying Reconstructed Daily Water Storage and Modified Wetness Index to Flood Monitoring: A Case Study in the Yangtze River Basin,
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A Web GIS Platform to Modeling, Simulate and Analyze Flood Events: The RiverCure Portal,
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Breznik, J.[Jana], Oštir, K.[Krištof], Ivacic, M.[Matjaž], Rak, G.[Gašper],
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Hamouda, M.A.[Mohamed A.], Hinge, G.[Gilbert], Yemane, H.S.[Henok S.], Mosteka, H.A.[Hasan Al], Makki, M.[Mohammed], Mohamed, M.M.[Mohamed M.],
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Cerbelaud, A., Roupioz, L., Blanchet, G., Breil, P., Briottet, X.,
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Losè, L.T.[L. Teppati], Chiabrando, F., Tonolo, F.G.[F. Giulio], Lingua, A.,
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ISPRS21(B3-2021: 727-734).
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Jony, R.I.[Rabiul Islam], Woodley, A.[Alan], Perrin, D.[Dimitri],
Fusing Visual Features and Metadata to Detect Flooding in Flickr Images,
DICTA20(1-8)
IEEE DOI 2201
Visualization, Social networking (online), Multimedia Web sites, Metadata, Feature extraction, Computational efficiency, Floods, Information retrieval BibRef

Muckley, L.[Leo], Garforth, J.[James],
Multi-input Convlstm for Flood Extent Prediction,
MAES20(75-85).
Springer DOI 2103
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Barz, B.[Björn], Schröter, K.[Kai], Kra, A.C.[Ann-Christin], Denzler, J.[Joachim],
Finding Relevant Flood Images on Twitter Using Content-based Filters,
MAES20(5-14).
Springer DOI 2103
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Said, A.[Abdullah], Shaat, O.[Omar], Su, P.H.[Po-Hsuan], Bogden, P.[Philip], Kraig, R.[Robert], Bosch, M.[Marc],
Understanding Flooding Detection Using Overhead Imagery - Lessons Learned,
ISVC20(I:696-706).
Springer DOI 2103
BibRef

Rambour, C., Audebert, N., Koeniguer, E., Le Saux, B., Crucianu, M., Datcu, M.,
Flood Detection In Time Series of Optical and Sar Images,
ISPRS20(B2:1343-1346).
DOI Link 2012
Ts - Cipa BibRef

Gasica, T.A., Bioresita, F., Murtiyoso, A.,
Identification of Temporary Surface Water Using Sentinel-1 Sar Data, Case Study: Sentani Flash Flooding, Indonesia,
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DOI Link 2012
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Kapilaratne, R.G.C.J., Kaneta, S.,
Towards An Automated Flood Area Extraction From High Resolution Satellite Images,
ISPRS20(B3:97-104).
DOI Link 2012
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Sipelgas, L., Aavaste, A., Uiboupin, R.,
Mapping Recurrent Flooding Zone Along Estonian Inland Waters From Sentinel-1 and -2,
ISPRS20(B3:627-632).
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Tavus, B., Kocaman, S., Nefeslioglu, H.A., Gokceoglu, C.,
A Fusion Approach for Flood Mapping Using Sentinel-1 and Sentinel-2 Datasets,
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Thakur, P.K., Ranjan, R., Singh, S., Dhote, P.R., Sharma, V., Srivastav, V., Dhasmana, M., Aggarwal, S.P., Chauhan, P., Nikam, B.R., Garg, V., Chouksey, A.,
Synergistic Use of Remote Sensing, GIS and Hydrological Models For Study of August 2018 Kerala Floods,
ISPRS20(B3:1263-1270).
DOI Link 2012
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de la Cruz, R.M., Olfindo Jr., N.T., Felicen, M.M., Borlongan, N.J.B., Difuntorum, J.K.L., Marciano Jr., J.J.S.,
Near-realtime Flood Detection From Multi-temporal Sentinel Radar Images Using Artificial Intelligence,
ISPRS20(B3:1663-1670).
DOI Link 2012
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Papila, I., Alganci, U., Sertel, E.,
Sentinel-1 Based Flood Mapping Using Interferometric Coherence And Intensity Change Detection Approach,
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Bonafilia, D., Tellman, B., Anderson, T., Issenberg, E.,
Sen1Floods11: a georeferenced dataset to train and test deep learning flood algorithms for Sentinel-1,
EarthVision20(835-845)
IEEE DOI 2008
Remote sensing, Earth, Artificial satellites, Training, Data models, Sensors, Machine learning BibRef

