2015
DOI: 10.1016/j.jhydrol.2015.02.029
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Mapping inundation in the heterogeneous floodplain wetlands of the Macquarie Marshes, using Landsat Thematic Mapper

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Cited by 80 publications
(64 citation statements)
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References 72 publications
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“…For example, the ability to map areas of inundation at regional scales has recently provided information on extent of inundation for different flow return intervals (Chojnacki et al 2012, Theiling andBurant 2013). In ungaged areas, remotely sensed data are being increasingly used to understand temporal inundation dynamics (Ward et al 2014, Thomas et al 2015. Spatially-explicit inundation information can be linked to known species responses to identify suitable habitat for species of interest (Jacobson et al 2011) and evaluate changes in habitat availability under different management and climate change scenarios (Matella and Merenlender 2015).…”
Section: Follow-up Surveymentioning
confidence: 99%
“…For example, the ability to map areas of inundation at regional scales has recently provided information on extent of inundation for different flow return intervals (Chojnacki et al 2012, Theiling andBurant 2013). In ungaged areas, remotely sensed data are being increasingly used to understand temporal inundation dynamics (Ward et al 2014, Thomas et al 2015. Spatially-explicit inundation information can be linked to known species responses to identify suitable habitat for species of interest (Jacobson et al 2011) and evaluate changes in habitat availability under different management and climate change scenarios (Matella and Merenlender 2015).…”
Section: Follow-up Surveymentioning
confidence: 99%
“…Mapping water surfaces with such imagery has been shown to be challenging [22], mainly due to the inability of lower spatial resolution imagery to adequately characterize pixel fragmentation, i.e., the so-called mixed pixel effect. This effect is augmented in vegetated floodplains [52] where the spectral response of vegetation weakens water signatures. For instance, in this study, it was found that NDWI and NDVI derived from low (300 m) MERIS images were generally higher over water surfaces than those generated from high-resolution (30 m) TM images.…”
Section: Discussionmentioning
confidence: 99%
“…This method of data acquisition and data extraction has been used in numerous studies that focused on mapping different phenomena or on particular properties that occur or are revealed on the Earth's surface, such as mining activities (Cutaia, Massacci, & Roselli, 2004;Lobo, Costa, & Novo, 2015), water quality parameters and temperature (Bonansea et al, 2015;Ding & Elmore, 2015;Tebbs, Remedios, & Harper, 2013), water surface extent and dynamics (Mueller et al, 2016) and mapping major flood events (Bhatt et al, 2016;Cutaia et al, 2004;Sakai et al, 2015;Sandholt et al, 2003;Thomas et al, 2015;Tulbure et al, 2016;Wang, 2004;Yang et al, 2015).…”
Section: Remote Sensing Image Processingmentioning
confidence: 99%
“…The computation of this index highlights water pixels (Li et al, 2013;Thomas et al, 2015). The MNDWI proposed by Xu (2006) replaces the traditional near infrared band (NIR) used by McFeeters (1996) with the MIR band, which results in more accurate results when extracting water features (Equation 3).…”
Section: Remote Sensing Image Processingmentioning
confidence: 99%
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