A Multi-Data Geospatial Approach for Understanding Flood Risk in the Coastal Plains of Tamil Nadu, India

George, Sekar Leo; Kantamaneni, Komali; Allat, Rasme; Prasad, Kumar Arun; Shekhar, Sulochana; Panneer, Sigamani; Rice, Louise; Balasubramani, K.

doi:10.3390/earth3010023

Cited by 14 publications

(5 citation statements)

References 54 publications

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“…Most of these papers (80%) monitored LAI over time (e.g., [119]), whereas about half of the papers (60%) compared different methods to minimize errors and retrieved this parameter from several remote data (e.g., [120]).…”

Section: Leaf Area Indexmentioning

confidence: 99%

Remote Data for Mapping and Monitoring Coastal Phenomena and Parameters: A Systematic Review

Cavalli

2024

Remote Sensing

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Since 1971, remote sensing techniques have been used to map and monitor phenomena and parameters of the coastal zone. However, updated reviews have only considered one phenomenon, parameter, remote data source, platform, or geographic region. No review has offered an updated overview of coastal phenomena and parameters that can be accurately mapped and monitored with remote data. This systematic review was performed to achieve this purpose. A total of 15,141 papers published from January 2021 to June 2023 were identified. The 1475 most cited papers were screened, and 502 eligible papers were included. The Web of Science and Scopus databases were searched using all possible combinations between two groups of keywords: all geographical names in coastal areas and all remote data and platforms. The systematic review demonstrated that, to date, many coastal phenomena (103) and parameters (39) can be mapped and monitored using remote data (e.g., coastline and land use and land cover changes, climate change, and coastal urban sprawl). Moreover, the authors validated 91% of the retrieved parameters, retrieved from remote data 39 parameters that were mapped or monitored 1158 times (88% of the parameters were combined together with other parameters), monitored 75% of the parameters over time, and retrieved 69% of the parameters from several remote data and compared the results with each other and with available products. They obtained 48% of the parameters using different methods, and their results were compared with each other and with available products. They combined 17% of the parameters that were retrieved with GIS and model techniques. In conclusion, the authors addressed the requirements needed to more effectively analyze coastal phenomena and parameters employing integrated approaches: they retrieved the parameters from different remote data, merged different data and parameters, compared different methods, and combined different techniques.

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Section: Leaf Area Indexmentioning

confidence: 99%

Remote Data for Mapping and Monitoring Coastal Phenomena and Parameters: A Systematic Review

Cavalli

2024

Remote Sensing

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“…(i) Importance of Flood: [5] sheds light on the dynamic behavior of groundwater in a flood plain that has been heavily drained and emphasizes the need of documenting flood episodes in order to calculate the overall groundwater contribution to floodplain water balances. A strong correlation between surface water radon readings and groundwater level suggested cyclical dynamics of connection-disconnection between shallow ground water and drains.…”

Section: Review Of Literaturementioning

confidence: 99%

Flood Inundation Mapping Using Sentinel 1A Satelite Data in Major Blocks of Mayiladuthurai District, Tamil Nadu, India

Sneka,

Pazhanivelan,

Ragunath

et al. 2023

IJPSS

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A research study was carried out for mapping flood affected areas from Sentinel 1A satellite data in the major blocks of Mayiladuthurai district, Tamil Nadu. A very high-resolution Sentinel 1A satellite data was acquired and processed with GIS tools. Ground truth gathered during the survey were utilized to identify the dB values for flood affected areas, which were then used to classify the flood pixels in the study regions. The flood affected areas of Mayiladuthurai district was found to be 18002 ha during the year 2022. Accuracy assessment and cross validation was done using confusion matrix with the ground truth points collected. The classification resulted with an overall accuracy of 86.2 % area with a Kappa score of 0.72.

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“…Low-lying and near-shore coastal settlements are always at high risk of various coastal hazards [48]. The risk of coastal inundation can be indirectly estimated with the help of assessing the extent of built-up areas [49].…”

Section: Vulnerability Of Built-up Areasmentioning

confidence: 99%

A Comprehensive Assessment of Climate Change and Coastal Inundation through Satellite-Derived Datasets: A Case Study of Sabang Island, Indonesia

et al. 2022

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Climate-change-induced hazards are negatively affecting the small islands across Indonesia. Sabang Island is one of the most vulnerable small islands due to the rising sea levels and increasing coastal inundation which threaten the low-lying coastal areas with and without coastal defences. However, there is still a lack of studies concerning the long-term trends in climatic variables and, consequently, sea level changes in the region. Accordingly, the current study attempts to comprehensively assess sea level changes and coastal inundation through satellite-derived datasets and model-based products around Sabang Island, Indonesia. The findings of the study show that the temperature (both minimum and maximum) and rainfall of the island are increasing by ~0.01 °C and ~11.5 mm per year, respectively. The trends of temperature and rainfall are closely associated with vegetative growth; an upward trend in the dense forest is noticed through the enhanced vegetation index (EVI). The trend analysis of satellite altimeter datasets shows that the sea level is increasing at a rate of 6.6 mm/year. The DEM-based modelling shows that sea level rise poses the greatest threat to coastal habitations and has significantly increased in recent years, accentuated by urbanisation. The GIS-based model results predict that about half of the coastal settlements (2.5 sq km) will be submerged completely within the next 30 years, provided the same sea level rise continues. The risk of coastal inundation is particularly severe in Sabang, the largest town on the island. The results allow regional, sub-regional, and local comparisons that can assess variations in climate change, sea level rise, coastal inundation, and associated vulnerabilities.

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A Multi-Data Geospatial Approach for Understanding Flood Risk in the Coastal Plains of Tamil Nadu, India

Cited by 14 publications

References 54 publications

Remote Data for Mapping and Monitoring Coastal Phenomena and Parameters: A Systematic Review

Remote Data for Mapping and Monitoring Coastal Phenomena and Parameters: A Systematic Review

Flood Inundation Mapping Using Sentinel 1A Satelite Data in Major Blocks of Mayiladuthurai District, Tamil Nadu, India

A Comprehensive Assessment of Climate Change and Coastal Inundation through Satellite-Derived Datasets: A Case Study of Sabang Island, Indonesia

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