A new dense 18-year time series of surface water fraction estimates from MODIS for the Mediterranean region

Linlin Li, Andrew Skidmore, Anton Vrieling, Tiejun Wang

Research output: Contribution to journalArticleResearchpeer-review

Abstract

Detailed knowledge on surface water distribution and itschanges is of high importance for water management and biodiversityconservation. Landsat-based assessments of surface water, such as the GlobalSurface Water (GSW) dataset developed by the European Commission JointResearch Centre (JRC), may not capture important changes in surface waterduring months with considerable cloud cover. This results in large temporalgaps in the Landsat record that prevent the accurate assessment of surface waterdynamics. Here we show that the frequent global acquisitions by the ModerateResolution Imaging Spectrometer (MODIS) sensors can compensate for thisshortcoming, and in addition allow for the examination of surface water changes at fine temporal resolution. To account for water bodies smaller than a MODIScell, we developed a global rule-based regression model for estimating thesurface water fraction from a 500 m nadir reflectance product from MODIS(MCD43A4). The model was trained and evaluated with the GSW monthly waterhistory dataset. A high estimation accuracy (R2=0.91, RMSE =11.41 %, and MAE =6.39 %) was achieved. We then applied the algorithm to18 years of MODIS data (2000–2017) to generate a time series of surfacewater fraction maps at an 8 d interval for the Mediterranean. From these mapswe derived metrics including the mean annual maximum, the standard deviation, and the seasonality of surface water. The dynamic surface water extent estimatesfrom MODIS were compared with the results from GSW and water level datameasured in situ or by satellite altimetry, yielding similar temporalpatterns. Our dataset complements surface water products at a fine spatialresolution by adding more temporal detail, which permits the effectivemonitoring and assessment of the seasonal, inter-annual, and long-termvariability of water resources, inclusive of small water bodies.

LanguageEnglish
Pages3037-3056
Number of pages20
JournalHydrology and Earth System Sciences
Volume23
Issue number7
DOIs
Publication statusPublished - 17 Jul 2019

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spectrometer
time series
surface water
Landsat
water
satellite altimetry
nadir
European Commission
cloud cover
seasonality
water management
reflectance
water level
water resource
sensor
water body
product

Bibliographical note

Copyright the Author(s) 2019. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

Cite this

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title = "A new dense 18-year time series of surface water fraction estimates from MODIS for the Mediterranean region",
abstract = "Detailed knowledge on surface water distribution and itschanges is of high importance for water management and biodiversityconservation. Landsat-based assessments of surface water, such as the GlobalSurface Water (GSW) dataset developed by the European Commission JointResearch Centre (JRC), may not capture important changes in surface waterduring months with considerable cloud cover. This results in large temporalgaps in the Landsat record that prevent the accurate assessment of surface waterdynamics. Here we show that the frequent global acquisitions by the ModerateResolution Imaging Spectrometer (MODIS) sensors can compensate for thisshortcoming, and in addition allow for the examination of surface water changes at fine temporal resolution. To account for water bodies smaller than a MODIScell, we developed a global rule-based regression model for estimating thesurface water fraction from a 500 m nadir reflectance product from MODIS(MCD43A4). The model was trained and evaluated with the GSW monthly waterhistory dataset. A high estimation accuracy (R2=0.91, RMSE =11.41 {\%}, and MAE =6.39 {\%}) was achieved. We then applied the algorithm to18 years of MODIS data (2000–2017) to generate a time series of surfacewater fraction maps at an 8 d interval for the Mediterranean. From these mapswe derived metrics including the mean annual maximum, the standard deviation, and the seasonality of surface water. The dynamic surface water extent estimatesfrom MODIS were compared with the results from GSW and water level datameasured in situ or by satellite altimetry, yielding similar temporalpatterns. Our dataset complements surface water products at a fine spatialresolution by adding more temporal detail, which permits the effectivemonitoring and assessment of the seasonal, inter-annual, and long-termvariability of water resources, inclusive of small water bodies.",
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A new dense 18-year time series of surface water fraction estimates from MODIS for the Mediterranean region. / Li, Linlin; Skidmore, Andrew; Vrieling, Anton; Wang, Tiejun.

In: Hydrology and Earth System Sciences, Vol. 23, No. 7, 17.07.2019, p. 3037-3056.

Research output: Contribution to journalArticleResearchpeer-review

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AU - Skidmore, Andrew

AU - Vrieling, Anton

AU - Wang, Tiejun

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