Landsat 15-m Panchromatic-Assisted Downscaling (LPAD) of the 30-m Reflective Wavelength Bands to Sentinel-2 20-m Resolution

The Landsat 15-m Panchromatic-Assisted Downscaling (LPAD) method to downscale Landsat-8 Operational Land Imager (OLI) 30-m data to Sentinel-2 multi-spectral instrument (MSI) 20-m resolution is presented. The method first downscales the Landsat-8 30-m OLI bands to 15-m using the spatial detail provided by the Landsat-8 15-m panchromatic band and then reprojects and resamples the downscaled 15-m data into registration with Sentinel-2A 20-m data. The LPAD method is demonstrated using pairs of contemporaneous Landsat-8 OLI and Sentinel-2A MSI images sensed less than 19 min apart over diverse geographic environments. The LPAD method is shown to introduce less spectral and spatial distortion and to provide visually more coherent data than conventional bilinear and cubic convolution resampled 20-m Landsat OLI data. In addition, results for a pair of Landsat-8 and Sentinel-2A images sensed one day apart suggest that image fusion should be undertaken with caution when the images are acquired under different atmospheric conditions. The LPAD source code is available at GitHub for public use.

[1]  M. Claverie,et al.  Preliminary analysis of the performance of the Landsat 8/OLI land surface reflectance product. , 2016, Remote sensing of environment.

[2]  Serge Rambal,et al.  Downscaling MODIS-derived maps using GIS and boosted regression trees: The case of frost occurrence over the arid Andean highlands of Bolivia , 2011 .

[3]  Bo Huang,et al.  Support Vector Regression-Based Downscaling for Intercalibration of Multiresolution Satellite Images , 2013, IEEE Transactions on Geoscience and Remote Sensing.

[4]  Gérard Dedieu,et al.  Assessing the robustness of Random Forests to map land cover with high resolution satellite image time series over large areas , 2016 .

[5]  Jocelyn Chanussot,et al.  Synthesis of Multispectral Images to High Spatial Resolution: A Critical Review of Fusion Methods Based on Remote Sensing Physics , 2008, IEEE Transactions on Geoscience and Remote Sensing.

[6]  Alan R. Gillespie,et al.  Color enhancement of highly correlated images. II. Channel ratio and “chromaticity” transformation techniques , 1987 .

[7]  Martha C. Anderson,et al.  Daily Landsat-scale evapotranspiration estimation over a forested landscape in North Carolina, USA using multi-satellite data fusion , 2016 .

[8]  Hankui K. Zhang,et al.  A general method to normalize Landsat reflectance data to nadir BRDF adjusted reflectance , 2016 .

[9]  Lawrence Ong,et al.  Landsat-8 Operational Land Imager Radiometric Calibration and Stability , 2014, Remote. Sens..

[10]  Gérard Dedieu,et al.  A Multi-Temporal and Multi-Spectral Method to Estimate Aerosol Optical Thickness over Land, for the Atmospheric Correction of FormoSat-2, LandSat, VENμS and Sentinel-2 Images , 2015, Remote. Sens..

[11]  Matthew F. McCabe,et al.  Effects of spatial aggregation on the multi-scale estimation of evapotranspiration , 2013 .

[12]  Michael A. Lefsky,et al.  A flexible spatiotemporal method for fusing satellite images with different resolutions , 2016 .

[13]  Martha C. Anderson,et al.  A Multiscale Remote Sensing Model for Disaggregating Regional Fluxes to Micrometeorological Scales , 2004 .

[14]  D. Roy,et al.  An empirical investigation of image resampling effects upon the spectral and textural supervised classification of a high spatial resolution multispectral image , 1996 .

[15]  Martha C. Anderson,et al.  Landsat-8: Science and Product Vision for Terrestrial Global Change Research , 2014 .

[16]  Jocelyn Chanussot,et al.  A Critical Comparison Among Pansharpening Algorithms , 2015, IEEE Transactions on Geoscience and Remote Sensing.

