Mr. Chandrasekar Nainarpandian Profile

Chandrasekar Nainarpandian

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Publications (4)

Proceedings Article | 10 February 2023 Paper

Rice lodging disaster monitoring method based on multi-source remote sensing data

Xuemei Dai, Shuisen Chen, Hao Jiang, Chandrasekar Nainarpandian

Proceedings Volume 12552, 1255224 (2023) https://doi.org/10.1117/12.2667454

KEYWORDS: Remote sensing, Vegetation, Satellites, Radar, Scattering, Polarization, Reflectivity

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SPIE Journal Paper | 23 February 2022 Open Access

Special Section Guest Editorial: Coastal Zone Remote Sensing for Environmental Sustainability

Shuisen Chen, Chandrasekar Nainarpandian, Ayad Fadhil

JARS, Vol. 16, Issue 01, 012001, (February 2022) https://doi.org/10.1117/12.10.1117/1.JRS.16.012001

KEYWORDS: Remote sensing, Environmental sensing, Associative arrays, Radar, Image quality, Image classification, Water, Unmanned aerial vehicles, Thermography, Sensors

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SPIE Journal Paper | 7 February 2022

Exploring beach placer minerals in the east coast of Tamil Nadu, India, using EO-1 Hyperion data

Rajan G. Rejith, Mayappan Sundararajan, Lakshmanan Gnanappazham, Kaliraj Seenipandi, Chandrasekar Nainarpandian

JARS, Vol. 16, Issue 01, 012017, (February 2022) https://doi.org/10.1117/12.10.1117/1.JRS.16.012017

KEYWORDS: Minerals, Absorption, Associative arrays, Reflectivity, Data modeling, Quartz, Image classification, Remote sensing, Calibration, Satellites

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SPIE Journal Paper | 5 January 2022

Appraisal of urban growth impacts on seawater intrusion vulnerability using GIS-based modified GALDIT-U model: a case study of Kozhikode coastal stretch, Kerala, South India

S. S. Salaj, Dharmarajan Ramesh, D. Suresh Babu, Kaliraj Seenipandi, Chandrasekar Nainarpandian

JARS, Vol. 16, Issue 01, 012014, (January 2022) https://doi.org/10.1117/12.10.1117/1.JRS.16.012014

KEYWORDS: Chlorine, Coastal modeling, Geographic information systems, Diffusion, Sodium, Ranging, Interfaces, Contamination, Calcium, Agriculture

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We investigate the potential vulnerability to seawater intrusion into the aquifers along the Kozhikode coastal stretch using the modified GALDIT (GALDIT-U) model from an urbanization perspective. Urban growth impact (expansion of the impervious surface) was added as an additional input parameter in the GALDIT model, and the analyses were performed using GIS. The results indicated that the area of 16.84 km2, found within the proximity of urban settlements and eroded shorelines along with the Kozhikode, Beypore, Kadalundi, and Faroke, falls under very high vulnerability to seawater intrusion with vulnerability index values ranging 24.82 to 29.82. In the southern sector, the area of 16.84 km2 between Elathur and Beypore also falls within very high vulnerability zones. Similarly, the area of 37.01 km2 in Quilandi, Faroke, Puthiyankadi, Panniyankara, and the east sector of Kozhikode municipality is seen as high vulnerability zones with the vulnerability index values ranging 19.84 to 24.82. Seawater intrusion estimated under moderate vulnerability zones is found to occupy 47.85 km2 (vulnerability index values 14.88 to 19.84). The low and very low vulnerability zones cover 65.07 and 48.07 km2, with the vulnerability index values ranging 9.92 to 14.88 and 4.96 to 9.92, respectively. When cross-validated using major hydrochemical parameters, the results indicate a strong correlation between the vulnerability index classes and groundwater physicochemical parameters. The sensitivity analysis carried out indicated that the distance from the shoreline (D), impacts of urban growth (U), and depth to groundwater table above sea level (L) to be highly influencing parameters for seawater intrusion vulnerability in the coastal stretches. The modified GALDIT-U model shows reliable accuracy for estimating and demarcating seawater intrusion vulnerability zones and could act as an efficient tool in the sustainable management of coastal aquifers in an urban environment.

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