Please use this identifier to cite or link to this item: http://idr.nitk.ac.in/jspui/handle/123456789/14846
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dc.contributor.authorChitale M.M.
dc.contributor.authorKundapura S.
dc.date.accessioned2021-05-05T10:15:52Z-
dc.date.available2021-05-05T10:15:52Z-
dc.date.issued2021
dc.identifier.citationLecture Notes in Civil Engineering , Vol. 99 , , p. 735 - 751en_US
dc.identifier.urihttps://doi.org/10.1007/978-981-15-6828-2_54
dc.identifier.urihttp://idr.nitk.ac.in/jspui/handle/123456789/14846-
dc.description.abstractQuick and accurate mapping of properties of soil is considered to be critical for agriculture and environmental management. Rapid assessment of soil properties is a daunting task in monitoring the environment. The conventional field sampling is a laborious as well as time-consuming job. The conventional methods are restricted to a specific region but there is a need to analyses the soil properties at landscape levels. Hence, this study emphasises on hyperspectral remote sensing which to some extent helps in rapid assessment of the properties. The hyperspectral data used for the study is AVIRIS-NG data. The study explored the potential of AVIRIS-NG hyperspectral data in mapping soil properties which were analysed by in situ laboratory methods and compared with them by geostatistical method of spatial interpolation. Hence, the method adopted for this purpose is the study on spatial variability of soil properties by using Kriging interpolation technique. Also, a review study is carried out on the visible and near-infrared analysis (VNIRA), multiple regression analysis approach and spectral angle mapper supervised classification technique on the high-resolution AVIRIS-NG Hyperspectral data, which will yield as an empirical model for predicting the soil property in question from both wet chemistry and spectral information of a representative set of samples and classifies the data accordingly. © Springer Nature Singapore Pte Ltd 2021.en_US
dc.titleHigh-resolution mapping of soil properties using aviris-ng hyperspectral remote sensing data—a case study over lateritic soils in mangalore, indiaen_US
dc.typeConference Paperen_US
Appears in Collections:2. Conference Papers

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