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Open AccessArticle

Pan-Sharpening of Landsat-8 Images and Its Application in Calculating Vegetation Greenness and Canopy Water Contents

Department of Geomatics Engineering, Schulich School of Engineering, University of Calgary, 2500 University Drive NW, Calgary, AB T2N 1N4, Canada
Author to whom correspondence should be addressed.
Academic Editors: Jason K. Levy and Wolfgang Kainz
ISPRS Int. J. Geo-Inf. 2017, 6(6), 168;
Received: 4 April 2017 / Revised: 18 May 2017 / Accepted: 5 June 2017 / Published: 7 June 2017
Pan-sharpening is the process of fusing higher spatial resolution panchromatic (PAN) with lower spatial resolution multispectral (MS) imagery to create higher spatial resolution MS images. Here, our overall objective was to pan-sharpen Landsat-8 images and calculate vegetation greenness (i.e., normalized difference vegetation index (NDVI)), canopy structure (i.e., enhanced vegetation index (EVI)), and canopy water content (i.e., normalized difference water index (NDWI))-related variables. Our proposed methods consisted of: (i) evaluating the relationships between PAN band (0.503–0.676 µm) with a spatial resolution of 15 m and individual MS bands of Landsat-8 from blue (i.e., acquiring in the range 0.452–0.512 µm), green (i.e., 0.533–0.590 µm), red (i.e., 0.636–0.673 µm), near infrared (NIR: 0.851–0.879 µm), shortwave infrared-I (SWIR-I: 1.566–1.651 µm), and SWIR-II (2.107–2.294 µm) bands with a spatial resolution of 30 m; (ii) determining the suitable individual MS bands to be enhanced into the spatial resolution of the PAN band; and (iii) calculating several vegetation greenness and canopy moisture indices (i.e., NDVI, EVI, NDWI-I, and NDWI-II) at 15 m spatial resolution and subsequent validation using their equivalent-values at a spatial resolution of 30 m. Our analysis revealed that strong linear relationships existed between the PAN and most of the MS individual bands of interest except NIR. For example, r2 values were 0.86–0.89 for blue band; 0.89–0.95 for green band; 0.84–0.96 for red band; 0.71–0.79 for SWIR-I band; and 0.71–0.83 for SWIR-II band. As a result, we performed smoothing filter-based intensity modulation method of pan-sharpening to enhance the spatial resolution of 30 m to 15 m. In calculating the vegetation indices, we used the enhanced MS images and resampled the NIR to 15 m. Finally, we evaluated these indices with their equivalents at 30 m spatial resolution and observed strong relationships (i.e., r2 values in the range 0.98–0.99 for NDVI, 0.95–0.98 for EVI, 0.98–1.00 for NDWI). View Full-Text
Keywords: data fusion; panchromatic; multispectral; imageries; spatial resolution data fusion; panchromatic; multispectral; imageries; spatial resolution
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Rahaman, K.R.; Hassan, Q.K.; Ahmed, M.R. Pan-Sharpening of Landsat-8 Images and Its Application in Calculating Vegetation Greenness and Canopy Water Contents. ISPRS Int. J. Geo-Inf. 2017, 6, 168.

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