Airborne Prism EXperiment Imaging Spectrometer Research Articles

Assessment of the TROPOMI tropospheric NO<sub>2</sub> product based on airborne APEX observations

Abstract. Sentinel-5 Precursor (S-5P), launched in October 2017, carrying the TROPOspheric Monitoring Instrument (TROPOMI) nadir-viewing spectrometer, is the first mission of the Copernicus Programme dedicated to the monitoring of air quality, climate, and ozone. In the presented study, the TROPOMI tropospheric nitrogen dioxide (NO2) level-2 (L2) product (OFFL v1.03.01; 3.5 km × 7 km at nadir observations) has been validated over strongly polluted urban regions by comparison with coincident high-resolution Airborne Prism EXperiment (APEX) remote sensing observations (∼ 75 m × 120 m). Satellite products can be optimally assessed based on (APEX) airborne remote sensing observations, as a large amount of satellite pixels can be fully mapped at high accuracy and in a relatively short time interval, reducing the impact of spatiotemporal mismatches. In the framework of the S-5P validation campaign over Belgium (S5PVAL-BE), the APEX imaging spectrometer has been deployed during four mapping flights (26–29 June 2019) over the two largest urban regions in Belgium, i.e. Brussels and Antwerp, in order to map the horizontal distribution of tropospheric NO2. For each flight, 10 to 20 TROPOMI pixels were fully covered by approximately 2700 to 4000 APEX measurements within each TROPOMI pixel. The TROPOMI and APEX NO2 vertical column density (VCD) retrieval schemes are similar in concept. Overall, for the ensemble of the four flights, the standard TROPOMI NO2 VCD product is well correlated (R = 0.92) but biased negatively by −1.2 ± 1.2 × 1015 molec cm−2 or −14 ± 12 %, on average, with respect to coincident APEX NO2 retrievals. When replacing the coarse 1∘ × 1∘ the massively parallel (MP) version of the Tracer Model version 5 (TM5) a priori NO2 profiles by NO2 profile shapes from the Copernicus Atmospheric Monitoring Service (CAMS) regional chemistry transport model (CTM) ensemble at 0.1∘ × 0.1∘, R is 0.94 and the slope increases from 0.82 to 0.93. The bias is reduced to −0.1 ± 1.0 × 1015 molec cm−2 or −1.0 ± 12 %. The absolute difference is on average 1.3 × 1015 molec cm−2 (16 %) and 0.7 × 1015 molec cm−2 (9 %), when comparing APEX NO2 VCDs with TM5-MP-based and CAMS-based NO2 VCDs, respectively. Both sets of retrievals are well within the mission accuracy requirement of a maximum bias of 25 %–50 % for the TROPOMI tropospheric NO2 product for all individual compared pixels. Additionally, the APEX data set allows the study of TROPOMI subpixel variability and impact of signal smoothing due to its finite satellite pixel size, typically coarser than fine-scale gradients in the urban NO2 field. For a case study in the Antwerp region, the current TROPOMI data underestimate localized enhancements and overestimate background values by approximately 1–2 × 1015 molec cm−2 (10 %–20 %).

Minimizing Reflectance Anisotropy Effects in Airborne Spectroscopy Data Using Ross–Li Model Inversion With Continuous Field Land Cover Stratification

The spectral and radiometric quality of airborne imaging spectrometer data is affected by the anisotropic reflectance behavior of the imaged surface. Illumination and observation angle-dependent patterns of surface reflected radiation propagate into products, hinder quantitative assessment of biophysical/biochemical parameters, and decrease the comparability of data from multiple flight lines. The Ross–Li model, originally developed for multiangular observations, can be inverted to estimate and correct for surface anisotropy effects. This requires land cover be stratified into distinct types of scattering behavior. When the observations subsumed in these classes cover a range of view angles, a pseudo multiangular view on the surface can be employed to invert the Ross–Li model. A discrete land cover classification, however, bears the risk of inappropriate scattering correction resulting in spatial artifacts in the corrected data, predominantly in transition regions of two land cover types (e.g., soil and sparse vegetation with varying fractions). We invert the Ross–Li model on continuous land cover fraction layers. We decompose land cover in dominating structural types using linear spectral unmixing. Ross–Li kernel weights and formulations are estimated for each type independently; the correction is then applied pixel-wise according to the fractional distribution. The corrected Airborne Prism EXperiment imaging spectrometer data show significant reduction of anisotropic reflectance effects of up to 90% (average 60% to 75%, $p=0.05$ ), measured in the overlapping regions of adjacent flight lines. No spatial artifacts or spectral irregularities are observed after correction.

