THE STUDY OF SURFACE DUST CONCENTRATION OF SATELLITE IN FAIRING SEPARATION

The explosion process is usually used for satellite releasing during fairing separation. Explosion products are not allowed to be leaked from the detonating tube connecting two parts of the fairing during the fairing separation process. This paper predicts the contamination of the explosion products falling on the satellite surface during fairing separation on the ground and in space in case of the computer simulation by using the theory of explosion gaseous dynamics and the basic theory of aerosol mechanics.

SATELLITE REMOTE SENSING OF SEA-ICE AND SEA SURFACE TEMPERATURE

Sea-ice and Sea Surface Temperature in offshore seas are important terms for operational monitoring and forecasting marine environment in China. The software system of regional marine environmental application designed by author is used for realtime operational monitoring sea-ice, SST, oceanic current and colours and characters of land surface. This software system processes quantitative AVHRR data from NOAA satellite to calculate calibration coefficient, solar angle correction, earth location parameter and atmospheric attenuation correction, then SST field will be produced through calculation using special SST model, and top-quality of colour composite imagery of satellite with variable spacial resolution (1, 2 or 5km) will be produced via image processing. Inside front covor Figure 1 is colour enhanced imagery with 5km resolution of NOAA satellite in offshore

Land Surface Albedo Variations in Sanjiang Plain from 1982 to 2015: Assessing with GLASS Data

As a key parameter for indicating the fraction of surface-reflected solar incident radiation, land surface albedo plays an important role in the Earth’s surface energy budget(SEB). Since the Sanjiang Plain has been severely affected by human activities(e.g., reclamation and shrinking of wetlands), it is important to assess the spatiotemporal variations of surface albedo in this region using a long-term remote sensing dataset. In order to investigate the surface albedo climatology, trends, and mechanisms of change, we evaluated the surface albedo variations in the Sanjiang Plain, China from 1982 to 2015 using the Global LAnd Surface Satellite(GLASS) broadband surface albedo product. The results showed that: 1) an increasing annual trend(+0.000 58/yr) of surface albedo was discovered in the Sanjiang Plain based on the GLASS albedo dataset, with a much stronger increasing trend(+0.001 26/yr) occurring during the winter. Most of the increasing trends occurred over the cultivated land, unused land, and land use conversion types located in the northeastern Sanjiang Plain. 2) The increasing trend of land surface albedo in Sanjiang Plain can be largely explained by the changes of both snow cover extent and land use. The surface albedo in winter is highly correlated with the snow cover extent in the Sanjiang Plain, and the increasing trend of surface albedo can be further enhanced by the land use changes.

Multi-scale Analysis of the Relationships between Solar Activity, CO_(2) and Global Surface Temperature

To reveal whether the dynamics of solar activity precede those of global temperature, especially in terms of global warming, the relationship between total solar irradiance(TSI), which is treated as a proxy of solar activity, and global surface temperature(GST) is investigated in the frequency domain using wavelet coherence. The results suggest that the effect of TSI on GST is mainly reflected on the characteristic scale around 22 yr, and variations in TSI lead to changes in GST with some delay effect as shown by the phase difference arrows. However, this implicated relationship has been perturbed by excessive CO_(2) emissions since 1960. Through the combination of co-integration analysis and wavelet coherence, the hidden relationship between TSI and GST has been uncovered without the CO_(2) effect and the results further indicate that TSI has a positive effect on GST at the characteristic scale around 22 yr with a 3 yr lead.

Strong Spatial Aggregation of Martian Surface Temperature Shaped by Spatial and Seasonal Variations in Meteorological and Environmental Factors

Spatio-temporal variation in the Martian surface temperature(MST)is an indicator of ground level thermal processes and hence a building block for climate models.However,the distribution of MST exhibits different levels of spatial aggregation or heterogeneity,and varies in space and time.Furthermore,the effect of regional differences in meteorological or environmental factors on the MST is not well understood.Thus,we investigated the degree of spatial autocorrelation of MST across the surface of Mars globally by Moran’s I,and identified the hot spots by GetisOrd G;*.We also estimated the regional differences in the influence of seasonally dominant factors including thermal inertia(TI),albedo,surface pressure,latitude,dust and slope on MST by a geographically weighted regression model.The results indicate(1)that MST is spatially aggregated and hot and cold spots varied over time and space.(2)Hemispheric differences in topography,surface TI and albedo were primarily responsible for the hemispheric asymmetry of hot spots.(3)The dominant factors varied by geographical locations and seasons.For example,the seasonal Hadley circulation dominates at the low-latitudes and CO;circulation at the high-latitudes.(4)Regions with extreme variations in topography and low TI were sensitive to meteorological and environmental factors such as dust and CO_(2)ice.We conclude that the spatial autocorrelation of MST and the spatial and seasonal heterogeneity of influencing factors must be considered when simulating Martian climate models.This work provides a reference for further exploration of Martian climatic processes.

