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Remote Sens. 2015, 7(12), 15989-16003; doi:10.3390/rs71215813

Downscaling Surface Water Inundation from Coarse Data to Fine-Scale Resolution: Methodology and Accuracy Assessment

1,2
and
1,2,*
1
Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 21008, China
2
State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 21008, China
*
Author to whom correspondence should be addressed.
Academic Editors: Guy J-P. Schumann, Magaly Koch and Prasad S. Thenkabail
Received: 18 August 2015 / Revised: 11 October 2015 / Accepted: 18 November 2015 / Published: 30 November 2015
View Full-Text   |   Download PDF [2542 KB, uploaded 30 November 2015]   |  

Abstract

The availability of water surface inundation with high spatial resolution is of fundamental importance in several applications such as hydrology, meteorology and ecology. Medium spatial resolution sensors, like MODerate-resolution Imaging Spectroradiometer (MODIS), exhibit a significant potential to study inundation dynamics over large areas because of their high temporal resolution. However, the low spatial resolution provided by MODIS is not appropriate to accurately delineate inundation over small scale. Successful downscaling of water inundation from coarse to fine resolution would be crucial for improving our understanding of complex inundation characteristics over the regional scale. Therefore, in this study, we propose an innovative downscaling method based on the normalized difference water index (NDWI) statistical regression algorithm towards generating small-scale resolution inundation maps from MODIS data. The method was then applied to the Poyang Lake of China. To evaluate the performance of the proposed downscaling method, qualitative and quantitative comparisons were conducted between the inundation extent of MODIS (250 m), Landsat (30 m) and downscaled MODIS (30 m). The results indicated that the downscaled MODIS (30 m) inundation showed significant improvement over the original MODIS observations when compared with simultaneous Landsat (30 m) inundation. The edges of the lakes become smoother than the results from original MODIS image and some undetected water bodies were delineated with clearer shapes in the downscaled MODIS (30 m) inundation map. With respect to high-resolution Landsat TM/ETM+ derived inundation, the downscaling procedure has significantly increased the R2 and reduced RMSE and MAE both for the inundation area and for the value of landscape metrics. The main conclusion of this study is that the downscaling algorithm is promising and quite feasible for the inundation mapping over small-scale lakes. View Full-Text
Keywords: terrestrial surface water; inundation; downscaling; NDWI; statistical regression algorithm terrestrial surface water; inundation; downscaling; NDWI; statistical regression algorithm
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Wu, G.; Liu, Y. Downscaling Surface Water Inundation from Coarse Data to Fine-Scale Resolution: Methodology and Accuracy Assessment. Remote Sens. 2015, 7, 15989-16003.

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