NDLI: Multisensory data fusion methods for the estimation of beach sediment features: Mineralogical, grain size and moisture

Content Provider	IEEE Xplore Digital Library
Author	Innocenti, C. Filipponi, F. Valentini, E. Taramelli, A.
Copyright Year	2013
Description	Author affiliation: ISPRA-Inst. for Environ. Protection & Res., Rome, Italy (Innocenti, C.; Filipponi, F.; Valentini, E.; Taramelli, A.)
Abstract	The research presented in this paper belongs to a wider research aimed to test innovative remote sensed techniques for the environmental and ecological characterization of emerged and submerged coastal areas [1]. Here we focus on multisensory data fusion methods for the estimation of beach sediment parameters (mineralogy, grain size and moisture content) applied to a 22 km long sandy beach, in the Sabaudia-Latina physiographic unit (central Italy) (Fig. 1). The lithologic composition and grain size distribution of sediments are primary determinants of their inherent reflectance properties [2,3]. Moreover, moisture content is also known to have a strong influence on reflectance of soils and sediments. If the effects of sediment composition, grain size and moisture content could be distinguished spectrally, it might be possible to map these properties at synoptic scales using hyperspectral, or perhaps even broadband, remote sensing in conjunction with few field sampling measures. In this study, we attempt to estimate the distribution of each of the above parameters through a multi linear regression model of airborne hyperspectral bands.
Sponsorship	IEEE Geosci. Remote Sens. Soc.
Starting Page	3064
Ending Page	3067
File Size	1149367
Page Count	4
File Format	PDF
ISBN	9781479911141
ISSN	21536996
DOI	10.1109/IGARSS.2013.6723473
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-07-21
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Sediments Grain size Moisture Hyperspectral imaging Atmospheric modeling beach MIVIS Sediment multi linear regression
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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