[17]  Frédéric Baret,et al.  Intercalibration of vegetation indices from different sensor systems , 2003 .

[18]  T. Eck,et al.  Variability of Absorption and Optical Properties of Key Aerosol Types Observed in Worldwide Locations , 2002 .

[19]  R. Keys.  Cubic convolution interpolation for digital image processing , 1981 .

[20]  Gregory Duveiller,et al.  Spatially downscaling sun-induced chlorophyll fluorescence leads to an improved temporal correlation with gross primary productivity , 2016 .

[21]  Matthias Drusch,et al.  Sentinel-2: ESA's Optical High-Resolution Mission for GMES Operational Services , 2012 .

[22]  Andrea Garzelli,et al.  Hypercomplex Quality Assessment of Multi/Hyperspectral Images , 2009, IEEE Geoscience and Remote Sensing Letters.

[23]  John L. Dwyer,et al.  Landsat: building a strong future , 2012 .

[24]  Hankui K. Zhang,et al.  Examination of Sentinel-2A Multi-spectral Instrument (MSI) Reflectance Anisotropy and the Suitability of a General Method to Normalize MSI Reflectance to Nadir BRDF Adjusted Reflectance , 2017 .

[25]  Eero P. Simoncelli,et al.  Image quality assessment: from error visibility to structural similarity , 2004, IEEE Transactions on Image Processing.

[26]  Lin Yan,et al.  An Automated Approach for Sub-Pixel Registration of Landsat-8 Operational Land Imager (OLI) and Sentinel-2 Multi Spectral Instrument (MSI) Imagery , 2016, Remote. Sens..

[27]  Hongliang Fang,et al.  Atmospheric correction of Landsat ETM+ land surface imagery. I. Methods , 2001, IEEE Trans. Geosci. Remote. Sens..

[28]  Hankui K. Zhang,et al.  Characterization of Landsat-7 to Landsat-8 reflective wavelength and normalized difference vegetation index continuity. , 2016, Remote sensing of environment.

[29]  J. Irons,et al.  Landsat 8: The plans, the reality, and the legacy , 2016 .

[30]  Peter Strobl,et al.  Copernicus Sentinel-2 Calibration and Validation , 2019, European Journal of Remote Sensing.

[31]  Christine Pohl,et al.  Multisensor image fusion in remote sensing: concepts, methods and applications , 1998 .

[32]  Guoman Huang,et al.  A Parallel Computing Paradigm for Pan-Sharpening Algorithms of Remotely Sensed Images on a Multi-Core Computer , 2014, Remote. Sens..

[33]  Nicholas C. Coops,et al.  Virtual constellations for global terrestrial monitoring , 2015 .

[34]  Julia A. Barsi,et al.  The next Landsat satellite: The Landsat Data Continuity Mission , 2012 .

[35]  David P. Roy,et al.  A note on the temporary misregistration of Landsat-8 Operational Land Imager (OLI) and Sentinel-2 Multi Spectral Instrument (MSI) imagery , 2016 .

[36]  S. Baronti,et al.  Remote Sensing Image Fusion , 2015 .

[37]  Serhiy Skakun,et al.  Automatic sub-pixel co-registration of Landsat-8 Operational Land Imager and Sentinel-2A Multi-Spectral Instrument images using phase correlation and machine learning based mapping , 2017, Int. J. Digit. Earth.

[38]  Matthew Montanaro,et al.  Stray Light Artifacts in Imagery from the Landsat 8 Thermal Infrared Sensor , 2014, Remote. Sens..

[39]  Lawrence Ong,et al.  Landsat-8 Operational Land Imager (OLI) Radiometric Performance On-Orbit , 2015, Remote. Sens..

[40]  D. Roy,et al.  Web-enabled Landsat Data (WELD): Landsat ETM+ composited mosaics of the conterminous United States , 2010 .

