Reducing signature variability in unmixing coastal marsh Thematic Mapper scenes using spectral indices

Rogers, A. S.; Kearney, Michael

doi:10.1080/01431160310001618103

Cited by 271 publications

(156 citation statements)

References 24 publications

Supporting

Mentioning

147

Contrasting

Order By: Relevance

“…It more consistently characterizes marsh spectra end members than the more common principal components approach [Rogers and Kearney, 2004]. Three indices were calculated by normalizing the difference between Landsat bands to produce a spectral space (NDX) that approximates the optimal spatial model for spectral unmixing and, thus, more tightly defines the following vegetation, water and soil spectral end members: NDVI = (band 4 NIR − band 3 [9] We calculated radiance for twelve, co-registered Landsat TM and ETM + scenes using standard remote sensing techniques and equations [Jensen, 2002;Chander et al, 2009].…”

Section: Methodsmentioning

confidence: 99%

Freshwater river diversions for marsh restoration in Louisiana: Twenty-six years of changing vegetative cover and marsh area

Kearney

Riter

Turner

2011

Geophys. Res. Lett.

View full text Add to dashboard Cite

The restoration of Louisiana's coastal wetlands will be one of the largest, most costly and longest environmental remediation projects undertaken. We use Landsat data to show that freshwater diversions, a major restoration strategy, have not increased vegetation and marsh coverage in three freshwater diversions operating for ∼19 years. Two analytic methods indicate no significant changes in either relative vegetation or overall marsh area from 1984 to 2005 in zones closest to diversion inlets. After Hurricanes Katrina and Rita, these zones sustained dramatic and enduring losses in vegetation and overall marsh area, whereas the changes in similar marshes of the adjacent reference sites were relatively moderate and short‐lived. We suggest that this vulnerability to storm damage reflects the introduction of nutrients in the freshwater diversions (that add insignificant amounts of additional sediments), which promotes poor rhizome and root growth in marshes where below‐ground biomass historically played the dominant role in vertical accretion.

show abstract

Section: Methodsmentioning

confidence: 99%

Freshwater river diversions for marsh restoration in Louisiana: Twenty-six years of changing vegetative cover and marsh area

Kearney

Riter

Turner

2011

Geophys. Res. Lett.

View full text Add to dashboard Cite

show abstract

“…Many water indices have been developed using different spectral bands and different satellite data (Gao, 1996;McFeeters, 1996;Rogers and Kearney, 2004;Xu, 2006) and are commonly used to differentiate land cover types.…”

Section: Detection Of Vegetated Flooded Pixelsmentioning

confidence: 99%

Characterizing floods in the poorly gauged wetlands of the Tana River Delta, Kenya, using a water balance model and satellite data

Léauthaud

Belaud

Duvail

et al. 2013

Hydrol. Earth Syst. Sci.

View full text Add to dashboard Cite

Abstract. Wetlands, such as those of the Tana River Delta in Kenya, are vital but threatened ecosystems. The flooding characteristics of wetlands largely determine their physical, chemical and biological properties, so their quantification is crucial for wetland management. This quantification can be achieved through hydrological modelling. In addition, the analysis of satellite imagery provides essential hydrological data to monitor floods in poorly gauged zones.The objective of this study was to quantify the main water fluxes and flooding characteristics (extent, duration and number of floods) in the poorly gauged Tana River Delta in East Africa during 2002-2011. To do so, we constructed a lumped hydrological model (the Tana Inundation Model, TIM) that was calibrated and validated with MODIS data. Further analysis of the MYD09A1 500 m composite product provided a map of the empirical probability of flooded state. In non-extreme years and for the current topology of the delta, the flood extent exceeded 300 km 2 . Floods over 200 km 2 occurred on average once a year, with a mean duration of 18 days. River discharge from the upper basin counted for over 95 % of the total water inflow. The results are discussed in the light of possible improvements of the models and wetland management issues.This study provides the first known quantification of spatial and temporal flooding characteristics in the Tana River Delta. As such, it is essential for the water and natural resource management of the Tana River basin. The water balance approach was pertinent to the study of this system, for which information on its internal properties and processes is limited. The methodology, a combination of hydrological modelling and flood mapping using MODIS products, should be applicable to other areas, including those for which data are scarce and cloud cover may be high, and where a medium spatial resolution is required.

show abstract

“…Memon et al (2012) [48] used three water indexes for delineating and mapping of surface water using MODIS (Terra) near real time images during the 2012 floods in Pakistan. The three water indexes included NDWI, Red and Short Wave Infra-Red (RSWIR) water index [49] and Green and Short Wave Infra-Red (GSWIR) water index [50]. Experimental results indicated the accuracy of NDWI, RSWIR, and GSWIR was 73.12%, 85.80%, and 81.54%, respectively, which was lower than the proposed MESMA+RF approach (94%).…”

Section: Discussionmentioning

confidence: 79%

Flood Mapping Based on Multiple Endmember Spectral Mixture Analysis and Random Forest Classifier—The Case of Yuyao, China

et al. 2015

View full text Add to dashboard Cite

Remote sensing is recognized as a valuable tool for flood mapping due to its synoptic view and continuous coverage of the flooding event. This paper proposed a hybrid approach based on multiple endmember spectral analysis (MESMA) and Random Forest classifier to extract inundated areas in Yuyao City in China using medium resolution optical imagery. MESMA was adopted to tackle the mixing pixel problem induced by medium resolution data. Specifically, 35 optimal endmembers were selected to construct a total of 3111 models in the MESMA procedure to derive accurate fraction information. A multi-dimensional feature space was constructed including the normalized difference water index (NDWI), topographical parameters of height, slope, and aspect together with the fraction maps. A Random Forest classifier consisting of 200 decision trees was adopted to classify the post-flood image based on the above multi-features. Experimental results indicated that the proposed method can extract the inundated areas precisely with a classification accuracy of 94% and a Kappa index of 0.88. The inclusion of fraction information can help improve the mapping accuracy with an increase of 2.5%. Moreover, the proposed method also outperformed the maximum likelihood classifier and the NDWI thresholding method. This research provided a useful reference for flood mapping using medium resolution optical remote sensing imagery. OPEN ACCESSRemote Sens. 2015, 7 12540

show abstract

Reducing signature variability in unmixing coastal marsh Thematic Mapper scenes using spectral indices

Cited by 271 publications

References 24 publications

Freshwater river diversions for marsh restoration in Louisiana: Twenty-six years of changing vegetative cover and marsh area

Freshwater river diversions for marsh restoration in Louisiana: Twenty-six years of changing vegetative cover and marsh area

Characterizing floods in the poorly gauged wetlands of the Tana River Delta, Kenya, using a water balance model and satellite data

Flood Mapping Based on Multiple Endmember Spectral Mixture Analysis and Random Forest Classifier—The Case of Yuyao, China

Contact Info

Product

Resources

About