Hyperspectral Empirical Absolute Calibration Model Using Libya 4 Pseudo Invariant Calibration Site

The objective of this paper is to find an empirical hyperspectral absolute calibration model using Libya 4 pseudo invariant calibration site (PICS). The approach involves using the Landsat 8 (L8) Operational Land Imager (OLI) as the reference radiometer and using Earth Observing One (EO-1) Hyperion, with a spectral resolution of 10 nm as a hyperspectral source. This model utilizes data from a region of interest (ROI) in an “optimal region” of 3% temporal, spatial, and spectral stability within the Libya 4 PICS. It uses an improved, simple, empirical, hyperspectral Bidirectional Reflectance Distribution function (BRDF) model accounting for four angles: solar zenith and azimuth, and view zenith and azimuth angles. This model can perform absolute calibration in 1 nm spectral resolution by predicting TOA reflectance in all existing spectral bands of the sensors. The resultant model was validated with image data acquired from satellite sensors such as Landsat 7, Sentinel 2A, and Sentinel 2B, Terra MODIS, Aqua MODIS, from their launch date to 2020. These satellite sensors differ in terms of the width of their spectral bandpass, overpass time, off-nadir viewing capabilities, spatial resolution, and temporal revisit time, etc. The result demonstrates the efficacy of the proposed model has an accuracy of the order of 3% with a precision of about 3% for the nadir viewing sensors (with view zenith angle up to 5) used in the study. For the off-nadir viewing satellites with view zenith angle up to 20, it can have an estimated accuracy of 6% and precision of 4%.

Adjusting ISCCP cloud detection to increase consistency of cloud amount and reduce artifacts

The International Satellite Cloud Climatology Project (ISCCP) began collecting data in the 1980s to help understand the distribution of clouds. Since then, it has provided important information on clouds in time and space and their radiative characteristics. However, it was apparent from some long term time series of the data that there are some latent artifacts related to the changing satellite coverage over the more than thirty years of the record. Changes in satellite coverage effectively create secular changes in the time series of view zenith angle (VZA) for a given location. There is an inconsistency in the current ISCCP cloud detection algorithm related to VZA: two satellites viewing the same location from different VZAs can produce vastly different estimates of cloud amount. Research is presented which shows that a simple change to the cloud detection algorithm can vastly increase the consistency. This is accomplished by making the cloud/no cloud threshold VZA dependent. The resulting cloud amounts are more consistent between different satellites and the distributions are shown to be more spatially homogenous. Likewise, the more consistent spatial data leads to more consistent temporal statistics.

Estimation of LAI in Winter Wheat from Multi-Angular Hyperspectral VNIR Data: Effects of View Angles and Plant Architecture

View angle effects present in crop canopy spectra are critical for the retrieval of the crop canopy leaf area index (LAI). In the past, the angular effects on spectral vegetation indices (VIs) for estimating LAI, especially in crops with different plant architectures, have not been carefully assessed. In this study, we assessed the effects of the view zenith angle (VZA) on relationships between the spectral VIs and LAI. We measured the multi-angular hyperspectral reflectance and LAI of two cultivars of winter wheat, erectophile (W411) and planophile (W9507), across different growing seasons. The reflectance of each angle was used to calculate a variety of VIs that have already been published in the literature as well as all possible band combinations of Normalized Difference Spectral Indices (NDSIs). The above indices, along with the raw reflectance of representative bands, were evaluated with measured LAI across the view zenith angle for each cultivar of winter wheat. Data analysis was also supported by the use of the PROSAIL (PROSPECT + SAIL) model to simulate a range of bidirectional reflectance. The study confirmed that the strength of linear relationships between different spectral VIs and LAI did express different angular responses depending on plant type. LAI–VI correlations were generally stronger in erectophile than in planophile wheat types, especially at the zenith angle where the background is expected to be more evident for erectophile type wheat. The band combinations and formulas of the indices also played a role in shaping the angular signatures of the LAI–VI correlations. Overall, off-nadir angles served better than nadir angle and narrow-band indices, especially NDSIs with combinations of a red-edge (700~720 nm) and a green band, were more useful for LAI estimation than broad-band indices for both types of winter wheat. But the optimal angles much differed between two plant types and among various VIs. High significance (R2 > 0.9) could be obtained by selecting appropriate VIs and view angles on both the backward and forward scattering direction. These results from the in-situ measurements were also corroborated by the simulation analysis using the PROSAIL model. For the measured datasets, the highest coefficient was obtained by NDSI(536,720) at −35° in the backward (R2 = 0.971) and NDSI(571,707) at 55° in the forward scattering direction (R2 = 0.984) for the planophile and erectophile varieties, respectively. This work highlights the influence of view geometry and plant architecture. The identification of crop plant type is highly recommended before using remote sensing VIs for the large-scale mapping of vegetation biophysical variables.

Improved ozone profile retrievals from GOME data with degradation correction in reflectance

We present a simple method to perform degradation correction to Global Ozone Monitoring Experiment (GOME) reflectance spectra by comparing the average reflectance for 60° N–60° S with that at the beginning of GOME observations after removing the dependences on solar zenith angle and seasonal variation. The results indicate positive degradation of up to ~15–25% in the wavelength range 289–370 nm during 2000–2002; the degradation also exhibits significant dependence on wavelength and view zenith angle. These results are consistent with previous studies using radiative transfer models and ozone observations or climatology. The degradation causes retrieval biases of up to ~3% (10 DU, 1 DU=2.69×1016 molecules cm−2), 30% (10 DU), 10%, and 40% in total column ozone, tropospheric column ozone, stratospheric ozone and tropospheric ozone, respectively, from our GOME ozone profile retrieval algorithm. The application of this degradation correction generally improves the retrievals relative to Dobson and ozonesonde measurements during 2000–2003 and improves the retrieval consistency during 1996–2003.