The Impact of Hurricane Katrina on the Coastal Vegetation of the Weeks Bay Reserve, Alabama from NDVI Data

Rodgers, J.; Murrah, Adam W.; Cooke, William H.

doi:10.1007/s12237-009-9138-z

Cited by 78 publications

(52 citation statements)

References 18 publications

(21 reference statements)

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“…It was regarded as the worst natural disaster on record in Dominica and Puerto Rico, and eye-witnesses reported extensive defoliation [6]. The combination of these hurricane events, including the high wind speeds, storm surge, and heavy precipitation, most likely had an adverse effect on the local vegetation, yet the extent and magnitude of the vegetation damage within the region has not been fully investigated [7].…”

Section: Introductionmentioning

confidence: 99%

The Impact of Hurricane Maria on the Vegetation of Dominica and Puerto Rico Using Multispectral Remote Sensing

Smith

2018

Remote Sensing

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Abstract:As the worst natural disaster on record in Dominica and Puerto Rico, Hurricane Maria in September 2017 had a large impact on the vegetation of these islands. In this paper, multitemporal Landsat 8 OLI and Sentinel-2 data are used to investigate vegetation damage on Dominica and Puerto Rico by Hurricane Maria, and related influencing factors are analyzed. Moreover, the changes in the normalized difference vegetation index (NDVI) in the year 2017 are compared to reference years (2015 and 2016). The results show that (1) there is a sudden drop in NDVI values after Hurricane Maria's landfall (decreased about 0.2) which returns to near normal vegetation after 1.5 months; (2) different land cover types have different sensitivities to Hurricane Maria, whereby forest is the most sensitive type, then followed by wetland, built-up, and natural grassland; and (3) for Puerto Rico, the vegetation damage is highly correlated with distance from the storm center and elevation. For Dominica, where the whole island is within Hurricane Maria's radius of maximum wind, the vegetation damage has no obvious relationship to elevation or distance. The study provides insight into the sensitivity and recovery of vegetation after a major land-falling hurricane, and may lead to improved vegetation protection strategies.

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Section: Introductionmentioning

confidence: 99%

The Impact of Hurricane Maria on the Vegetation of Dominica and Puerto Rico Using Multispectral Remote Sensing

Smith

2018

Remote Sensing

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“…Because remote sensing equipment observes a wide area at any one time and regularly observes the same location, remotely sensed data have recently been used to assess the impact of floods, tsunamis and other natural disasters (Barnes et al 2007;Fritz et al 2008Fritz et al , 2011Gotoh et al 1999;Kume et al 2009;Liu et al 2013;McAdoo et al 2007;Middleton 2009;Nuttall and Armstrong 2010;Overton et al 2006;Ramachandran et al 2005;Rodgers et al 2009;Suppasri et al 2012;Velmurugan et al 2006). Furthermore, the effects of salinity on vegetation (Wang and Xu 2008) and the impact of sea water and soil salinity (Dan and Richard 2002;Datta and Jong 2002;Fritz et al 2011;Gotoh et al 1999Gotoh et al , 2012McAdoo et al 2007;Middleton 2009;Overton et al 2006) have been evaluated from satellite data.…”

Section: Introductionmentioning

confidence: 99%

Evaluating salinity damage to crops through satellite data analysis: application to typhoon affected areas of southern Japan

Goto

Nmor

et al. 2014

Nat Hazards

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In recent times, tsunamis and typhoons have threatened Japan's coastal lands with increased flooding and salinity. Using satellite data, we monitored the effect of increased salinity on vegetation health in the coastal area of southern Japan, which was affected by flooding following Typhoon 9918 in 1999. An index of plant activity called the Normalized Difference Vegetation Index (NDVI) was evaluated before and after the typhoon, and the change in NDVI was computed as a comparison measure. The results were then correlated with electric conductivity, which is a measure of soil salinity. A strong negative correlation was found between NDVI ratio and salt concentration (r = -0.7731, n = 50, p \ 0.0001), indicating that the reduced NDVI values were attributable to increased salinity from the flooding. These results not only provide useful insight into a rapid method of assessing large-scale flood impacts using satellite data, but also validate the monitoring of NDVI as an indicator of salinity damage to vegetation. To summarise, by understanding the changes in vegetation health following natural disasters such as flooding (as revealed by NDVI), we can potentially develop improved management strategies.

