References

• Allen, C., Gonzales, R., and Parrott, L. 2020. “Modelling the contribution of ephemeral wetlands to landscape connectivity.” Ecological Modelling, Vol. 419: pp. 108944. doi:10.1016/j.ecolmodel.2020.108944.
   Web of Science ®Google Scholar
• Alonso, A., Muñoz-Carpena, R., and Kaplan, D. 2020. “Coupling high-resolution field monitoring and MODIS for reconstructing wetland historical hydroperiod at a high temporal frequency.” Remote Sensing of Environment, Vol. 247: pp. 111807. doi:10.1016/j.rse.2020.111807.
   Web of Science ®Google Scholar
• Amani, M., Brisco, B., Warren, R., DeLancey, E.R., Seydi, S.T., and Poncos, V. 2022. “Wetland hydroperiod analysis in alberta using InSAR coherence data.” Remote Sensing, Vol. 14 (No. 14): pp. 3469. doi:10.3390/rs14143469.
   Web of Science ®Google Scholar
• Battaglia, M.J., Banks, S., Behnamian, A., Bourgeau-Chavez, L., Brisco, B., Corcoran, J., Chen, Z., et al. 2021. “Multi-source EO for dynamic wetland mapping and monitoring in the great lakes basin.” Remote Sensing, Vol. 13 (No. 4): pp. 599. doi:10.3390/rs13040599.
   Web of Science ®Google Scholar
• Baxter, B. K., and Butler, J. K. 2020. “Climate change and great salt lake.” In Great Salt Lake Biology, edited by Baxter, B.K., Butler, J.K., pp. 23–52. Cham: Springer International Publishing. doi:10.1007/978-3-030-40352-2_2.
   Google Scholar
• Champagne, C., McNairn, H., Daneshfar, B., and Shang, J. 2014. “A bootstrap method for assessing classification accuracy and confidence for agricultural land use mapping in Canada.” International Journal of Applied Earth Observation and Geoinformation, Vol. 29: pp. 44–52. doi:10.1016/j.jag.2013.12.016.
   Web of Science ®Google Scholar
• Claverie, M., Ju, J., Masek, J.G., Dungan, J.L., Vermote, E.F., Roger, J.-C., Skakun, S.V., and Justice, C. 2018. “The Harmonized Landsat and Sentinel-2 surface reflectance data set.” Remote Sensing of Environment, Vol. 219: pp. 145–161. doi:10.1016/j.rse.2018.09.002.
   Web of Science ®Google Scholar
• Cohen-Shacham, E., Walters, G., Janzen, C., Maginnis, S. (Eds.). 2016. Nature-based solutions to address global societal challenges. Gland, Switzerland: IUCN International Union for Conservation of Nature. doi:10.2305/IUCN.CH.2016.13.en.
   Google Scholar
• Copass, C., Antonova, N., and Kennedy, R. 2018. “Comparison of office and field techniques for validating landscape change classification in pacific northwest national parks.” Remote Sensing, Vol. 11(No. 1): pp. 3. doi:10.3390/rs11010003.
   Web of Science ®Google Scholar
• Davidson, N.C., and Davidson, N.C. 2014. “How much wetland has the world lost? Long-term and recent trends in global wetland area.” Marine and Freshwater Research, Vol. 65(No. 10): pp. 934–941. doi:10.1071/MF14173.
   Web of Science ®Google Scholar
• Dekker, A.G., Hoogenboom, H.J., Goddijn, L.M., and Malthus, T.J.M. 1997. “The relation between inherent optical properties and reflectance spectra in turbid inland waters.” Remote Sensing Reviews, Vol. 15(No. 1–4): pp. 59–74. doi:10.1080/02757259709532331.
   Google Scholar
• Environmental Laboratory 1987. Corps of Engineers wetlands delineation manual, technical report Y-87-1. Vicksburg, MS: U.S. Army Engineer Waterways Experiment Station.
   Google Scholar
• European Commission 2020. Global surface water explorer [WWW Document]. https://global-surface-water.appspot.com/.
   Google Scholar
• Feulner, G., Rahmstorf, S., Levermann, A., and Volkwardt, S. 2013. “On the origin of the surface air temperature difference between the hemispheres in earth’s present-day climate.” Journal of Climate, Vol. 26(No. 18): pp. 7136–7150. doi:10.1175/JCLI-D-12-00636.1.
