152
Views
1
CrossRef citations to date
0
Altmetric
Research article

Flood sequence mapping with multimodal remote sensing under the influence of dense vegetation

& ORCID Icon
Pages 1059-1078 | Received 18 Sep 2023, Accepted 10 Jan 2024, Published online: 02 Feb 2024

References

  • Afshari, S., A. A. Tavakoly, M. A. Rajib, X. Zheng, M. L. Follum, E. Omranian, and B. M. Fekete. 2018. “Comparison of New Generation Low-Complexity Flood Inundation Mapping Tools with a Hydrodynamic Model.” Canadian Journal of Fisheries and Aquatic Sciences 556:539–556. https://doi.org/10.1016/j.jhydrol.2017.11.036.
  • Alabbad, Y., and I. Demir. 2022. “Comprehensive Flood Vulnerability Analysis in Urban Communities: Iowa Case Study.” International Journal of Disaster Risk Reduction 74:102955. https://doi.org/10.1016/J.IJDRR.2022.102955.
  • Alabbad, Y., E. Yildirim, and I. Demir. 2022. “Flood Mitigation Data Analytics and Decision Support Framework: Iowa Middle Cedar Watershed Case Study.” Science of the Total Environment 814:152768. https://doi.org/10.1016/J.SCITOTENV.2021.152768.
  • Ali, A. U., and R. Ogie. 2017. “Social Media and Disasters: Highlighting Some Wicked Problems [Leading Edge].” IEEE Technology and Society Magazine 36 (4): 41–43. https://doi.org/10.1109/MTS.2017.2763450.
  • Avand, M., H. Moradi, and M. R. Lasboyee. 2021. “Using Machine Learning Models, Remote Sensing, and GIS to Investigate the Effects of Changing Climates and Land Uses on Flood Probability.” Canadian Journal of Fisheries and Aquatic Sciences 595:125663. https://doi.org/10.1016/J.JHYDROL.2020.125663.
  • Baeza, S., E. Vélez-Martin, D. De Abelleyra, S. Banchero, F. Gallego, J. Schirmbeck, S. Veron, et al. 2022. “Two decades of land cover mapping in the Río de la Plata grassland region: The MapBiomas Pampa initiative.” Remote Sensing Applications: Society & Environment 28:100834. https://doi.org/10.1016/J.RSASE.2022.100834.
  • Bair, E. H., J. Dozier, K. Rittger, T. Stillinger, W. Kleiber, and R. E. Davis. 2023. “How Do Tradeoffs in Satellite Spatial and Temporal Resolution Impact Snow Water Equivalent Reconstruction?” The Cryosphere 17 (7): 2629–2643. https://doi.org/10.5194/TC-17-2629-2023.
  • Billah, M., A. K. M. S. Islam, W. B. Mamoon, and M. R. Rahman. 2023. “Random Forest Classifications for Landuse Mapping to Assess Rapid Flood Damage Using Sentinel-1 and Sentinel-2 Data.” Remote Sensing Applications: Society & Environment 30:100947. https://doi.org/10.1016/J.RSASE.2023.100947.
  • Cao, H., H. Zhang, C. Wang, and B.-Z. Water. 2019. “Undefined. (2019). Operational Flood Detection Using Sentinel-1 SAR Data Over Large Areas.” Water 11 (4): 786. https://doi.org/10.3390/w11040786.
  • Cavallo, C., M. N. Papa, M. Gargiulo, G. Palau-Salvador, P. Vezza, and G. Ruello. 2021. “Continuous Monitoring of the Flooding Dynamics in the Albufera Wetland (Spain) by Landsat-8 and Sentinel-2 Datasets.” Remote Sensing 13 (17): 3525. https://doi.org/10.3390/RS13173525.
  • Costache, R., Q. B. Pham, E. Corodescu-Roşca, C. Cîmpianu, H. Hong, N. T. Thuy Linh, C. M. Fai, et al. 2020. “Using GIS, Remote Sensing, and Machine Learning to Highlight the Correlation Between the Land-Use/land-Cover Changes and Flash-Flood Potential.” Remote Sensing 12 (9): 1422. https://doi.org/10.3390/RS12091422.
  • Costache, R., Q. B. Pham, E. Sharifi, N. T. T. Linh, S. I. Abba, M. Vojtek, J. Vojteková, P. T. T. Nhi, and D. N. Khoi. 2019. “Flash-Flood Susceptibility Assessment Using Multi-Criteria Decision Making and Machine Learning Supported by Remote Sensing and GIS Techniques.” Remote Sensing 12 (1): 106. https://doi.org/10.3390/RS12010106.