[41]  Yaping Yang,et al.  Mapping Extent Dynamics of Small Lakes Using Downscaling MODIS Surface Reflectance , 2017, Remote. Sens..

[42]  Christopher O. Justice,et al.  Meeting Earth Observation Requirements for Global Agricultural Monitoring: An Evaluation of the Revisit Capabilities of Current and Planned Moderate Resolution Optical Earth Observing Missions , 2015, Remote. Sens..

[43]  Andrea Garzelli,et al.  A Review of Image Fusion Algorithms Based on the Super-Resolution Paradigm , 2016, Remote. Sens..

[44]  Seymour Shlien,et al.  Geometric Correction, Registration, and Resampling of Landsat Imagery , 1979 .

[45]  Michael E. Schaepman,et al.  Sentinels for science: potential of Sentinel-1, -2, and -3 missions for scientific observations of ocean, cryosphere, and land , 2012 .

[46]  D. Roy,et al.  Conterminous United States demonstration and characterization of MODIS-based Landsat ETM+ atmospheric correction☆ , 2014 .

[47]  Gabriele Bitelli,et al.  Preliminary Comparison of Sentinel-2 and Landsat 8 Imagery for a Combined Use , 2016, Remote. Sens..

[48]  R. Houborg,et al.  Impacts of dust aerosol and adjacency effects on the accuracy of Landsat 8 and RapidEye surface reflectances , 2017 .

[49]  Yifan Zhang,et al.  Noise-Resistant Wavelet-Based Bayesian Fusion of Multispectral and Hyperspectral Images , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[50]  D. Greslou,et al.  Sentinel-2 geometric image quality commissioning: first results , 2015, SPIE Remote Sensing.

[51]  Venkataramana Sridhar,et al.  Evapotranspiration Estimation and Scaling Effects Over The Nebraska Sandhills , 2007 .

[52]  Hankui K. Zhang,et al.  A New Look at Image Fusion Methods from a Bayesian Perspective , 2015, Remote. Sens..

[53]  Robert A. Schowengerdt,et al.  Image reconstruction by parametric cubic convolution , 1982, Comput. Graph. Image Process..

[54]  Gérard Dedieu,et al.  Assessment of an Operational System for Crop Type Map Production Using High Temporal and Spatial Resolution Satellite Optical Imagery , 2015, Remote. Sens..

[55]  Gérard Dedieu,et al.  Building a Data Set over 12 Globally Distributed Sites to Support the Development of Agriculture Monitoring Applications with Sentinel-2 , 2015, Remote. Sens..

[56]  Martha C. Anderson,et al.  Toward mapping crop progress at field scales through fusion of Landsat and MODIS imagery , 2017 .

[57]  Kenton Lee,et al.  Landsat 8 Operational Land Imager On-Orbit Geometric Calibration and Performance , 2014, Remote. Sens..

[58]  Luciano Alparone,et al.  Bi-cubic interpolation for shift-free pan-sharpening , 2013 .

[59]  Jian Li,et al.  Best practices for the reprojection and resampling of Sentinel-2 Multi Spectral Instrument Level 1C data , 2016 .

[60]  D. Roy,et al.  Continental-scale Validation of MODIS-based and LEDAPS Landsat ETM+ Atmospheric Correction Methods , 2012 .

[61]  Andreas Kääb,et al.  Glacier Remote Sensing Using Sentinel-2. Part II: Mapping Glacier Extents and Surface Facies, and Comparison to Landsat 8 , 2016, Remote. Sens..

[62]  David P. Roy,et al.  Computationally Inexpensive Landsat 8 Operational Land Imager (OLI) Pansharpening , 2016, Remote. Sens..

[63]  Peter M. Atkinson,et al.  Fusion of Landsat 8 OLI and Sentinel-2 MSI Data , 2017, IEEE Transactions on Geoscience and Remote Sensing.