Otieno, O.M., Abdillahi, H.S., Wambui, E.M., Kiprono, K.S.,
Flood Impact-based Forecasting for Early Warning and Early Action In Tana River Basin, Kenya,
Gi4DM19(293-300).
DOI Link 1912
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Panidi, E., Popova, K., Tsepelev, V.,
GIS-based Mapping of Estimated Flood Inundation Area, Geometrical Aspect,
Gi4DM19(307-309).
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Reksten, J.H., Salberg, A.B., Solberg, R.,
Flood Detection in Norway Based On Sentinel-1 Sar Imagery,
Gi4DM19(349-355).
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Toshiharu, K., Narantsetseg, C.,
Long Term Changes in Flooding Around Gifu City,
Gi4DM19(421-427).
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Zelentsov, V.A., Potryasaev, S.A., Pimanov, I.Y., Ponomarenko, M.R.,
Integrated Use of GIS, Remote Sensing Data and a Set of Models For Operational Flood Forecasting,
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Sunar, A.F., Yagmur, N., Dervisoglu, A.,
Flood Analysis With Remote Sensing Data - a Case Study: Maritsa River, Edirne,
Gi4DM19(497-502).
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Bibi, T., Nawaz, F., Abdul Rahman, A., Latif, A.,
Flood Hazard Assessment Using Participatory Approach and Weighted Overlay Methods,
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Jamali, A., Abdul Rahman, A.,
Flood Mapping Using Synthetic Aperture Radar: a Case Study of Ramsar Flash Flood,
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Kaoje, I.U., Abdul Rahman, M.Z., Tam, T.H., Mohd Salleh, M.R.,
An Indicator-based Approach for Micro-scale Physical Flood Vulnerability Mapping,
GGT19(331-337).
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Lahsaini, M., Tabyaoui, H., El Hammichi, F.,
Big Data Processing and Analysis Using Multi-temporal Sentinel 1 Data To Manage Floods in North of Morocco,
GGT19(359-363).
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Ramsewak, D., Maharaj, B.,
Extent Mapping of a Major Flooding Event On The Island of Trinidad Using Space-borne Synthetic Aperture Radar,
GGT19(527-530).
DOI Link 1912
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Ganji, K., Gharachelou, S., Ahmadi, A.,
Urban's River Flood Analysing Using Sentinel-1 Data Case Study: (gorganrood, Aq'qala),
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Hosseiny, B., Ghasemian, N., Amini, J.,
A Convolutional Neural Network for Flood Mapping Using Sentinel-1 And Srtm Dem Data: Case Study in Poldokhtar-iran,
SMPR19(527-533).
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Khalifeh Soltanian, F., Abbasi, M., Riyahi Bakhtyari, H.R.,
Flood Monitoring Using Ndwi and Mndwi Spectral Indices: a Case Study Of Aghqala Flood-2019, Golestan Province, Iran,
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Kianfar, N.,
The Applicability of Dual Polarized Sentinel-1 SAR Data for Detection Of Flooded Areas in Pol-e Dokhtar, Lorestan, Iran,
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Nasirzadehdizaji, R., Akyuz, D.E., Cakir, Z.,
Flood Mapping and Permanent Water Bodies Change Detection Using Sentinel Sar Data,
SMPR19(797-801).
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Pouyanfar, S., Tao, Y., Sadiq, S., Tian, H., Tu, Y., Wang, T., Chen, S., Shyu, M.,
Unconstrained Flood Event Detection Using Adversarial Data Augmentation,
ICIP19(155-159)
IEEE DOI 1910
Flood event detection, deep learning, style transfer, generative adversarial networks BibRef