  • Dalla Mura, M., S. Prasad, F. Pacifici, P. Gamba, J. Chanussot, and J. A. Benediktsson. 2015. “Challenges and Opportunities of Multimodality and Data Fusion in Remote Sensing.” Proceedings of the IEEE 103 (9): 1585–1601. https://doi.org/10.1109/JPROC.2015.2462751.
  • Demir, I., H. Conover, W. F. Krajewski, B. C. Seo, R. Goska, Y. He, M. F. McEniry, S. J. Graves, and W. Petersen. 2015. “Data-Enabled Field Experiment Planning, Management, and Research Using Cyberinfrastructure.” Journal of Hydrometeorology 16 (3): 1155–1170. https://doi.org/10.1175/JHM-D-14-0163.1.
  • Durgun, Y. Ö., A. Gobin, G. Duveiller, and B. Tychon. 2020. “A Study on Trade-Offs Between Spatial Resolution and Temporal Sampling Density for Wheat Yield Estimation Using Both Thermal and Calendar Time.” International Journal of Applied Earth Observation and Geoinformation 86:101988. https://doi.org/10.1016/J.JAG.2019.101988.
  • Frazier, A. E., and B. L. Hemingway. 2021. “A Technical Review of Planet Smallsat Data: Practical Considerations for Processing and Using PlanetScope Imagery.” Remote Sensing 13 (19): 3930. https://doi.org/10.3390/RS13193930.
  • Gao, W., Q. Shen, Y. Zhou, and X. Li. 2018. “Analysis of Flood Inundation in Ungauged Basins Based on Multi-Source Remote Sensing Data.” Environmental Monitoring and Assessment 190 (3): 1–13. https://doi.org/10.1007/s10661-018-6499-4.
  • Gašparovič, M., and D. Klobučar. 2021. “Mapping Floods in Lowland Forest Using Sentinel-1 and Sentinel-2 Data and an Object-Based Approach.” Forests 12 (5): 553. https://doi.org/10.3390/F12050553.
  • Gautam, A., M. Sit, and I. Demir. 2022. “Realistic River Image Synthesis Using Deep Generative Adversarial Networks.” Frontiers in Water 4:10. https://doi.org/10.3389/frwa.2022.784441.
  • Gilles, D., N. Young, H. Schroeder, J. Piotrowski, and Y. J. Chang. 2012. “Inundation Mapping Initiatives of the Iowa Flood Center: Statewide Coverage and Detailed Urban Flooding Analysis.” Water (Switzerland) 4 (1): 85–106. https://doi.org/10.3390/w4010085.
  • Goffi, A., D. Stroppiana, P. A. Brivio, G. Bordogna, and M. Boschetti. 2020. “Towards an Automated Approach to Map Flooded Areas from Sentinel-2 MSI Data and Soft Integration of Water Spectral Features.” International Journal of Applied Earth Observation and Geoinformation 84:101951. https://doi.org/10.1016/J.JAG.2019.101951.
  • Google Earth Engine. Ee.Image.connectedpixelcount. Accessed November 20, 2023, from https://developers.google.com/earth-engine/apidocs/ee-image-connectedpixelcount
  • Haltas, I., E. Yildirim, F. Oztas, and I. Demir. 2021. “A Comprehensive Flood Event Specification and Inventory: 1930–2020 Turkey Case Study.” International Journal of Disaster Risk Reduction 56:102086. https://doi.org/10.1016/J.IJDRR.2021.102086.
  • Huang, H., and D. P. Roy. 2021. “Characterization of Planetscope-0 Planetscope-1 surface reflectance and normalized difference vegetation index continuity.” Science of Remote Sensing 3:100014. https://doi.org/10.1016/J.SRS.2021.100014.
  • Hu, A., and I. Demir. 2021. “Real-Time Flood Mapping on Client-Side Web Systems Using Hand Model.” Hydrology 8 (2): 65. https://doi.org/10.3390/hydrology8020065.
  • Hu, J., R. Liu, D. Hong, A. Camero, J. Yao, M. Schneider, F. Kurz, K. Segl, and X. X. Zhu. 2023. “MDAS: a new multimodal benchmark dataset for remote sensing.” Earth System Science Data 15 (1): 113–131. https://doi.org/10.5194/ESSD-15-113-2023.
