Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Spatial Resolution Enhancement of Vegetation Indexes via Fusion of Hyperspectral and Multispectral Satellite Data
The definition and calculation of a spectral index suitable for characterizing vegetated landscapes depend on the number and widths of the bands of the imaging instrument. Here, we point out the advantages of performing the fusion of hyperspectral (HS) satellite data with the multispectral (MS) bands of Sentinel-2 to calculate such vegetation indexes as the normalized area over reflectance curve (NAOC) and the red-edge inflection point (REIP), which benefit from the availability of quasicontinuous pixel spectra. Unfortunately, MS data may be acquired from satellite platforms with very high spatial resolution; HS data may not. Despite their excellent spectral resolution, satellite imaging spectrometers currently resolve areas not greater than 30 × 30 m2, where different thematic classes of landscape may be mixed together to form a unique pixel spectrum. A way to resolve mixed pixels is to perform the fusion of the HS dataset with the same dataset produced by an MS scanner that images the same scene with a finer spatial resolution. The HS dataset is sharpened from 30 m to 10 m by means of the Sentinel-2 bands that have all been previously brought to 10 m. To do so, the hyper-sharpening protocol, that is, m : n fusion, is exploited in two nested steps: the first one to bring the 20 m bands of Sentinel-2 all to 10 m, the second one to sharpen all the 30 m HS bands to 10 m by using the Sentinel-2 bands previously hyper-sharpened to 10 m. Results are presented on an agricultural test site in The Netherlands imaged by Sentinel-2 and by the satellite imaging spectrometer recently launched as a part of the environmental mapping and analysis program (EnMAP). Firstly, the excellent match of statistical consistency of the fused HS data to the original MS and HS data is evaluated by means of analysis tools, existing and developed ad hoc for this specific case. Then, the spatial and radiometric accuracy of REIP and NAOC calculated from fused HS data are analyzed on the classes of pure and mixed pixels. On pure pixels, the ...
Spatial Resolution Enhancement of Vegetation Indexes via Fusion of Hyperspectral and Multispectral Satellite Data
The definition and calculation of a spectral index suitable for characterizing vegetated landscapes depend on the number and widths of the bands of the imaging instrument. Here, we point out the advantages of performing the fusion of hyperspectral (HS) satellite data with the multispectral (MS) bands of Sentinel-2 to calculate such vegetation indexes as the normalized area over reflectance curve (NAOC) and the red-edge inflection point (REIP), which benefit from the availability of quasicontinuous pixel spectra. Unfortunately, MS data may be acquired from satellite platforms with very high spatial resolution; HS data may not. Despite their excellent spectral resolution, satellite imaging spectrometers currently resolve areas not greater than 30 × 30 m2, where different thematic classes of landscape may be mixed together to form a unique pixel spectrum. A way to resolve mixed pixels is to perform the fusion of the HS dataset with the same dataset produced by an MS scanner that images the same scene with a finer spatial resolution. The HS dataset is sharpened from 30 m to 10 m by means of the Sentinel-2 bands that have all been previously brought to 10 m. To do so, the hyper-sharpening protocol, that is, m : n fusion, is exploited in two nested steps: the first one to bring the 20 m bands of Sentinel-2 all to 10 m, the second one to sharpen all the 30 m HS bands to 10 m by using the Sentinel-2 bands previously hyper-sharpened to 10 m. Results are presented on an agricultural test site in The Netherlands imaged by Sentinel-2 and by the satellite imaging spectrometer recently launched as a part of the environmental mapping and analysis program (EnMAP). Firstly, the excellent match of statistical consistency of the fused HS data to the original MS and HS data is evaluated by means of analysis tools, existing and developed ad hoc for this specific case. Then, the spatial and radiometric accuracy of REIP and NAOC calculated from fused HS data are analyzed on the classes of pure and mixed pixels. On pure pixels, the ...
Spatial Resolution Enhancement of Vegetation Indexes via Fusion of Hyperspectral and Multispectral Satellite Data
Alparone, Luciano (Autor:in) / Arienzo, Alberto (Autor:in) / Garzelli, Andrea (Autor:in) / Alparone, Luciano / Arienzo, Alberto / Garzelli, Andrea
01.01.2024
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
DDC:
710
Mapping salt-marsh vegetation by multispectral and hyperspectral remote sensing
Online Contents | 2006
|Coupled Nonnegative Matrix Factorization Unmixing for Hyperspectral and Multispectral Data Fusion
Online Contents | 2012
|