   Web of Science ®Google Scholar
• Flood, N. 2014. “Continuity of reflectance data between Landsat-7 ETM + and Landsat-8 OLI, for both top-of-atmosphere and surface reflectance: A study in the Australian landscape.” Remote Sensing, Vol. 6(No. 9): pp. 7952–7970. doi:10.3390/rs6097952.
   Web of Science ®Google Scholar
• Foga, S., Scaramuzza, P.L., Guo, S., Zhu, Z., Dilley, R.D., Beckmann, T., Schmidt, G.L., Dwyer, J.L., Joseph Hughes, M., and Laue, B. 2017. “Cloud detection algorithm comparison and validation for operational Landsat data products.” Remote Sensing of Environment, Vol. 194: pp. 379–390. doi:10.1016/j.rse.2017.03.026.
   Web of Science ®Google Scholar
• Friedl, M.A., Sulla-Menashe, D., Tan, B., Schneider, A., Ramankutty, N., Sibley, A., and Huang, X. 2010. “MODIS Collection 5 global land cover: Algorithm refinements and characterization of new datasets.” Remote Sensing of Environment, Vol. 114(No. 1): pp. 168–182. doi:10.1016/j.rse.2009.08.016.
   Web of Science ®Google Scholar
• Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., and Moore, R. 2017. “Google Earth Engine: Planetary-scale geospatial analysis for everyone.” Remote Sensing of Environment, Vol. 202: pp. 18–27. doi:10.1016/j.rse.2017.06.031.
   Web of Science ®Google Scholar
• Halabisky, M., Moskal, L.M., Gillespie, A., and Hannam, M. 2016. “Reconstructing semi-arid wetland surface water dynamics through spectral mixture analysis of a time series of Landsat satellite images (1984–2011).” Remote Sensing of Environment, Vol. 177: pp. 171–183. doi:10.1016/j.rse.2016.02.040.
   Web of Science ®Google Scholar
• Heidi van, D., Linström, A., Durand, J.F., Naidoo, L., and Cho, M.A. 2022. “Deriving the maximum extent and hydroperiod of open water from Sentinel-2 imagery for global sustainability and biodiversity reporting for wetlands.” Water SA, Vol. 48(No. 1): pp. 75–89. doi:10.17159/wsa/2022.v48.i1.3883.
   Web of Science ®Google Scholar
• Hemati, M., Hasanlou, M., Mahdianpari, M., and Mohammadimanesh, F. 2023. “Iranian wetland inventory map at a spatial resolution of 10 m using Sentinel-1 and Sentinel-2 data on the Google Earth Engine cloud computing platform.” Environmental Monitoring and Assessment, Vol. 195(No. 5): pp. 558. doi:10.1007/s10661-023-11202-z.
   PubMed Web of Science ®Google Scholar
• Hemati, M., Hasanlou, M., Mahdianpari, M., and Mohammadimanesh, F. 2021. “A systematic review of Landsat data for change detection applications: 50 years of monitoring the earth.” Remote Sensing, Vol. 13(No. 15): pp. 2869. doi:10.3390/rs13152869.
   Web of Science ®Google Scholar
• Hemati, M., Mahdianpari, M., Hasanlou, M., and Mohammadimanesh, F. 2022. Iranian wetland hydroperiod change detection using an unsupervised method on 20 years of Landsat data within the Google Earth Engine. Presented at the IGARSS 2022 – 2022 IEEE International Geoscience and Remote Sensing Symposium, IEEE, Kuala Lumpur, Malaysia, pp. 6209–6212. doi:10.1109/IGARSS46834.2022.9884716.
   Google Scholar
• Hemati, M. A., Hasanlou, M., Mahdianpari, M., and Mohammadimanesh, F. 2021. Wetland Mapping of Northern Provinces of Iran Using Sentinel-1 and Sentinel-2 in Google Earth Engine. Presented at the IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium, IEEE, Brussels, Belgium, pp. 96–99. doi:10.1109/IGARSS47720.2021.9554984.
   Google Scholar
• Hopkinson, C., Fuoco, B., Grant, T., Bayley, S.E., Brisco, B., and MacDonald, R. 2020. “Wetland hydroperiod change along the upper Columbia river Floodplain, Canada, 1984 to 2019.” Remote Sensing, Vol. 12(No. 24): pp. 4084. doi:10.3390/rs12244084.
