An Evaluation of MODIS Daily and 8-day Composite Products for Floodplain and Wetland Inundation Mapping

Wetland and floodplain inundation is well-known for its hydrological, ecological and environmental importance. Satellite remote sensing provides an effective and efficient tool for detecting inundation extent. This study compares and validates inundation maps derived from NASA’s Moderate Imaging Spectroradiometer (MODIS) imagery. The comparison was performed between MODIS daily and 8-day composite products; and the validation was conducted using Landsat Thematic Mapper (TM) images. Two floodplain wetlands in the Murray-Darling Basin in Australia were selected as case studies, and inundation extents corresponding to the peak flows of significant flood events were extracted using the Open Water Likelihood (OWL) algorithm and the modified Normalised Difference Water Index (mNDWI) for MODIS and TM images, respectively. The accuracy of the inundation maps derived from different images were assessed spatially and statistically. The evaluation results show that both MODIS products may provide a reasonable estimate of the dynamic extent of floodplain inundation at the regional scale. The accuracy of inundation mapping is mainly due to the spatial and spectral characteristics of MODIS imagery and has nothing to do with the type of products chosen, thus the 8-day composite images can be used as a surrogate for daily images for the purpose of inundation delineation.

[1]  J. R. Landis,et al.  The measurement of observer agreement for categorical data. , 1977, Biometrics.

[2]  C. Justice,et al.  Analysis of the dynamics of African vegetation using the normalized difference vegetation index , 1986 .

[3]  John R. Jensen,et al.  Introductory Digital Image Processing: A Remote Sensing Perspective , 1986 .

[4]  Russell G. Congalton,et al.  A review of assessing the accuracy of classifications of remotely sensed data , 1991 .

[5]  Debbie Whitall,et al.  WETLANDS , 1995, Restoration & Management Notes.

[6]  B. Gao NDWI—A normalized difference water index for remote sensing of vegetation liquid water from space , 1996 .

[7]  S. K. McFeeters The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features , 1996 .

[8]  L. Smith Satellite remote sensing of river inundation area, stage, and discharge: a review , 1997 .

[9]  Russell G. Congalton,et al.  Assessing the accuracy of remotely sensed data : principles and practices , 1998 .

[10]  P. Frazier,et al.  Water body detection and delineation with Landsat TM data. , 2000 .

[11]  Antony K. Liu,et al.  Satellite Remote Sensing Sar , 2001 .

[12]  Giles M. Foody,et al.  Status of land cover classification accuracy assessment , 2002 .

[13]  A. Huete,et al.  Overview of the radiometric and biophysical performance of the MODIS vegetation indices , 2002 .

[14]  J. Gallant,et al.  A multiresolution index of valley bottom flatness for mapping depositional areas , 2003 .

[15]  John Louis,et al.  Relating wetland inundation to river flow using Landsat TM data , 2003 .

[16]  René R. Colditz,et al.  Flood delineation in a large and complex alluvial valley, lower Pánuco basin, Mexico , 2003 .

[17]  A preliminary investigation into the influence of changing stream network patterns on the distribution of water in the Narran Lakes Ecosystem , 2004 .

[18]  Ning Shu,et al.  Study of Dongting Lake area variation and its influence on water level using MODIS data / Etude de la variation de la surface du Lac Dongting et de son influence sur le niveau d’eau, grâce à des données MODIS , 2005 .

[19]  Hanqiu Xu Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery , 2006 .

[20]  M. Thoms,et al.  Unravelling the physical template of a terminal flood plain-wetland sediment storage system. , 2006 .

[21]  E. Anderson,et al.  MODIS-BASED FLOOD DETECTION, MAPPING AND MEASUREMENT: THE POTENTIAL FOR OPERATIONAL HYDROLOGICAL APPLICATIONS , 2006 .

[22]  Cassandra James,et al.  The Narran Ecosystem project: the response of a terminal wetland system to variable wetting and drying: final report to the Murray-Darling Basin Commission , 2007 .

[23]  T. Sakamoto,et al.  Detecting temporal changes in the extent of annual flooding within the cambodia and the vietnamese mekong delta from MODIS time-series imagery , 2007 .

[24]  M. Friedl,et al.  Using MODIS data to characterize seasonal inundation patterns in the Florida Everglades , 2008 .

[25]  Peng Gong,et al.  Modelling spatial‐temporal change of Poyang Lake using multitemporal Landsat imagery , 2008 .

[26]  B. Wylie,et al.  Analysis of Dynamic Thresholds for the Normalized Difference Water Index , 2009 .

[27]  David Gillieson,et al.  Evaluation of Landsat TM vegetation indices for estimating vegetation cover on semi-arid rangelands: a case study from Australia , 2009 .

[28]  Rick L. Lawrence,et al.  Change detection of wetland ecosystems using Landsat imagery and change vector analysis , 2007, Wetlands.

[29]  Charlotte MacAlister,et al.  Mapping wetlands in the Lower Mekong Basin for wetland resource and conservation management using Landsat ETM images and field survey data. , 2009, Journal of environmental management.

[30]  David P. Roy,et al.  Wetland mapping in the Congo Basin using optical and radar remotely sensed data and derived topographical indices , 2010 .

[31]  Yun Chen,et al.  Linking inundation timing and extent to ecological response models using the Murray-Darling Basin Floodplain Inundation Model (MDB-FIM) , 2010 .

[32]  Huili Gong,et al.  Economic value evaluation of wetland service in Yeyahu Wetland Nature Reserve, Beijing , 2011 .

[33]  Guy Byrne,et al.  MODIS-based standing water detection for flood and large reservoir mapping: Algorithm development and applications for the Australian continent , 2011 .

[34]  G. Lin Urban China in transformation: Hybrid economy, juxtaposed space, and new testing ground for geographical enquiries , 2011 .

[35]  Shahid Habib,et al.  Satellite Remote Sensing and Hydrologic Modeling for Flood Inundation Mapping in Lake Victoria Basin: Implications for Hydrologic Prediction in Ungauged Basins , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[36]  Robert L. Crabtree,et al.  Percent surface water estimation from MODIS BRDF 16-day image composites , 2011 .

[37]  Xiaoling Chen,et al.  Assessment of inundation changes of Poyang Lake using MODIS observations between 2000 and 2010 , 2012 .

[38]  Yun Chen,et al.  Spatial modelling of potential soil water retention under floodplain inundation using remote sensing and GIS , 2012 .

[39]  Jia Yu,et al.  Detecting floodplain inundation frequency using MODIS time-series imagery , 2012, 2012 First International Conference on Agro- Geoinformatics (Agro-Geoinformatics).