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Physical and Environmental Geography Commons™
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Articles 1 - 2 of 2
Full-Text Articles in Physical and Environmental Geography
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, David P. Roy, Jian Li, Hankui Zhang, Lin Yan Dr., Haiyan Huang, Zhongbin Li
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, David P. Roy, Jian Li, Hankui Zhang, Lin Yan Dr., Haiyan Huang, Zhongbin Li
GSCE Faculty Publications
The Sentinel-2A multi-spectral instrument (MSI) acquires multi-spectral reflective wavelength observations with directional effects due to surface reflectance anisotropy and changes in the solar and viewing geometry. Directional effects were examined by considering two ten day periods of Sentinel-2A data acquired close to the solar principal and orthogonal planes over approximately 20° × 10° of southern Africa. More than 6.6 million (January 2016) and 10.6 million (April 2016) pairs of reflectance observations sensed 3 or 7 days apart in the forward and backscatter directions in overlapping Sentinel-2A orbit swaths were considered. The Sentinel-2A data were projected into the MODIS sinusoidal projection …
Using The 500 M Modis Land Cover Product To Derive A Consistent Continental Scale 30 M Landsat Land Cover Classification, Hankui Zhang, David P. Roy
Using The 500 M Modis Land Cover Product To Derive A Consistent Continental Scale 30 M Landsat Land Cover Classification, Hankui Zhang, David P. Roy
GSCE Faculty Publications
Classification is a fundamental process in remote sensing used to relate pixel values to land cover classes present on the surface. Over large areas land cover classification is challenging particularly due to the cost and difficulty of collecting representative training data that enable classifiers to be consistent and locally reliable. A novel methodology to classify large volume Landsat data using high quality training data derived from the 500 m MODIS land cover product is demonstrated and used to generate a 30 m land cover classification for all of North America between 20°N and 50°N. Publically available 30 m global monthly …