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Remote Sens. 2018, 10(8), 1308; https://doi.org/10.3390/rs10081308

Multispectral Pansharpening with Radiative Transfer-Based Detail-Injection Modeling for Preserving Changes in Vegetation Cover

1
Department of Information Engineering and Mathematics, University of Siena, 53100 Siena, Italy
2
Institute of Applied Physics “Nello Carrara”, IFAC-CNR, Research Area of Florence, 50019 Sesto Fiorentino (FI), Italy
3
Department of Information Engineering, University of Florence, 50139 Florence, Italy
4
Institute of Methodologies for Environmental Analysis, CNR–IMAA, 85050 Tito Scalo (PZ), Italy AND NASA-JCET, Greenbelt, MD 20771, USA
5
Department of Information Engineering, Electrical Engineering and Applied Mathematics, University of Salerno, 84084 Fisciano (SA), Italy
*
Author to whom correspondence should be addressed.
Received: 27 July 2018 / Revised: 9 August 2018 / Accepted: 9 August 2018 / Published: 19 August 2018
(This article belongs to the Section Forest Remote Sensing)
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Abstract

Whenever vegetated areas are monitored over time, phenological changes in land cover should be decoupled from changes in acquisition conditions, like atmospheric components, Sun and satellite heights and imaging instrument. This especially holds when the multispectral (MS) bands are sharpened for spatial resolution enhancement by means of a panchromatic (Pan) image of higher resolution, a process referred to as pansharpening. In this paper, we provide evidence that pansharpening of visible/near-infrared (VNIR) bands takes advantage of a correction of the path radiance term introduced by the atmosphere, during the fusion process. This holds whenever the fusion mechanism emulates the radiative transfer model ruling the acquisition of the Earth’s surface from space, that is for methods exploiting a multiplicative, or contrast-based, injection model of spatial details extracted from the panchromatic (Pan) image into the interpolated multispectral (MS) bands. The path radiance should be estimated and subtracted from each band before the product by Pan is accomplished. Both empirical and model-based estimation techniques of MS path radiances are compared within the framework of optimized algorithms. Simulations carried out on two GeoEye-1 observations of the same agricultural landscape on different dates highlight that the de-hazing of MS before fusion is beneficial to an accurate detection of seasonal changes in the scene, as measured by the normalized differential vegetation index (NDVI). View Full-Text
Keywords: atmospheric path-radiance; change analysis; detail injection modeling; haze; data fusion; normalized differential vegetation index (NDVI); pansharpening; radiative transfer atmospheric path-radiance; change analysis; detail injection modeling; haze; data fusion; normalized differential vegetation index (NDVI); pansharpening; radiative transfer
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Garzelli, A.; Aiazzi, B.; Alparone, L.; Lolli, S.; Vivone, G. Multispectral Pansharpening with Radiative Transfer-Based Detail-Injection Modeling for Preserving Changes in Vegetation Cover. Remote Sens. 2018, 10, 1308.

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