   Web of Science ®Google Scholar
• Hosseiny, B., Mahdianpari, M., Hemati, M., Radman, A., Mohammadimanesh, F., and Chanussot, J. 2024. “Beyond supervised learning in remote sensing: A systematic review of deep learning approaches.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol. 17: pp. 1035–1052. doi:10.1109/JSTARS.2023.3316733.
   Google Scholar
• Jin, H., Huang, C., Lang, M.W., Yeo, I.-Y., and Stehman, S.V. 2017. “Monitoring of wetland inundation dynamics in the Delmarva Peninsula using Landsat time-series imagery from 1985 to 2011.” Remote Sensing of Environment, Vol. 190: pp. 26–41. doi:10.1016/j.rse.2016.12.001.
   Web of Science ®Google Scholar
• Jones, J.W. 2019. “Improved automated detection of subpixel-scale inundation—Revised dynamic surface water extent (DSWE) partial surface water tests.” Remote Sensing, Vol. 11(No. 4): pp. 374. doi:10.3390/rs11040374.
   Web of Science ®Google Scholar
• Junk, W., Bayley, P., and Sparks, R. 1989. “The flood pulse concept in river-floodplain systems.” Paper presented at International Large River Symposium.
   Google Scholar
• Kouhgardi, E., Hemati, M., Shakerdargah, E., Shiri, H., and Mahdianpari, M. 2022. “Monitoring shoreline and land use/land cover changes in sandbanks provincial park using remote sensing and climate data.” Water, Vol. 14(No. 22): pp. 3593. doi:10.3390/w14223593.
   Web of Science ®Google Scholar
• Leach, J.A., Buttle, J.M., Webster, K.L., Hazlett, P.W., Jeffries, D.S., 2020. “Travel times for snowmelt-dominated headwater catchments: Influences of wetlands and forest harvesting, and linkages to stream water quality.” Hydrological Processes, Vol. 34: pp. 21542175. doi:10.1002/hyp.13746.
   Google Scholar
• Li, P., Jiang, L., and Feng, Z. 2013. “Cross-comparison of vegetation indices derived from Landsat-7 Enhanced Thematic Mapper plus (ETM+) and Landsat-8 Operational Land Imager (OLI) sensors.” Remote Sensing, Vol. 6(No. 1): pp. 310–329. doi:10.3390/rs6010310.
   Web of Science ®Google Scholar
• Lyon, S.W., Laudon, H., Seibert, J., Mörth, M., Tetzlaff, D., and Bishop, K.H. 2010. “Controls on snowmelt water mean transit times in northern boreal catchments.” Hydrological Processes, Vol. 24(No. 12): pp. 1672–1684. doi:10.1002/hyp.7577.
   Web of Science ®Google Scholar
• Mahdianpari, M., Brisco, B., Granger, J., Mohammadimanesh, F., Salehi, B., Homayouni, S., and Bourgeau-Chavez, L. 2021. “The third generation of Pan-Canadian Wetland map at 10 m resolution using multisource earth observation data on cloud computing platform.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol. 14: pp. 8789–8803. doi:10.1109/JSTARS.2021.3105645.
   Web of Science ®Google Scholar
• Mishra, N., Haque, M., Leigh, L., Aaron, D., Helder, D., and Markham, B. 2014. “Radiometric cross calibration of Landsat 8 operational land imager (OLI) and Landsat 7 enhanced thematic mapper plus (ETM+).” Remote Sensing, Vol. 6(No. 12): pp. 12619–12638. doi:10.3390/rs61212619.
   Web of Science ®Google Scholar
• Mueller, N., Lewis, A., Roberts, D., Ring, S., Melrose, R., Sixsmith, J., Lymburner, L., et al. 2016. “Water observations from space: Mapping surface water from 25 years of Landsat imagery across Australia.” Remote Sensing of Environment, Vol. 174 pp. 341–352. doi:10.1016/j.rse.2015.11.003.
   Web of Science ®Google Scholar
• Olthof, I., and Rainville, T. 2022. “Dynamic surface water maps of Canada from 1984 to 2019 Landsat satellite imagery.” Remote Sensing of Environment, Vol. 279. pp. 113121. doi:10.1016/j.rse.2022.113121.
   Web of Science ®Google Scholar
• Owen, R.K., Webb, E.B., Haukos, D.A., and Goyne, K.W. 2020. “Projected climate and land use changes drive plant community composition in agricultural wetlands.” Environmental and Experimental Botany, Vol. 175. pp. 104039. doi:10.1016/j.envexpbot.2020.104039.
