Global evaluation of the precipitable-water-vapor product from MERSI-II (Medium Resolution Spectral Imager) on board the Fengyun-3D satellite

Atmospheric water vapor plays a key role in Earth's radiation balance and hydrological cycle, and the precipitable-water-vapor (PWV) product under clear-sky conditions has been routinely provided by the advanced Medium Resolution Spectral Imager (MERSI-II) on board Fengyun-3D since 2018. The global evaluation of the PWV product derived from MERSI-II is performed herein by comparing it with PWV from the Integrated Global Radiosonde Archive (IGRA) based on a total of 462 sites (57 219 matchups) during 2018–2021. The monthly averaged PWV from MERSI-II presents a decreasing distribution of PWV from the tropics to the polar regions. In general, a sound consistency exists between PWV values of MERSI-II and IGRA; their correlation coefficient is 0.951, and their root mean squared error (RMSE) is 0.36 cm. The histogram of mean bias (MB) shows that the MB is concentrated around zero and mostly located within the range from −1.00 cm to 0.50 cm. For most sites, PWV is underestimated with the MB between −0.41 and 0.05 cm. However, there is also an overestimated PWV, which is mostly distributed in the area surrounding the Black Sea and the middle of South America. There is a slight underestimation of MERSI-II PWV for all seasons with the MB value below −0.18 cm, with the bias being the largest magnitude in summer. This is probably due to the presence of thin clouds, which weaken the radiation signal observed by the satellite. We also find that there is a larger bias in the Southern Hemisphere, with a large value and significant variation in PWV. The binned error analysis revealed that the MB and RMSE increased with the increasing value of PWV, but there is an overestimation for PWV smaller than 1.0 cm. In addition, there is a higher MB and RMSE with a larger spatial distance between the footprint of the satellite and the IGRA station, and the RMSE ranged from 0.33 to 0.47 cm. There is a notable dependency on solar zenith angle of the deviations between MERSI-II and IGRA PWV products.

A New Algorithm for Extracting Winter Wheat Planting Area Based on Ownership Parcel Vector Data and Medium-Resolution Remote Sensing Images

In the complex planting area with scattered parcels, combining the parcel vector data with remote sensing images to extract the winter wheat planting information can make up for the deficiency of the classification from remote sensing images simply. It is a feasible direction for precision agricultural subsidies, but it is difficult to collect large-scale parcel data and obtain high spatial resolution or time-series remote sensing images in mass production. It is a beneficial exploration of making use of existing parcel data generated by the ground survey and medium-resolution remote sensing images with suitable time and spatial resolution to extract winter wheat planting areas for large-scale precision agricultural subsidies. Therefore, this paper proposes a new algorithm to extract winter wheat planting areas based on ownership parcel data and medium-resolution remote sensing images for improving classification accuracy. Initially, the segmentation of the image is carried out. To this end, the parcel data is used to generate the region of interest (ROI) of each parcel. Second, the homogeneity of each ROI is detected by its statistical indices (mean value and standard deviation). Third, the parallelepiped classifier and rule-based feature extraction classification methods are utilized to conduct the homogeneous and nonhomogeneous ROIs. Finally, two classification results are combined as the final classification result. The new algorithm was applied to a complex planting area of 103.60 km2 in central China based on the ownership parcel data and Gaofen-1 PMS and WFV remote sensing images in this paper. The experimental results show that the new algorithm can effectively extract winter wheat planting area, eliminate the problem of salt-and-pepper noise, and obtain high-precision classification results (kappa = 0.9279, overall accuracy = 96.41%, user’s accuracy = 99.16%, producer’s accuracy = 93.39%, commission errors = 0.84%, and omission errors = 6.61%) when the size of ownership parcels matches the spatial resolution of remote sensing images.