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“…These types of approaches are effective in providing a general overview of impacts and recovery within less processing time (Joyce et al 2009a). Lee et al (2008), Rodgers III et al (2009), Zhang et al (2013 and Bhowmik and Cabral (2013) …”

Section: A) Pre-classificationmentioning

confidence: 99%

“…Most previous tropical cyclone impact assessment studies have focused on single impacts in the landscape (Klemas 2009;Wang and Xu 2010;Rodgers III et al 2009;Bhowmik and Cabral 2013). Forest damage assessment and recovery represents the dominant focus in most of the studies (Zhang et al 2013;Dutta et al 2015;Wang and Xu 2009).…”

Section: Introductionmentioning

confidence: 99%

“…Most previous tropical cyclone impact assessment studies have used the land cover change detection followed by field impact assessment which focuses on single impacts in the landscape (Klemas 2009;Wang and Xu 2010;Rodgers III et al 2009;Bhowmik and Cabral 2013). Forest damage assessment represents the dominant focus in most of these studies.…”

Section: Introductionmentioning

confidence: 99%

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Cyclone disaster mapping, monitoring and management using satellite remote sensing and spatial analysis

Hoque¹

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Tropical cyclones are one of the most catastrophic natural hazards regularly affecting tropical coastal areas globally. The overall impacts of tropical cyclones can be minimized using a range of management approaches, in terms of: prevention/reduction, and preparedness. Accurate and detailed spatial information on the natural and built environment is required to support the development, implementation and evaluation of these cyclone management approaches. There is a lack of appropriate mapping approaches and spatial models at local scales (<1000 km 2 ) to derive this information.This thesis developed and evaluated mapping approaches and spatial models at the local scale (<1000 km 2 ) by integrating remote sensing, field data and spatial analysis for assessing, monitoring and managing tropical cyclone impacts. Three specific objectives were addressed: (1) developing and evaluating an approach for assessing the multiple impacts of tropical cyclones through objectbased image analysis applied to moderate spatial resolution satellite imagery; (2) developing and testing a risk mapping approach for tropical cyclone impacts using an analytical hierarchy process (AHP) with data derived from remote sensing, field data and spatial analysis; and (3) producing and evaluating a simple risk modelling approach under present and future climate scenarios for tropical cyclone impacts using remote sensing, field data and spatial analysis. The developed mapping approaches and models were tested to justify the applicability in Sarankhola Upazila (151 km 2 ), a local government area in coastal Bangladesh. Cyclone Sidr (2007) was used as a case study for objective one in the study site.After introductory, review and research approach chapters, chapter four developed a method for mapping the multiple impacts of tropical cyclones. The object-based approach was used to map land cover types in pre-and post-cyclone Sidr (2007) damage to cropland and the changes to landforms. The damage results were verified using local damage reports and high spatial resolution satellite imagery that were taken after the cyclone.ii Chapter five integrated remote sensing, field data and spatial analysis for developing a multi-criteria tropical cyclone risk mapping approach at a local scale. Three risk components: 1-vulnerability and exposure; 2-hazard; and 3-mitigation capacity, and their 14 relevant criteria were considered.Thematic raster map layers were prepared for every criterion and weighted using AHP. A weighted overlay technique was used for generating vulnerability, hazard, mitigation capacity and risk maps.The verified results revealed that detailed cyclone risk information can be successfully mapped using geospatial techniques and an AHP at the local scale. The study found that incorporation of mitigation capacity significantly influenced the risk results. The approach also solved several issues for local level multi-criteria data generation, processing and integration. The approach provided was validated by confidence level assessment an...

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The Impact of Hurricane Katrina on the Coastal Vegetation of the Weeks Bay Reserve, Alabama from NDVI Data

Cited by 78 publications

References 18 publications

The Impact of Hurricane Maria on the Vegetation of Dominica and Puerto Rico Using Multispectral Remote Sensing

The Impact of Hurricane Maria on the Vegetation of Dominica and Puerto Rico Using Multispectral Remote Sensing

Evaluating salinity damage to crops through satellite data analysis: application to typhoon affected areas of southern Japan

Cyclone disaster mapping, monitoring and management using satellite remote sensing and spatial analysis

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