  • Islam, K. A., M. S. Uddin, C. Kwan, and J. Li. 2020. “Flood Detection Using Multi-Modal and Multi-Temporal Images: A Comparative Study.” Remote Sensing 12 (15): 2455. https://doi.org/10.3390/RS12152455.
  • Kim, J. G., B. Kang, and S. Kim. 2022. “Flood Inflow Estimation in an Ungauged Simple Serial Cascade of Reservoir System Using Sentinel-2 Multi-Spectral Imageries: A Case Study of Imjin River, South Korea.” Remote Sensing 14 (15): 3699. https://doi.org/10.3390/RS14153699.
  • Li, Z., and I. Demir. 2022. “A Comprehensive Web-Based System for Flood Inundation Map Generation and Comparative Analysis Based on Height Above Nearest Drainage.” Science of the Total Environment 828:154420. https://doi.org/10.1016/J.SCITOTENV.2022.154420.
  • Li, Z., and I. Demir. 2023a. “Better Localized Predictions with Out-Of-Scope Information and Explainable AI: One-Shot SAR Backscatter Nowcast Framework with Data from Neighboring Region.” EarthArxiv 5509. https://doi.org/10.31223/X5P95M.
  • Li, Z., and I. Demir. 2023b. “U-Net-Based Semantic Classification for Flood Extent Extraction Using SAR Imagery and GEE Platform: A Case Study for 2019 Central US Flooding.” Science of the Total Environment 869:161757. https://doi.org/10.1016/J.SCITOTENV.2023.161757.
  • Li, Z., F. Q. Duque, T. Grout, B. Bates, and I. Demir. 2023. “Comparative Analysis of Performance and Mechanisms of Flood Inundation Map Generation Using Height Above Nearest Drainage.” Environmental Modelling & Software 159:105565. https://doi.org/10.1016/J.ENVSOFT.2022.105565.
  • Li, J., D. Hong, L. Gao, J. Yao, K. Zheng, B. Zhang, and J. Chanussot. 2022. “Deep learning in multimodal remote sensing data fusion: A comprehensive review.” International Journal of Applied Earth Observation and Geoinformation 112:102926. https://doi.org/10.1016/J.JAG.2022.102926.
  • Li, M., S. Lu, C. Du, Y. Wang, C. Fang, X. Li, H. Tang, M. H. A. Baig, and H. O. Ikhumhen. 2022. “Time-Series Surface Water Reconstruction Method (TSWR) Based on Spatial Distance Relationship of Multi-Stage Water Boundaries.” International Journal of Digital Earth 15 (1): 2335–2354. https://doi.org/10.1080/17538947.2022.2159553.
  • Li, Z., J. Mount, and I. Demir. 2022. “Accounting for Uncertainty in Real-Time Flood Inundation Mapping Using HAND Model: Iowa Case Study.” Natural Hazards 112 (1): 977–1004. https://doi.org/10.1007/S11069-022-05215-Z.
  • Ling, J., H. Zhang, and Y. Lin. 2021. “Improving Urban Land Cover Classification in Cloud-Prone Areas with Polarimetric SAR Images.” Remote Sensing 13 (22): 4708. https://doi.org/10.3390/RS13224708.
  • Liu, Y. 2018. Height Above Nearest Drainage (HAND) for CONUS | CUAHSI HydroShare. https://doi.org/10.4211/hs.69f7d237675c4c73938481904358c789
  • Li, Z., C. Wang, C. T. Emrich, and D. Guo. 2018. “A Novel Approach to Leveraging Social Media for Rapid Flood Mapping: A Case Study of the 2015 South Carolina Floods.” Cartography and Geographic Information Science 45 (2): 97–110. https://doi.org/10.1080/15230406.2016.1271356.
  • Li, Z., Z. Xiang, B. Z. Demiray, M. Sit, and I. Demir. 2022. “MA-SARNet: A One-Shot Forecasting Framework for SAR Image Prediction with Physical Driving Forces.” EarthArxiv 4846. https://doi.org/10.31223/X5765J.
  • Margareta Wahlstrom, D. G.-S. 2015. The Human Costs of Weather Related Disasters. In The United Nations Office for Diaster Risk Reduction. https://www.unisdr.org/files/46796_cop21weatherdisastersreport2015.pdf
  • Markert, K. N., A. M. Markert, T. Mayer, C. Nauman, A. Haag, A. Poortinga, B. Bhandari, et al. 2020. “Comparing Sentinel-1 Surface Water Mapping Algorithms and Radiometric Terrain Correction Processing in Southeast Asia Utilizing Google Earth Engine.” Remote Sensing 12 (15): 2469. https://doi.org/10.3390/RS12152469.