Land Surface Temperature Retrieval from Fengyun-3D Medium Resolution Spectral Imager II (FY-3D MERSI-II) Data with the Improved Two-Factor Split-Window Algorithm

Land surface temperature (LST) is an essential parameter widely used in environmental studies. The Medium Resolution Spectral Imager II (MERSI-II) boarded on the second generation Chinese polar-orbiting meteorological satellite, Fengyun-3D (FY-3D), provides a new opportunity for LST retrieval at a spatial resolution of 250 m that is higher than that of the already widely used Moderate Resolution Imaging Spectrometer (MODIS) LST data of 1000 m. However, there is no operational LST product from FY-3D MERSI-II data available for free access. Therefore, in this study, we developed an improved two-factor split-window algorithm (TFSWA) of LST retrieval from this data source as it has two thermal-infrared (TIR) bands. The essential coefficients of the TFSWA algorithm have been carefully and precisely estimated for the FY-3D MERSI-II TIR thermal bands. A new approach for estimating land surface emissivity has been developed using the ASTER Global Emissivity Database (ASTER GED) and the International Geosphere-Biosphere Program (IGBP) data. A model to estimate the atmospheric water vapor content (AWVC) from the three atmospheric water vapor absorption bands (bands 16, 17, and 18) has been developed as AWVC has been recognized as the most important factor determining the variation of AT. Using MODTRAN 5.2, the equations for the AT estimate from the retrieved AWVC were established. In addition, the AT of the pixels at the far edge of FY-3D MERSI-II data may be strongly affected by the increase of the optical path. Viewing zenith angle (VZA) correction equations were proposed in the study to correct this effect on AT estimation. Field data from four stations were applied to validate the improved TFSWA in the study. Cross-validation with MODIS LST (MYD11) was also conducted to evaluate the improved TFSWA. The cross-validation result indicates that the FY-3D MERSI-II LST from the improved TFSWA are comparable with MODIS LST while the correlation coefficients between FY-3D MERSI-II LST and MODIS LST over the Mid-East China region are in the range of 0.84~0.98 for different seasons and land cover types. Validation with 318 field LST samples indicates that the average MAE and R2 of the scenes at the four stations are about 1.97 K and 0.98, respectively. Thus, it could be concluded that the improved TFSWA developed in the study can be a good algorithm for LST retrieval from FY-3D MERSI-II data with acceptable accuracy.

Detection of earthflow dynamics using medium-resolution digital terrain models: Diachronic perspective of the Jovac earthflow, Southern Serbia

The paper presents and discusses the landslide research procedure related to the topography before and after its occurrence, using the comparative analysis of two medium-resolution digital terrain models. The case study is the Jovac mega-landslide—the largest landslide to occur in Serbia in the last 100 years, active for three days in February 1977. The indicators used to determine the volume and movement mechanism were the spatial distribution of elevation differences within the two digital terrain models (DTM), and the analysis of geomorphological features before the landslide. The obtained elevation differences allowed the definition of the approximate landslide volume: 11.6 × 106 m3. All the data obtained indicate that the movement mechanism falls into the category of earthflow.

Characterizing the Protolunar Disk of the Accreting Companion GQ Lupi B*

GQ Lup B is a young and accreting, substellar companion that appears to drive a spiral arm in the circumstellar disk of its host star. We report high-contrast imaging observations of GQ Lup B with VLT/NACO at 4–5 μm and medium-resolution integral field spectroscopy with VLT/MUSE. The optical spectrum is consistent with an M9 spectral type, shows characteristics of a low-gravity atmosphere, and exhibits strong Hα emission. The H − M′ color is ≳1 mag redder than field dwarfs with similar spectral types, and a detailed analysis of the spectral energy distribution (SED) from optical to mid-infrared wavelengths reveals excess emission in the L′, NB4.05, and M′ bands. The excess flux is well described by a blackbody component with T disk ≈ 460 K and R disk ≈ 65 R J and is expected to trace continuum emission from small grains in a protolunar disk. We derive an extinction of A V ≈ 2.3 mag from the broadband SED with a suspected origin in the vicinity of the companion. We also combine 15 yr of astrometric measurements and constrain the mutual inclination with the circumstellar disk to 84 ± 9 deg, indicating a tumultuous dynamical evolution or a stellar-like formation pathway. From the measured Hα flux and the estimated companion mass, M p ≈ 30 M J, we derive an accretion rate of M ̇ ≈ 10 − 6.5 M J yr − 1 . We speculate that the disk is in a transitional stage in which the assembly of satellites from a pebble reservoir has opened a central cavity while GQ Lup B is in the final stages of its formation.