Continuous Fields From Imaging Spectrometer Data for Ecosystem Parameter Mapping and Their Potential for Animal Habitat Assessment in Alpine Regions

Remote sensing offers an objective and efficient way to monitor ecosystem properties including their spatial variability across different land cover types. Especially, the representation of gradients of biochemical and structural properties of ecosystems using continuous fields (CF) approaches bears advantages compared to discrete land cover classification schemes. This paper presents a concept to synergistically generate CF maps of an alpine ecosystem parameter, i.e., total surface water content, from imaging spectrometer (IS) data. Further, the potential of linking such maps to ecological patterns, i.e., the spatial distribution of large ungulates is being assessed. In vegetated areas, total surface water content is considered as a surrogate of plant physiological status. Water is, besides temperature, light, or nutrients, an important limiting growth factor determining biomass production and therefore potential animal forage quantity in alpine grasslands. Resource ecology interested in trophic interactions between large ungulates and their forage requires spatial and temporal information on ecosystem properties and processes. The study area is located in the upper Trupchun Valley (Val Trupchun) in the Swiss National Park (SNP). The valley is famous for its high densities of chamois (Rupicapra rupicapra L.), ibex (Capra ibex L.), and red deer (Cervus elaphus L.). CF maps of total surface water content were derived from Airborne Prism EXperiment (APEX) IS data collected over the SNP in June 2010 and 2011. Abundance maps of predominant land cover classes were derived from linear spectral mixture analysis (SMA). They were then combined with water content information of the respective land cover originating from either empirically or physically based approaches. The resulting CF maps depicted a spatially continuous representation of relative total surface water content. APEX IS data from two consecutive seasons revealed differences in total surface water content in June 2010 and 2011, predominantly related to an advanced phenological development in spring 2011 and to considerable differences in snow cover between the 2 years. Linking total surface water content of grasslands to observed ungulates spatial distributions did not reveal any statistically significant patterns of habitat use. We conclude that water availability in Val Trupchun may not be the dominant limiting factor for potential forage quantity (biomass), or that ungulates choose their grazing sites based on other criteria, i.e., high nutritious quality (P, N). Nevertheless, multitemporal CF maps derived from APEX IS data were found to provide spatially explicit and fine-scaled information for analyses of an ecosystem's total surface water content. The combination of multitemporal CF maps of a wide range of ecosystem parameters and more accurate and extensive observations of animal habitat use will contribute to ongoing and future vegetation-ungulates research in the SNP.

Modeling the noise equivalent radiance requirements of imaging spectrometers based on scientific applications.

The derivation of radiometric specifications for imaging spectrometers from the visible to the short-wave infrared part of the spectrum is a task based on the requirements of potential scientific applications. A method for modeling the noise equivalent radiance at-sensor level is proposed. The model starts with surface reflectance signatures, transforms them to at-sensor signatures, and combines signatures of various applications with regard to performance requirements. The wavelength-dependent delta radiances are then derived at predefined radiance levels by use of a model of the sensor performance. The model is applied with regard to the upcoming Airborne Prism Experiment imaging spectrometer system. A combination of various potential application disciplines forms the basis of the experiment. The results help in the definition of radiometric levels for laboratory calibration of the noise equivalent radiance levels, the quantization of the signal, and the spectral range of an instrument to be designed.