  • Moothedan, A. J., P. R. Dhote, P. K. Thakur, and V. Garg. 2020. “Automatic Flood Mapping Using Sentinel-1 GRD SAR Images and Google Earth Engine : A Case Study of DARBHANGAH”. In: BIHAR. Recent Advances in Geospatial Technology & Applications. India: IIRS Dehradun; August: 1–4. https://www.researchgate.net/publication/343539830.
  • Musser, J., K. Watson, J. Painter, and A. Gotvald. 2016. Flood-Inundation Maps of Selected Areas Affected by the Flood of October 2015 in Central and Coastal South Carolina. https://pubs.er.usgs.gov/publication/ofr20161019
  • Muste, M., D. A. Lyn, D. Admiraal, R. Ettema, V. Nikora, and M. H. García, Eds. 2017. Experimental Hydraulics: Methods, Instrumentation, Data Processing and Management: Volume I: Fundamentals and Methods. The Netherlands: CRC Press.
  • NASA. What is Synthetic Aperture Radar? | Earthdata. Accessed June 1, 2023, from https://www.earthdata.nasa.gov/learn/backgrounders/what-is-sar
  • NOAA. Weather Related Fatality and Injury Statistics. NOAA’s National Weather Service. Accessed February 1, 2022, from https://www.weather.gov/hazstat/
  • Nobre, A. D., L. A. Cuartas, M. Hodnett, C. D. Rennó, G. Rodrigues, A. Silveira, M. Waterloo, and S. Saleska. 2011. “Height Above the Nearest Drainage - a Hydrologically Relevant New Terrain Model.” Canadian Journal of Fisheries and Aquatic Sciences 404 (1–2): 13–29. https://doi.org/10.1016/j.jhydrol.2011.03.051.
  • Rahman, M. R., and P. K. Thakur. 2018. “Detecting, Mapping and Analysing of Flood Water Propagation Using Synthetic Aperture Radar (SAR) Satellite Data and GIS: A Case Study from the Kendrapara District of Orissa State of India.” The Egyptian Journal of Remote Sensing & Space Science 21:S37–S41. https://doi.org/10.1016/J.EJRS.2017.10.002.
  • Rambour, C., N. Audebert, E. Koeniguer, B. Le Saux, M. Crucianu, and M. Datcu. 2020. “Flood Detection in Time Series of Optical and SAR Images.” The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences 1343–1346. https://doi.org/10.5194/ISPRS-ARCHIVES-XLIII-B2-2020-1343-2020.
  • Refice, A., M. Zingaro, A. D’addabbo, and M. Chini. 2020. “Integrating C- and L-Band SAR Imagery for Detailed Flood Monitoring of Remote Vegetated Areas.” Water 12 (10): 2745. https://doi.org/10.3390/W12102745.
  • Rennó, C. D., A. D. Nobre, L. A. Cuartas, J. V. Soares, M. G. Hodnett, J. Tomasella, and M. J. Waterloo. 2008. “HAND, a New Terrain Descriptor Using SRTM-DEM: Mapping Terra-Firme Rainforest Environments in Amazonia.” Remote Sensing of Environment 112 (9): 3469–3481. https://doi.org/10.1016/j.rse.2008.03.018.
  • Romali, N. S., and Z. Yusop. 2021. “Flood Damage and Risk Assessment for Urban Area in Malaysia.” Hydrology Research 52 (1): 142–159. https://doi.org/10.2166/NH.2020.121.
  • Sadeh, Y., X. Zhu, D. Dunkerley, J. P. Walker, Y. Zhang, O. Rozenstein, V. S. Manivasagam, and K. Chenu. 2021. “Fusion of Sentinel-2 and PlanetScope Time-Series Data into Daily 3 M Surface Reflectance and Wheat LAI Monitoring.” International Journal of Applied Earth Observation and Geoinformation 96:102260. https://doi.org/10.1016/J.JAG.2020.102260.
  • Sai, V., K. Vanama, D. Mandal, and Y. S. Rao. 2020. “GEE4FLOOD: rapid mapping of flood areas using temporal Sentinel-1 SAR images with Google Earth Engine cloud platform.” Journal of Applied Remote Sensing 14 (3): 1. https://doi.org/10.1117/1.JRS.14.034505.