Delineating the elusive BaMMV resistance gene rym15 in barley by medium-resolution mapping

Barley mild mosaic virus (BaMMV), transmitted by the soil-borne protist Polymyxa graminis, has a serious impact on winter barley production. Previously, the BaMMV resistance gene rym15 was mapped on chromosome 6HS, but the order of flanking markers was non-collinear between different maps. To resolve the position of the flanking markers and to enable map-based cloning of rym15, two medium-resolution mapping populations Igri (susceptible) × Chikurin Ibaraki 1 (resistant) (I × C) and Chikurin Ibaraki 1 × Uschi (susceptible) (C × U), consisting of 342 and 180 F2 plants, respectively, were developed. Efficiency of the mechanical inoculation of susceptible standards varied from 87.5 to 100% and in F2 populations from 90.56 to 93.23%. Phenotyping of F2 plants and corresponding F3 families revealed segregation ratios of 250 s:92r (I × C, χ2 = 0.659) and 140 s:40r (C × U, χ2 = 0.741), suggesting the presence of a single recessive resistance gene. After screening the parents with the 50 K Infinium chip and anchoring corresponding SNPs to the barley reference genome, 8 KASP assays were developed and used to remap the gene. Newly constructed maps revealed a collinear order of markers, thereby allowing the identification of high throughput flanking markers. This study demonstrates how construction of medium-resolution mapping populations in combination with robust phenotyping can efficiently resolve conflicting marker ordering and reduce the size of the target interval. In the reference genome era and genome-wide genotyping era, medium-resolution mapping will help accelerate candidate gene identification for traits where phenotyping is difficult.

LAMOST Time-Domain survey: first results of four K2 plates

From Oct. 2019 to Apr. 2020, LAMOST performed a time-domain (TD) spectroscopic survey of four K2 plates with both low- and medium-resolution observations. The low-resolution spectroscopic survey acquired 282 exposures ( ≈ 46.6 h) over 25 nights, yielding a total of about 767 000 spectra, and the medium-resolution survey took 177 exposures ( ≈ 49.1 h) over 27 nights, collecting about 478 000 spectra. More than 70%/50% of low-resolution/medium-resolution spectra have signal-to-noise ratio higher than 10. We determine stellar parameters (e.g., T eff, log g, [Fe/H]) and radial velocity (RV) with different methods, including LASP, DD-Payne and SLAM. In general, these parameter estimations from different methods show good agreement, and the stellar parameter values are consistent with those of APOGEE. We use the Gaia DR2 RV values to calculate a median RV zero point (RVZP) for each spectrograph exposure by exposure, and the RVZP-corrected RVs agree well with the APOGEE data. The stellar evolutionary and spectroscopic masses are estimated based on the stellar parameters, multi-band magnitudes, distances and extinction values. Finally, we construct a binary catalog including about 2700 candidates by analyzing their light curves, fitting the RV data, calculating the binarity parameters from medium-resolution spectra and cross-matching the spatially resolved binary catalog from Gaia EDR3. The LAMOST TD survey is expected to represent a breakthrough in various scientific topics, such as binary systems, stellar activity, stellar pulsation, etc.

