Abstract
The Harmonized Landsat/Sentinel-2 (HLS) project aims to generate a seamless surface reflectance product by combining observations from USGS/NASA Landsat-8 and ESA Sentinel-2 remote sensing satellites. These satellites’ sampling characteristics provide nearly constant observation geometry and low illumination variation through the scene. However, the illumination variation throughout the year impacts the surface reflectance by producing higher values for low solar zenith angles and lower reflectance for large zenith angles. In this work, we present a model to derive the bidirectional reflectance distribution function (BRDF) normalization and apply it to the HLS product at 30 m spatial resolution. It is based on the BRDF parameters estimated from the MODerate Resolution Imaging Spectroradiometer (MODIS) surface reflectance product (M{O,Y}D09) at 1 km spatial resolution using the VJB method (Vermote et al., 2009). Unsupervised classification (segmentation) of HLS images is used to disaggregate the BRDF parameters to the HLS spatial resolution and to build a BRDF parameters database at HLS scale. We first test the proposed BRDF normalization for different solar zenith angles over two homogeneous sites, in particular one desert and one Peruvian Amazon forest. The proposed method reduces both the correlation with the solar zenith angle and the coefficient of variation (CV) of the reflectance time series in the red and near infrared bands to 4% in forest and keeps a low CV of 3% to 4% for the deserts. Additionally, we assess the impact of the view zenith angle (VZA) in an area of the Brazilian Amazon forest close to the equator, where impact of the angular variation is stronger because it occurs in the principal plane. The directional reflectance shows a strong dependency with the VZA. The current HLS BRDF correction reduces this dependency but still shows an under-correction, especially in the near infrared, while the proposed method shows no dependency with the view angles. We also evaluate the BRDF parameters using field surface albedo measurements as a reference over seven different sites of the US surface radiation budget observing network (SURFRAD) and five sites of the Australian OzFlux network.
Highlights
The Harmonized Landsat/Sentinel-2 (HLS) project [1] provides a surface reflectance product that combines observations from USGS/NASA’s Landsat 8 and ESA’s Sentinel-2 satellites at moderate spatial resolution (30 m)
Along with a common atmospheric correction algorithm [2], geometric resampling to 30 m spatial resolution and geographic registration [1], the product is corrected for Bidirectional Reflectance Distribution Function (BRDF) effects and band pass adjustment
We describe the adaptation of the method of Franch [11,14] for HLS BRDF normalization, apply the proposed method to the HLS product from 2013 to 2017 and validate its applicability to Landsat 8 and Sentinel 2 data, test it on three homogeneous sites to assess its capability to remove BRDF artifacts, and evaluate it through the comparison to ground albedo measurements over surface radiation budget observing network (SURFRAD) and OzFlux networks
Summary
The Harmonized Landsat/Sentinel-2 (HLS) project [1] provides a surface reflectance product that combines observations from USGS/NASA’s Landsat 8 and ESA’s Sentinel-2 satellites at moderate spatial resolution (30 m). Gao [4] concluded that for Landsat-like narrow swath sensors, the major BRDF effect arises from the day of year effect, and can cause variations of 0.04–0.06 reflectance compared to mid-summer observations Such angular effects can be corrected using a Bidirectional Reflectance Distribution Function (BRDF) model. Shuai [6] used the MODIS Bidirectional Reflectance Distribution Function (BRDF) MDC43 product at 500 m [7] to generate a Landsat surface albedo product that later was implemented back to the 80s to the “pre-MODIS era” [8] Their method achieves a Root Mean Square Error (RMSE) generally lower than 0.03 (12%) when compared with in situ data. We describe the adaptation of the method of Franch [11,14] for HLS BRDF normalization, apply the proposed method to the HLS product from 2013 to 2017 and validate its applicability to Landsat 8 and Sentinel 2 data, test it on three homogeneous sites to assess its capability to remove BRDF artifacts, and evaluate it through the comparison to ground albedo measurements over SURFRAD and OzFlux networks
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