Kumar, K., Ledoux, H., Stoter, J.,
Dynamic 3D Visualization of Floods: Case of the Netherlands,
GeoInfo18(83-87).
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Wu, Y., Liu, Z., Xu, W., Feng, J., Palaiahnakote, S., Lu, T.,
Context-Aware Attention LSTM Network for Flood Prediction,
ICPR18(1301-1306)
IEEE DOI 1812
Context modeling, Rivers, Predictive models, Training, Hydrology, Support vector machines BibRef

Wu, Y.R.[Yi-Rui], Xu, W.G.[Wei-Gang], Yu, Q.H.[Qing-Han], Feng, J.[Jun], Lu, T.[Tong],
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Springer DOI 1901
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Wu, Y.R.[Yi-Rui], Xu, W.G.[Wei-Gang], Feng, J.[Jun], Palaiahnakote, S., Lu, T.[Tong],
Local and Global Bayesian Network based Model for Flood Prediction,
ICPR18(225-230)
IEEE DOI 1812
Hydrology, Bayes methods, Rivers, Predictive models, Robustness, Data models, Computational modeling BibRef

de O. Werneck, R.[Rafael], Dourado, I.C.[Icaro C.], Fadel, S.G.[Samuel G.], Tabbone, S.[Salvatore], da Silva Torres, R.[Ricardo],
Graph-Based Early-Fusion for Flood Detection,
ICIP18(1048-1052)
IEEE DOI 1809
Feature extraction, Social network services, Visualization, Principal component analysis, Monitoring, Streaming media, image representation BibRef

Boori, M.S., Choudhary, K., Evers, M., Kupriyanov, A.,
Food Vulnerability And Alluvial Farming for Food Security in Central Dry Zone Area of Myanmar,
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Arkhipkin, O.P., Sagatdinova, G.N.,
Possibilities of the Joint Use of Optical And Radar Data in Flood Space Monitoring,
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Gandini, A., Prieto, I., Garmendia, L., San-José, J.T., Egusquiza, A.,
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Kwak, Y.J.,
Flash Flood Mapping for Mountain Streams Using High-resolution Alos-2 Data,
Gi4DM18(307-312).
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Kwak, Y., Muraoka, K., Asai, K.,
Community-based Nationwide Capacity Building for GIS-based Integrated Flood Management,
Gi4DM18(313-318).
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Zakaria, S., Mahadi, M.R., Abdullah, A.F., Abdan, K.,
Aerial Platform Reliability for Flood Monitoring Under Various Weather Conditions: A Review,
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Al-Akad, S., Akensous, Y., Hakdaoui, M.,
Mapping Infected Area After A Flash-flooding Storm Using Multi Criteria Analysis And Spectral Indices,
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Chaabani, C.[Chayma], Abdelfattah, R.[Riadh],
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Ichim, L.[Loretta], Popescu, D.[Dan],
Monitoring and Evaluation of Flooded Areas Based on Fused Texture Descriptors,
ACIVS17(349-360).
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Ichim, L.[Loretta], Popescu, D.[Dan],
Combining Color Fractal with LBP Information for Flood Segmentation in UAV-Based Images,
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Sarker, C., Alvarez, L.M., Woodley, A.,
Integrating Recursive Bayesian Estimation with Support Vector Machine to Map Probability of Flooding from Multispectral Landsat Data,
DICTA16(1-8)
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Australia BibRef

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A Flood Detection and Warning System Based on Video Content Analysis,
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Lateral Flooding Associated To Wave Flood Generation On River Surface,
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Advance flood detection and notification system based on sensor technology and machine learning algorithm,
WSSIP15(105-108)
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floods BibRef

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Mcdougall, K., Temple-Watts, P.,
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Chapter on Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR continues in
Flood Damage Analysis, Impacts, Economic .