LAMOST medium-resolution spectral survey of Galactic nebulae (LAMOST-MRS-N): subtraction of geocoronal Hα emission

We introduce a method of subtracting geocoronal Hα emissions from the spectra of LAMOST medium-resolution spectral survey of Galactic nebulae (LAMOST-MRS-N). The flux ratios of the Hα sky line to the adjacent OH λ6554 single line do not show a pattern or gradient distribution in a plate. More interestingly, the ratio is well correlated to solar altitude, which is the angle of the Sun relative to the Earthʼs horizon. It is found that the ratio decreases from 0.8 to 0.2 with the decreasing solar altitude from –17 to –73 degree. Based on this relation, which is described by a linear function, we can construct the Hα sky component and subtract it from the science spectrum. This method has been applied to the LAMOST-MRS-N data, and the contamination level of the Hα sky to nebula is reduced from 40% to less than 10%. The new generated spectra will significantly improve the accuracy of the classifications and the measurements of physical parameters of Galactic nebulae.

A Novel Method for Layover Detection in Mountainous Areas with SAR Images

It is well known that there are geometric distortions in synthetic aperture radar (SAR) images when the terrain undulates. Layover is the most common one, which brings challenges to the application of SAR remote sensing. This study proposes a novel detection method that is mainly aimed at the layover caused by mountains and can be performed with only medium-resolution SAR images and no other auxiliary data. The detection includes the following four stages: initial processing, difference image calculation and rough and fine layover detection. Initial processing mainly obtains the potential layover areas, which are mixed with the built-up areas after classification. Additionally, according to the analysis of the backscatter coefficient (BC) of various ground objects with different polarization images, the layover areas are detected step-by-step from the mixed areas, in which the region-based FCM segmentation algorithm and spatial relationship criteria are used. Taking the Danjiangkou Reservoir area as the study area, the relevant experiments with Sentinel-1A SAR images were conducted. The quantitative analysis of detection results adopted the figure of merit (FoM), and the highest accuracy was up to 87.6% of one selected validation region. Experiments in the South Taihang area also showed the satisfactory effect of layover detection, and the values of FoM were all above 85%. These results show that the proposed method can do well in the layover detection caused by mountains. Its simplicity and effectiveness are helpful in removing the influence of layover on SAR image applications to a certain extent and improving the development of SAR remote sensing technology.

The Early-type Stars from the LAMOST Survey: Atmospheric Parameters

Massive stars play key roles in many astrophysical processes. Deriving the atmospheric parameters of massive stars is important to understanding their physical properties, and thus the atmospheric parameters are key inputs to trace the evolution of massive stars. Here we report our work on adopting the data-driven technique called stellar label machine (SLAM) with the nonlocal thermal equilibrium TLUSTY synthetic spectra as the training data set to estimate the stellar parameters of Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) optical spectra for early-type stars. We apply two consistency tests to verify this machine-learning method and compare stellar labels given by SLAM with the labels in the literature for several objects having high-resolution spectra. We provide the stellar labels of effective temperature (T eff), surface gravity ( log g ), metallicity ([M/H]), and projected rotational velocity ( v sin i ) for 3931 and 578 early-type stars from the LAMOST low-resolution survey (LRS) and medium-resolution survey (MRS), respectively. To estimate the average statistical uncertainties of our results, we calculated the standard deviation between the predicted stellar label and the prelabeled published values from the high-resolution spectra. The uncertainties of the four parameters are σ(T eff) = 2185 K, σ ( log g ) = 0.29 dex, and σ ( v sin i ) = 11 km s − 1 for MRS, and σ(T eff) = 1642 K, σ ( log g ) = 0.25 dex, and σ ( v sin i ) = 42 km s − 1 for LRS spectra, respectively. We note that the parameters of T eff, log g , and [M/H] can be better constrained using LRS spectra than using MRS spectra, most likely due to their broad wavelength coverage, while v sin i is constrained better by MRS spectra than by LRS spectra, probably due to the relatively accurate line profiles of MRS spectra.