globalchange  > 气候变化与战略
DOI: 10.5194/hess-23-3037-2019
论文题名:
A new dense 18-year time series of surface water fraction estimates from MODIS for the Mediterranean region
作者: Li L.; Skidmore A.; Vrieling A.; Wang T.
刊名: Hydrology and Earth System Sciences
ISSN: 1027-5606
出版年: 2019
卷: 23, 期:7
起始页码: 3037
结束页码: 3056
语种: 英语
Scopus关键词: Biodiversity ; Conservation ; Radiometers ; Regression analysis ; Spectrometers ; Surface water resources ; Time series ; Water levels ; Water management ; Water supply systems ; Biodiversity conservation ; European Commission ; Long-term variability ; Mediterranean region ; Moderate resolution imaging spectrometers ; Monitoring and assessment ; Rule based regression models ; Similar temporal patterns ; Surface waters ; accuracy assessment ; cloud cover ; data set ; estimation method ; European Commission ; fractionation ; groundwater-surface water interaction ; Landsat ; Mediterranean environment ; MODIS ; satellite data ; surface water ; time series analysis ; water management
英文摘要: Detailed knowledge on surface water distribution and its changes is of high importance for water management and biodiversity conservation. Landsat-based assessments of surface water, such as the Global Surface Water (GSW) dataset developed by the European Commission Joint Research Centre (JRC), may not capture important changes in surface water during months with considerable cloud cover. This results in large temporal gaps in the Landsat record that prevent the accurate assessment of surface water dynamics. Here we show that the frequent global acquisitions by the Moderate Resolution Imaging Spectrometer (MODIS) sensors can compensate for this shortcoming, and in addition allow for the examination of surface water changes at fine temporal resolution. To account for water bodies smaller than a MODIS cell, we developed a global rule-based regression model for estimating the surface water fraction from a 500 m nadir reflectance product from MODIS (MCD43A4). The model was trained and evaluated with the GSW monthly water history dataset. A high estimation accuracy (R2 D 0:91, RMSE D 11:41 %, and MAE D 6:39 %) was achieved. We then applied the algorithm to 18 years of MODIS data (2000-2017) to generate a time series of surface water fraction maps at an 8 d interval for the Mediterranean. From these maps we derived metrics including the mean annual maximum, the standard deviation, and the seasonality of surface water. The dynamic surface water extent estimates from MODIS were compared with the results from GSW and water level data measured in situ or by satellite altimetry, yielding similar temporal patterns. Our dataset complements surface water products at a fine spatial resolution by adding more temporal detail, which permits the effective monitoring and assessment of the seasonal, inter-annual, and long-term variability of water resources, inclusive of small water bodies. © 2019 Author(s).
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/162933
Appears in Collections:气候变化与战略

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作者单位: Li, L., Faculty of Geo-information Science and Earth Observation, University of Twente, Enschede, Netherlands; Skidmore, A., Faculty of Geo-information Science and Earth Observation, University of Twente, Enschede, Netherlands, Department of Environmental Sciences, Macquarie UniversityNSW, Australia; Vrieling, A., Faculty of Geo-information Science and Earth Observation, University of Twente, Enschede, Netherlands; Wang, T., Faculty of Geo-information Science and Earth Observation, University of Twente, Enschede, Netherlands

Recommended Citation:
Li L.,Skidmore A.,Vrieling A.,et al. A new dense 18-year time series of surface water fraction estimates from MODIS for the Mediterranean region[J]. Hydrology and Earth System Sciences,2019-01-01,23(7)
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