Mapping inundation in the heterogeneous floodplain wetlands of the Macquarie Marshes, using Landsat Thematic Mapper

Thomas, Rachael F.; Kingsford, Richard T.; Lu, Yi; Cox, Stephen J.; Sims, Neil; Hunter, S. J.

doi:10.1016/j.jhydrol.2015.02.029

Cited by 81 publications

(64 citation statements)

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%

Stakeholder-led science: engaging resource managers to identify science needs for long-term management of floodplain conservation lands

Bouska¹,

Lindner²,

Paukert³

et al. 2016

E&S

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Section: Follow-up Surveymentioning

confidence: 99%

Stakeholder-led science: engaging resource managers to identify science needs for long-term management of floodplain conservation lands

Bouska¹,

Lindner²,

Paukert³

et al. 2016

E&S

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“…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%

A Spectral Unmixing Method with Ensemble Estimation of Endmembers: Application to Flood Mapping in the Caprivi Floodplain

et al. 2017

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The Caprivi basin in Namibia has been affected by severe flooding in recent years resulting in deaths, displacements and destruction of infrastructure. The negative consequences of these floods have emphasized the need for timely, accurate and objective information about the extent and location of affected areas. Due to the high temporal variability of flood events, Earth Observation (EO) data at high revisit frequency is preferred for accurate flood monitoring. Currently, EO data has either high temporal or coarse spatial resolution. Accurate methodologies for the estimation and monitoring of flooding extent using coarse spatial resolution optical image data are needed in order to capture spatial details in heterogeneous areas such as Caprivi. The objective of this work was the retrieval of the fractional abundance of water (γ w ) by applying a new spectral indices-based unmixing algorithm to Medium Resolution Imaging Spectrometer Full Resolution (MERIS FR) data using a minimum number of spectral bands. These images are technically similar to the OLCI image data acquired by the Sentinel-3 satellite, which are to be systematically provided in the near future. The normalized difference wetness index (NDWI) was applied to delineate the water surface and combined with normalized difference vegetation index (NDVI) to account for emergent vegetation within the water bodies. The challenge to map flooded areas by applying spectral unmixing is the estimation of spectral endmembers, i.e., pure spectra of land cover features. In our study, we developed and applied a new unmixing method based on the use of an ensemble of spectral endmembers to capture and take into account spectral variability within each endmember. In our case study, forty realizations of the spectral endmembers gave a stable frequency distribution of γ w . Quality of the flood map derived from the Envisat MERIS (MERIS) data was assessed against high (30 m) spatial resolution Landsat Thematic Mapper (TM) images on two different dates (17 April 2008 and 22 May 2009) during which floods occurred. The findings show that both the spatial and the frequency distribution of the γ w extracted from the MERIS data were in good agreement with the high-resolution TM retrievals. The use of conventional linear unmixing, instead, applied using the entire available spectra for each image, resulted in relatively large differences between TM and MERIS retrievals.

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“…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%

“…Other mapping techniques include geomorphological data analysis and historical maps (Magliulo & Cusano, 2016;Magliulo, Bozzi, & Pignone, 2016;Visser, 2014). A common practice in the specialized literature, which implies Landsat imagery, is mapping inundations in heterogeneous floodplains and wetlands due to the stagnant character of the water (Thomas et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

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Historic flood events in NE Romania (post-1990)

et al. 2017

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Using open-source satellite imagery like Landsat TM, ETM+ and Sentinel 2 can lead to accurate cartographic products. We mapped flood events from Siret and Prut river basins in the last 30 years based on the availability of Landsat data archive. In this area were recorded historical values in flow rates for the entire Romanian territory: 4650 m³/s on the Siret River in 2005 -the maximum value ever recorded for Romania; 4240 m³/s on the Prut in 2008 -second maximum value recorded for Romania. The most powerful floods that took place in Romania in the last years were in

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Mapping inundation in the heterogeneous floodplain wetlands of the Macquarie Marshes, using Landsat Thematic Mapper

Cited by 81 publications

References 72 publications

Stakeholder-led science: engaging resource managers to identify science needs for long-term management of floodplain conservation lands

Stakeholder-led science: engaging resource managers to identify science needs for long-term management of floodplain conservation lands

A Spectral Unmixing Method with Ensemble Estimation of Endmembers: Application to Flood Mapping in the Caprivi Floodplain

Historic flood events in NE Romania (post-1990)

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