Journal
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
Volume 6, Issue 6, Pages -Publisher
MDPI AG
DOI: 10.3390/ijgi6060168
Keywords
data fusion; panchromatic; multispectral; imageries; spatial resolution
Funding
- National Sciences and Engineering Council of Canada (NSERC)
- Alberta Innovates Technology Futures (AITF)
- NSERC
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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 mu m) 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 mu m), green (i.e., 0.533-0.590 mu m), red (i.e., 0.636-0.673 mu m), near infrared (NIR: 0.851-0.879 mu m), shortwave infrared-I (SWIR-I: 1.566-1.651 mu m), and SWIR-II (2.107-2.294 mu m) 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, r(2) 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., r(2) values in the range 0.98-0.99 for NDVI, 0.95-0.98 for EVI, 0.98-1.00 for NDWI).
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