Structure and seasonal variability of fronts in the Southeast Indian Ocean along sections from Fremantle, Australia to Antarctic Zhongshan Station

Four sections of expendable conductivity-temperature-depth （XCTD） profiles from Fremantle, Australia to Antarctic Zhongshan Station and Moderate Resolution Imaging Spectroradiometer-Aquarius （MODIS-A） sea surface temperature （SST） products were used to study the structure and seasonal variability of Southeast Indian Ocean fronts. Water mass analysis showed that surface water masses in the Southeast Indian Ocean were less salty in March than in November. Compared with November, the subtropical front （STF） moved southward about one degree of latitude in March, whereas seasonal variability of the subantarctic front （SAF） and polar front （PF） locations was not obvious. In March, the saline front moved northward about two degrees of latitude relative to the thermal front in the upper 100 m at the SAF, which was the northern boundary of sub- Antarctic surface water （SASW）. Analysis of climatological SST gradients from the satellite data showed that regions of enhanced sea surface temperature （SST） gradients were collocated with frontal locations identified with the XCTD data using water mass criteria. The surface expression of the PF identified by the SST gradient was further south by about one degree of latitude relative to the subsurface expression of the PF identified by the northern boundary of cold water.

Lunar cratering asymmetries with high lunar orbital obliquity and inclination of the Moon

Accurate estimation of cratering asymmetry on the Moon is crucial for understanding Moon evolution history.Early studies of cratering asymmetry have omitted the contributions of high lunar obliquity and inclination.Here,we include lunar obliquity and inclination as new controlling variables to derive the cratering rate spatial variation as a function of longitude and latitude.With examining the influence of lunar obliquity and inclination on the asteroids population encountered by the Moon,we then have derived general formulas of the cratering rate spatial variation based on the crater scaling law.Our formulas with addition of lunar obliquity and inclination can reproduce the lunar cratering rate asymmetry at the current Earth-Moon distance and predict the apex/ant-apex ratio and the pole/equator ratio of this lunar cratering rate to be 1.36 and 0.87,respectively.The apex/ant-apex ratio is decreasing as the obliquity and inclination increasing.Combining with the evolution of lunar obliquity and inclination,our model shows that the apex/ant-apex ratio does not monotonically decrease with Earth-Moon distance and hence the influences of obliquity and inclination are not negligible on evolution of apex/ant-apex ratio.This model is generalizable to other planets and moons,especially for different spin-orbit resonances.

Resource potential and planning for exploration of the Hebrus Valles, Mars

Mars is the only extraterrestrial body which could host primitive lifeforms and also has the potential to host a human base in the near future. Towards fulfilling these objectives, several remote sensing missions and rover based missions have been sent to Mars. Still, confirmation of existing or extinct life on this planet in any form has not been achieved and possibly human missions at selected sites in the future are the key to addressing this problem. Here, we have used remote sensing data from Mars Reconnaissance Orbiter(MRO;NASA), Mars Global Surveyor(MGS;NASA), Mars Odyssey(NASA) and Mars Express(MEX;ESA) to devise an exploration strategy for one such area known as Hebrus Valles, which is a potential site for human exploration of the surface of Mars. A geological context map of the Hebrus Valles and Hephaestus Fossae region has been prepared and a candidate landing site has been proposed in the Hebrus Valles region. Suitable rover paths have been worked out from the proposed landing site for harnessing the science and resource potential of the region. The proposed landing site is located in the equatorial region at(20?40′N, 126?23′E) and due to its proximity to the Potential Subsurface Access Candidates(PSACs) in the region, such as sinkholes and skylights and also other resources such as crater ejecta, silicate material and fluvial channels, the site is appropriate for exploration of the region.