   Web of Science ®Google Scholar
• Pekel, J.-F., Cottam, A., Gorelick, N., and Belward, A.S. 2016. “High-resolution mapping of global surface water and its long-term changes.” Nature, Vol. 540(No. 7633): pp. 418–422. doi:10.1038/nature20584.
   PubMed Web of Science ®Google Scholar
• Perreault, N., Lévesque, E., Fortier, D., Gratton, D., and Lamarque, L.J. 2017. “Remote sensing evaluation of High Arctic wetland depletion following permafrost disturbance by thermo-erosion gullying processes.” Arctic Science, Vol. 3(No. 2): pp. 237–253. doi:10.1139/as-2016-0047.
   Web of Science ®Google Scholar
• Pickens, A.H., Hansen, M.C., Hancher, M., Stehman, S.V., Tyukavina, A., Potapov, P., Marroquin, B., and Sherani, Z. 2020. “Mapping and sampling to characterize global inland water dynamics from 1999 to 2018 with full Landsat time-series.” Remote Sensing of Environment, Vol. 243. pp. 111792. doi:10.1016/j.rse.2020.111792.
   Web of Science ®Google Scholar
• Pickens, A.H., Hansen, M.C., Stehman, S.V., Tyukavina, A., Potapov, P., Zalles, V., and Higgins, J. 2022. “Global seasonal dynamics of inland open water and ice.” Remote Sensing of Environment, Vol. 272. pp. 112963. doi:10.1016/j.rse.2022.112963.
   Web of Science ®Google Scholar
• Prigent, C., Jimenez, C., and Bousquet, P. 2020. “Satellite‐derived global surface water extent and dynamics over the last 25 years (GIEMS‐2).” Journal of Geophysical Research, Vol. 125: pp. e2019JD030711. doi:10.1029/2019JD030711.
   Web of Science ®Google Scholar
• Qiu, S., Zhu, Z., and He, B. 2019. “Fmask 4.0: Improved cloud and cloud shadow detection in Landsats 4–8 and Sentinel-2 imagery.” Remote Sensing of Environment, Vol. 231: pp. 111205. doi:10.1016/j.rse.2019.05.024.
   Web of Science ®Google Scholar
• Ramsar Convention. 2016. An Introduction to the Convention on Wetlands (previously The Ramsar Convention Manual). Gland, Switzerland: Ramsar Convention Secretariat.
   Google Scholar
• Rokaya, P., Peters, D.L., Elshamy, M., Budhathoki, S., and Lindenschmidt, K. 2020. “Impacts of future climate on the hydrology of a northern headwaters basin and its implications for a downstream deltaic ecosystem.” Hydrological Processes, Vol. 34(No. 7): pp. 1630–1646. doi:10.1002/hyp.13687.
   Web of Science ®Google Scholar
• Roy, D.P., Kovalskyy, V., Zhang, H.K., Vermote, E.F., Yan, L., Kumar, S.S., and Egorov, A. 2016. “Characterization of Landsat-7 to Landsat-8 reflective wavelength and normalized difference vegetation index continuity.” Remote Sensing of Environment, Vol. 185(No. 1): pp. 57–70. doi:10.1016/j.rse.2015.12.024.
   Google Scholar
• She, X., Zhang, L., Cen, Y., Wu, T., Huang, C., and Baig, M. 2015. “Comparison of the continuity of vegetation indices derived from Landsat 8 OLI and Landsat 7 ETM + data among different vegetation types.” Remote Sensing, Vol. 7(No. 10): pp. 13485–13506. doi:10.3390/rs71013485.
   Web of Science ®Google Scholar
• Soulard, C.E., Walker, J.J., and Petrakis, R.E. 2020. “Implementation of a surface water extent model in Cambodia using cloud-based remote sensing.” Remote Sensing, Vol. 12(No. 6): pp. 984. doi:10.3390/rs12060984.
   Web of Science ®Google Scholar
• Tang, H., Lu, S., Ali Baig, M.H., Li, M., Fang, C., and Wang, Y. 2022. “Large-scale surface water mapping based on Landsat and Sentinel-1 images.” Water, Vol. 14(No. 9): pp. 1454. doi:10.3390/w14091454.
