气候变化领域集成服务门户(CCPortal): Coupling high-resolution field monitoring and MODIS for reconstructing wetland historical hydroperiod at a high temporal frequency

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DOI	10.1016/j.rse.2020.111807
	Coupling high-resolution field monitoring and MODIS for reconstructing wetland historical hydroperiod at a high temporal frequency
	Alonso A.; Muñoz-Carpena R.; Kaplan D.
发表日期	2020
ISSN	00344257
卷号	247
英文摘要	Historical wetland hydrology data are instrumental to support the design of wetland management and restoration strategies but are rarely available. In this study, we tested the capabilities and limitations of a simple methodological framework based on publicly available MODIS Land Reflectance Products to estimate wetland soil surface saturation and inundation spatiotemporal dynamics. Using supervised learning and high-resolution groundwater and surface water elevation data, the framework searches for spectral algorithms, referred to as the wet/dry wetland status classifier (WSC) and the continuous wetland dynamics identifier (WDI), that best predict upper soil layer wetness status in the study wetland. We used Google Earth Engine (GEE) for fast access and processing of the full range of MODIS data. The capabilities of GEE also enabled us to readily conduct a comparative assessment of the MODIS 8-day composite and daily collections and test various pixel-level quality filters to select reliable data at the highest possible temporal resolution. We tested the framework on the internationally-recognized Ramsar site Palo Verde National Park wetland in Costa Rica, and we obtained good results (overall prediction accuracy of 86.6% and kappa coefficient of 0.7 for the WSC; r2 of 0.71 for the WDI). High-resolution water level data allowed us to assess the challenges, promises and limitations of using MODIS products for wetland hydrology applications. We then applied the WSC and WDI to map the 2000-2016 sub-weekly wetland hydroperiod at 500m resolution, achieving a temporal resolution rarely matched in remote sensing for wetland studies. The analysis of the end-products, combined with the field water elevation data, provided new insights into the drivers controlling the spatiotemporal dynamics of hydroperiod within the Palo Verde wetland and did not reveal any significant temporal trends. The WSC and WDI framework developed here can be useful for reconstructing long-term hydroperiod variability and uncovering its drivers for other wetland systems globally. © 2020 Elsevier Inc.
英文关键词	Costa Rica; Flood; Google Earth Engine; Groundtruthing; Hydrology; Hydroperiod; MODIS; Palo Verde National Park; Remote sensing; Spectral index; Tropical wetland; Wetland
语种	英语
scopus关键词	Dynamics; Groundwater; Hydrology; Radiometers; Remote sensing; Soils; Surface waters; Water levels; Comparative assessment; High temporal frequency; Methodological frameworks; Prediction accuracy; Restoration strategies; Spatio-temporal dynamics; Temporal resolution; Wetland management; Wetlands; algorithm; hydrological regime; hydroperiod; MODIS; reconstruction; remote sensing; software; spectral analysis; wetland management; wettability; Costa Rica; Guanacaste; Palo Verde National Park
来源期刊	Remote Sensing of Environment
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/179266
作者单位	Agricultural and Biological Engineering Department, University of Florida, 287 Frazier Rogers Hall, P.O. Box 110570, Gainesville, FL 32611-0570, United States; Engineering School of Sustainable Infrastructure & Environment, University of Florida, 102 Phelps Lab, PO Box 116350, Gainesville, FL 32611-6350, United States; Earth and Life Institute – Environmental Sciences, Université catholique de Louvain, Croix du Sud 2, bte L7.05.02., Louvain-la-Neuve, 1348, Belgium
推荐引用方式 GB/T 7714	Alonso A.,Muñoz-Carpena R.,Kaplan D.. Coupling high-resolution field monitoring and MODIS for reconstructing wetland historical hydroperiod at a high temporal frequency[J],2020,247.
APA	Alonso A.,Muñoz-Carpena R.,&Kaplan D..(2020).Coupling high-resolution field monitoring and MODIS for reconstructing wetland historical hydroperiod at a high temporal frequency.Remote Sensing of Environment,247.
MLA	Alonso A.,et al."Coupling high-resolution field monitoring and MODIS for reconstructing wetland historical hydroperiod at a high temporal frequency".Remote Sensing of Environment 247(2020).