Mapping of Compositional Diversity and Chronological Ages of Lunar Farside Multiring Mare Moscoviense Basin:Implications to the Middle Imbrian Mare Basalts

The Mare Moscoviense is an astonishing rare flatland multi-ring basin and one of the recognizable mare regions on the Moon's farside.The mineralogical,chronological,topographical and morphological studies of the maria surface of the Moon provide a primary understanding of the origin and evolution of the mare provinces.In this study,the Chandrayaan-1 M^(3)data have been employed to prepare optical maturity index,FeO and TiO^(2)concentration,and standard band ratio map to detect the mafic indexes like olivine and pyroxene minerals.The crater size frequency distribution method has been applied to LROC WAC data to obtain the absolute model ages of the Moscoviense basin.The four geological unit ages were observed as 3.57 Ga(U-2),3.65 Ga(U-1),3.8 Ga(U-3)and 3.92 Ga(U-4),which could have been formed between the Imbrian and Nectarian epochs.The M^(3)imaging and reflectance spectral parameters were used to reveal the minerals like pyroxene,olivine,ilmenite,plagioclase,orthopyroxene-olivine-spinel lithology,and olivine-pyroxene mixtures present in the gabbroic basalt,anorthositic and massive ilmenite rocks,and validated with the existing database.The results show that the Moscoviense basin is dominated by intermediate TiO^(2)basalts that derived from olivine-ilmenite-pyroxene cumulate depths ranging from 200 to 500 km between 3.5 Ga and 3.6 Ga.

Physical properties of lunar craters

The surface of the Moon is highly cratered due to impacts of meteorites, asteroids, comets and other celestial objects. The origin, size, structure, age and composition vary among craters. We study a total of 339 craters observed by the Lunar Reconnaissance Orbiter Camera （LROC）. Out of these 339 craters, 214 craters are known （named craters included in the IAU Gazetteer of Planetary Nomenclature） and 125 craters are unknown （craters that are not named and objects that are absent in the IAU Gazetteer）. We employ images taken by LROC at the North and South Poles and near side of the Moon. We report for the first time the study of unknown craters, while we also review the study of known craters conducted earlier by previous researchers. Our study is focused on measurements of diameter, depth, latitude and longitude of each crater for both known and unknown craters. The diameter measurements are based on considering the Moon to be a spherical body. The LROC website also provides a plot which enables us to measure the depth and diameter. We found that out of 214 known craters, 161 craters follow a linear relationship between depth （d） and diameter （D）, but 53 craters do not follow this linear relationship. We study physical dimensions of these 53 craters and found that either the depth does not change significantly with diameter or the depths are extremely high relative to diameter （conical）. Similarly, out of 125 unknown craters, 78 craters follow the linear relationship between depth （d） and diameter （D） but 47 craters do not follow the linear relationship. We propose that the craters following the scaling law of depth and diameter, also popularly known as the linear relationship between d and D, are formed by the impact of meteorites having heavy metals with larger dimension, while those with larger diameter but less depth are formed by meteorites/celestial objects having low density material but larger diameter. The craters with very high depth and with very small diameter are perhaps formed by the impact of meteorites that have very high density but small diameter with a conical shape. Based on analysis of the data selected for the current investigation, we further found that out of 339 craters, 100 （29.5%） craters exist near the equator, 131 （38.6%） are in the northern hemisphere and 108 （31.80%） are in the southern hemisphere. This suggests the Moon is heavily cratered at higher latitudes and near the equatorial zone.

Unsupervised Martian Dust Storm Removal via Disentangled Representation Learning

Mars exploration has become a hot spot in recent years and is still advancing rapidly. However, Mars has massive dust storms that may cover many areas of the planet and last for weeks or even months. The local/global dust storms are so influential that they can significantly reduce visibility, and thereby the images captured by the cameras on the Mars rover are degraded severely. This work presents an unsupervised Martian dust storm removal network via disentangled representation learning(DRL). The core idea of the DRL framework is to use the content encoder and dust storm encoder to disentangle the degraded images into content features(on domain-invariant space) and dust storm features(on domain-specific space). The dust storm features carry the full dust storm-relevant prior knowledge from the dust storm images. The “cleaned” content features can be effectively decoded to generate more natural, faithful, clear images.The primary advantages of this framework are twofold. First, it is among the first to perform unsupervised training in Martian dust storm removal with a single image, avoiding the synthetic data requirements. Second, the model can implicitly learn the dust storm-relevant prior knowledge from the real-world dust storm data sets, avoiding the design of the complicated handcrafted priors. Extensive experiments demonstrate the DRL framework’s effectiveness and show the promising performance of our network for Martian dust storm removal.