   Web of Science ®Google Scholar
• Thorslund, J., Jarsjo, J., Jaramillo, F., Jawitz, J.W., Manzoni, S., Basu, N.B., Chalov, S.R., et al. 2017. “Wetlands as large-scale nature-based solutions: Status and challenges for research, engineering and management.” Ecological Engineering, Vol. 108: pp. 489–497. doi:10.1016/j.ecoleng.2017.07.012.
   Web of Science ®Google Scholar
• Tulbure, M.G., and Broich, M. 2013. “Spatiotemporal dynamic of surface water bodies using Landsat time-series data from 1999 to 2011.” ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 79: pp. 44–52. doi:10.1016/j.isprsjprs.2013.01.010.
   Web of Science ®Google Scholar
• United Nations. 2019. World population prospects - Population division - United Nations [WWW Document]. URL https://population.un.org/wpp/.
   Google Scholar
• Woodcock, C.E., Allen, R., Anderson, M., Belward, A., Bindschadler, R., Cohen, W., Gao, F., et al. 2008. “Free access to landsat imagery.” Science, Vol. 320(No. 5879): pp. 1011–1011. doi:10.1126/science.320.5879.1011a.
   PubMed Web of Science ®Google Scholar
• Wu, Q., Lane, C.R., Li, X., Zhao, K., Zhou, Y., Clinton, N., DeVries, B., Golden, H.E., and Lang, M.W. 2019. “Integrating LiDAR data and multi-temporal aerial imagery to map wetland inundation dynamics using Google Earth Engine.” Remote Sensing of Environment, Vol. 228: pp. 1–13. doi:10.1016/j.rse.2019.04.015.
   PubMed Web of Science ®Google Scholar
• Wulder, M., Li, Z., Campbell, E., White, J., Hobart, G., Hermosilla, T., and Coops, N. 2018. “A national assessment of wetland status and trends for Canada’s forested ecosystems using 33 years of earth observation satellite data.” Remote Sensing, Vol. 10(No. 10): pp. 1623. doi:10.3390/rs10101623.
   Web of Science ®Google Scholar
• Wulder, M.A., Loveland, T.R., Roy, D.P., Crawford, C.J., Masek, J.G., Woodcock, C.E., Allen, R.G., et al. 2019. “Current status of Landsat program, science, and applications.” Remote Sensing of Environment, Vol. 225: pp. 127–147. doi:10.1016/j.rse.2019.02.015.
   Web of Science ®Google Scholar
• Wulder, M.A., Roy, D.P., Radeloff, V.C., Loveland, T.R., Anderson, M.C., Johnson, D.M., Healey, S., et al. 2022. “Fifty years of Landsat science and impacts.” Remote Sensing of Environment, Vol. 280: pp. 113195. doi:10.1016/j.rse.2022.113195.
   Web of Science ®Google Scholar
• Yang, X., Qin, Q., Yésou, H., Ledauphin, T., Koehl, M., Grussenmeyer, P., and Zhu, Z. 2020. “Monthly estimation of the surface water extent in France at a 10-m resolution using Sentinel-2 data.” Remote Sensing of Environment, Vol. 244: pp. 111803. doi:10.1016/j.rse.2020.111803.
   Web of Science ®Google Scholar
• Zhao, J., Malone, S.L., Oberbauer, S.F., Olivas, P.C., Schedlbauer, J.L., Staudhammer, C.L., and Starr, G. 2019. “Intensified inundation shifts a freshwater wetland from a CO2 sink to a source.” Global Change Biology, Vol. 25(No. 10): pp. 3319–3333. doi:10.1111/gcb.14718.
   PubMed Web of Science ®Google Scholar
• Zhao, L., Yang, J., Li, P., and Zhang, L. 2014. “Seasonal inundation monitoring and vegetation pattern mapping of the Erguna floodplain by means of a RADARSAT-2 fully polarimetric time series.” Remote Sensing of Environment, Vol. 152: pp. 426–440. doi:10.1016/j.rse.2014.06.026.
   Web of Science ®Google Scholar
• Zou, Z., DeVries, B., Huang, C., Lang, M.W., Thielke, S., McCarty, G.W., Robertson, A.G., et al. 2021. “Characterizing wetland inundation and vegetation dynamics in the arctic coastal plain using recent satellite data and field photos.” Remote Sensing, Vol. 13(No. 8): pp. 1492. doi:10.3390/rs13081492.
   Web of Science ®Google Scholar