  • Sit, M. A., B. Seo, and I. Demir. 2023. “TempNet–Temporal Super-Resolution of Radar Rainfall Products with Residual CNNs.” Journal of Hydroinformatics 25 (2): 552–566. https://doi.org/10.2166/HYDRO.2023.196.
  • Teng, J., A. J. Jakeman, J. Vaze, B. F. W. Croke, D. Dutta, and S. Kim. 2017. “Flood Inundation Modelling: A Review of Methods, Recent Advances and Uncertainty Analysis.” Environmental Modelling and Software 90:201–216. https://doi.org/10.1016/j.envsoft.2017.01.006.
  • Thakur, P. K., R. Ranjan, S. Singh, P. R. Dhote, V. Sharma, V. Srivastav, M. Dhasmana, et al. 2020. “Synergistic Use Of Remote Sensing, Gis And Hydrological Models For Study Of August 2018 Kerala Floods.” The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2020. https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-1263-2020.
  • Thapa, A., T. Horanont, and B. Neupane. 2022. “Parcel-Level Flood and Drought Detection for Insurance Using Sentinel-2A, Sentinel-1 SAR GRD and Mobile Images.” Remote Sensing 14 (23): 6095. https://doi.org/10.3390/RS14236095.
  • Tiwari, V., V. Kumar, M. A. Matin, A. Thapa, W. L. Ellenburg, N. Gupta, S. Thapa, and G. J.-P. Schumann. 2020. “Flood Inundation Mapping-Kerala 2018; Harnessing the Power of SAR, Automatic Threshold Detection Method and Google Earth Engine.” PloS ONE 15 (8): e0237324. https://doi.org/10.1371/journal.pone.0237324.
  • Tsyganskaya, V., S. Martinis, P. Marzahn, and R. Ludwig. 2018. “Detection of Temporary Flooded Vegetation Using Sentinel-1 Time Series Data.” Remote Sensing 10 (8): 1286. https://doi.org/10.3390/rs10081286.
  • Tsyganskaya, V., S. Martinis, A. Twele, W. Cao, A. Schmitt, P. Marzahn, and R. Ludwig. 2016. “A Fuzzy Logic-Based Approach for the Detection of Flooded Vegetation by Means of Synthetic Aperture Radar Data.” International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives 41:371–378. https://doi.org/10.5194/isprsarchives-XLI-B7-371-2016.
  • Tulbure, M. G., M. Broich, V. Perin, M. Gaines, J. Ju, S. V. Stehman, T. Pavelsky, et al. 2022. “Can We Detect More Ephemeral Floods with Higher Density Harmonized Landsat Sentinel 2 Data Compared to Landsat 8 Alone?” ISPRS Journal of Photogrammetry and Remote Sensing 185:232–246. https://doi.org/10.1016/J.ISPRSJPRS.2022.01.021.
  • Twele, A., W. Cao, S. Plank, and S. Martinis. 2016. “Sentinel-1-Based Flood Mapping: A Fully Automated Processing Chain.” International Journal of Remote Sensing 37 (13): 2990–3004. https://doi.org/10.1080/01431161.2016.1192304.
  • U.S. Army Corps of Engineers . 2016. “Upper Mississippi River Restoration (UMRR) Program Long Term Resource Monitoring (LTRM) Element.” https://doi.org/10.5066/F7057CZ3
  • Yan, K., G. Di Baldassarre, D. P. Solomatine, and G. J. P. Schumann. 2015. “A Review of Low-Cost Space-Borne Data for Flood Modelling: Topography, Flood Extent and Water Level.” Hydrological Processes 29 (15): 3368–3387. https://doi.org/10.1002/HYP.10449.
  • Yildirim, E., and I. Demir. 2022. “Agricultural Flood Vulnerability Assessment and Risk Quantification in Iowa.” Science of the Total Environment 826:154165. https://doi.org/10.1016/J.SCITOTENV.2022.154165.
  • Zhai, H., H. Zhang, L. Zhang, and P. Li. 2018. “Cloud/Shadow Detection Based on Spectral Indices for Multi/Hyperspectral Optical Remote Sensing Imagery.” ISPRS Journal of Photogrammetry and Remote Sensing 144:235–253. https://doi.org/10.1016/J.ISPRSJPRS.2018.07.006.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.