Determining proportions of lunar crater populations by fitting crater size distribution

We determine the proportions of two mixed crater populations distinguishable by size distributions on the Moon. A ＂multiple power-law＂ model is built to formulate crater size distribution N（D） ∝ D-αwhose slope α varies with crater diameter D. This model is then used to fit size distributions of lunar highland craters and Class 1 craters. The former is characterized by α = 1.17 ± 0.04, 1.88 ± 0.07,3.17 ± 0.10 and 1.40 ± 0.15 for D ranges ~ 10- 49, 49- 120, 120- 251 and ~ 251- 2500 km, while the latter has a single slope α = 1.96 ± 0.14 for about 10- 100 km. They are considered as Population 1 and2 crater size distributions, whose sum is then fitted to the global size distribution of lunar craters with D between 10 and 100 km. Estimated crater densities of Population 1 and 2 are 44 × 10-5and 5 × 10-5km-2respectively, leading to the proportion of the latter being 10%. This result underlines the need for more thoroughly investigating Population 1 craters and their related impactors, the primordial main-belt asteroids, which dominated the late heavy bombardment.

Assessing the potential for satellite image monitoring of seagrass thermal dynamics:for inter-and shallow sub-tidal seagrasses in the inshore Great Barrier Reef World Heritage Area,Australia

Seagrass meadows are at increasing risk of thermal stress and recent work has shown that water temperature around seagrass meadows could be used as an indicator for seagrass condition.Satellite thermal data have not been linked to the thermal properties of seagrass meadows.This work assessed the covariation between 20 in situ average daily temperature logger measurement sites in tropical seagrass meadows and satellite derived daytime SST(sea surface temperature)from the daytime MODIS and Landsat sensors along the Great Barrier Reef coast in Australia.Statistically significant(R2=0.787–0.939)positive covariations were found between in situ seagrass logger temperatures and MODIS SST temperature and Landsat sensor temperatures at all sites along the reef.The MODIS SST were consistently higher than in situ temperature at the majority of the sites,possibly due to the sensor’s larger pixel size and location offset from field sites.Landsat thermal data were lower than field-measured SST,due to differences in measurement scales and times.When refined significantly and tested over larger areas,this approach could be used to monitor seagrass health over large(106 km2)areas in a similar manner to using satellite SST for predicting thermal stress for corals.

Estimating global land surface broadband thermal-infrared emissivityusing advanced very high resolution radiometer optical data

An algorithm for retrieving global eight-day 5 km broadband emissivity (BBE)from advanced very high resolution radiometer (AVHRR) visible and nearinfrared data from 1981 through 1999 was presented. Land surface was dividedinto three types according to its normalized difference vegetation index (NDVI)values: bare soil, vegetated area, and transition zone. For each type, BBE at813.5 mm was formulated as a nonlinear function of AVHRR reflectance forChannels 1 and 2. Given difficulties in validating coarse emissivity products withground measurements, the algorithm was cross-validated by comparing retrievedBBE with BBE derived through different methods. Retrieved BBE was initiallycompared with BBE derived from moderate-resolution imaging spectroradiometer (MODIS) albedos. Respective absolute bias and root-mean-square errorwere less than 0.003 and 0.014 for bare soil, less than 0.002 and 0.011 fortransition zones, and 0.002 and 0.005 for vegetated areas. Retrieved BBE wasalso compared with BBE obtained through the NDVI threshold method. Theproposed algorithm was better than the NDVI threshold method, particularly forbare soil. Finally, retrieved BBE and BBE derived from MODIS data wereconsistent, as were the two BBE values.

Fractional vegetation cover estimation in heterogeneous areas by combining a radiative transfer model and a dynamic vegetation model

A fractional vegetation cover(FVC)estimation method incorporating a vegetation growth model and a radiative transfer model was previously developed,which was suitable for FVC estimation in homogeneous areas because the finer-resolution pixels corresponding to one coarseresolution FVC pixel were all assumed to have the same vegetation growth model.However,this assumption does not hold over heterogeneous areas,meaning that the method cannot be applied to large regions.Therefore,this study proposes a finer spatial resolution FVC estimation method applicable to heterogeneous areas using Landsat 8 Operational Land Imager reflectance data and Global LAnd Surface Satellite(GLASS)FVC product.The FVC product was first decomposed according to the normalized difference vegetation index from the Landsat 8 OLI data.Then,independent dynamic vegetation models were built for each finer-resolution pixel.Finally,the dynamic vegetation model and a radiative transfer model were combined to estimate FVC at the Landsat 8 scale.Validation results indicated that the proposed method(R^(2)=0.7757,RMSE=0.0881)performed better than either the previous method(R^(2)=0.7038,RMSE=0.1125)or a commonly used method involving look-up table inversions of the PROSAIL model(R^(2)=0.7457,RMSE=0.1249).