Photometric, spectroscopic and polarimetric variability of the weak-emission T Tauri star HD 288313

Photometric observations over three seasons show HD 288313 to be a light variable with a 2.2636-d period. The observed V amplitudes lie in the range of 0.06–0.15 mag. The star showed appreciable changes in the brightness at maximum and minimum of the light curve from season to season. The (   b − y   ) colour did not show any significant variation during the photometric cycle. The light variation appears to be caused by the rotational modulation of stellar flux by cool starspots distributed asymmetrically across the stellar longitudes. The Hα line strength in HD 288313 varied drastically from completely filled-in emission to almost full absorption, that is typical of a normal star of similar spectral type. The Hα equivalent width is found to show a clear rotational modulation only occasionally. Most of the time, chromospheric active regions are distributed well across the stellar longitudes, thereby suppressing obvious rotational modulations. Broad-band linear polarization measurements show HD 288313 to be a short period, low-amplitude polarization variable. The polarization variation is, apparently, rotationally modulated. Dust grain scattering in a non-spherical circumstellar envelope of a star with inhomogeneities in the surface brightness distribution seems to be the mechanism operating in producing the observed polarization.     

航海雷达测波系统中海杂波数据的校正

为了对航海雷达图像进行海杂波数据的精确校正,结合实测海浪数据,提出了一种海杂波数据校正方法.首先,针对雷达成像过程中的几何畸变,结合数据采集系统的实际工作参数,通过方位向和距离向数据的快速分离进行几何校正;然后,针对海杂波数据沿扫描线方向存在的辐射量畸变,根据实际海浪分析的信号要求,利用沿扫描线上的非线性原理进行相对辐射校正.结果表明,无论是数据处理速度还是校正后的影像质量,均达到了海浪分析工程的实用要求.     

利用地物杂波进行天气雷达强度标定

地物杂波的回波强度相对稳定 ,对成都和新疆地区的地物杂波强度的统计表明 ,地物杂波的雷达反射因子方差分别小于 3db和 1.5db ,因此 ,地物回波可作为一个标准目标 ,用来对天气雷达进行强度的标定。本文给出了这种强度标定的流程图、标定方法和标定结果。使用这种标定方法将大大改善天气雷达的维护和使用质量。     

Multidimensional GPR array processing using Kirchhoff migration

We compare the ability of several practical ground-penetrating radar (GPR) array processing methods to improve signal-to-noise ratio (SNR), increase depth of signal penetration, and suppress out-of-plane arrivals for data with SNR of roughly 1. The methods include two-dimensional (2-D) monostatic, three-dimensional (3-D) monostatic, and 3-D bistatic Kirchhoff migration. The migration algorithm is modified to include the radiation pattern for interfacial dipoles. Results are discussed for synthetic and field data. The synthetic data model includes spatially coherent noise sources that yield nonstationary signal statistics like those observed in high noise GPR settings. Array results from the model data clearly indicate that resolution and noise suppression performance increases as array dimensionality increases. Using 50-MHz array data collected on a temperate glacier (Gulkana Glacier, AK), we compare 2-D and 3-D monostatic migration results. The data have low SNR and contain reflections from a complex, steeply dipping bed. We demonstrate that the glacier bed can only be accurately localized with the 3-D array. In addition, we show that the 3-D array increases SNR (relative to a 2-D array) by a factor of three.     

Combining multisource satellite data to estimate storage variation of a lake in the Rift Valley Basin,Ethiopia

Integration of remote sensing data sets from multiple satellites is tested to simulate water storage variation of Lake Ziway, Ethiopia for the period 2009-2018. Sixty Landsat ETM+/OLI images served to trace temporal variation of lake surface area using a water extraction index. Time series of lake levels were acquired from two altimetry databases that were validated by in-situ lake level measurements. Coinciding pairs of optical satellite based lake surface area and radar altimetry based lake levels were related through regression and served for simulating lake storage variation. Indices for extracting lake surface area from images showed 91–99 % overall accuracy. Lake water levels from the altimetry products well agreed to in-situ lake level measurements with R² = 0.92 and root mean square error of 11.9 cm. Based on this study we conclude that integrating satellite imagery and radar altimetry is a viable approach for frequent and accurate monitoring of lake water volume variation and for long-term change detection. Findings indicate water level reduction (4 cm/annum), surface area shrinkage (0.08km²/annum) and water storage loss (20.4Mm³/annum) of Lake Ziway (2009–2018).     

Fine scale mapping of fractional tree canopy cover to support river basin management

Management of water, regionally, nationally and globally will continue to be a priority and complex undertaking. In riverine systems, biotic components like flora and fauna play critical roles in filtering water so it is available for human use and consumption. Preservation of ecosystems and associated ecosystem functions is therefore vital. In highly regulated large river basins, natural ecosystems are often supported through provision of environmental flows. Flow delivery, however, should be underpinned by rigorous monitoring to identify and prioritise biotic water requirements. Currently, large-scale monitoring solutions are scaled from remote sensing data via measurement of field evapotranspiration for woody tree vegetation species. However, as there is generally a mismatch between field data collection area and remote sensing pixel size, new methods are required to proportion tree evapotranspiration based on tree fractional canopy area per pixel. We present a novel method to derive tree fractional canopy cover (FTCC) at 20 m resolution in semi-arid and arid floodplain areas. The method employs LiDAR as a canopy area field measurement proxy (10 m resolution). We used Sentinel-1 and Sentinel-2 (radar and multispectral imagery) in a Random Forest analysis, undertaken to develop a predictive FTCC model trained using LiDAR for two regions in the Murray–Darling Basin. A predictor model combining the results of both regions was able to explain between 71%–85% of FTCC variation when compared to LiDAR FTCC when output in 10% increments. Development of this method underpins the advancement of woody vegetation monitoring to inform environmental flow management in the Murray–Darling Basin. The method and fine scale outputs will also be of value to other catchment management concerns such as altered catchment water yields related to bushfires and as such has application to water management worldwide.     

基于Sentinel-1A的全球有效波高的反演研究

本文利用神经网络的技术手段,针对Sentinel-1A二级波模式数据提出一种用于海浪有效波高(Hs)反演的模型——N_N模型。该模型在基于ERS2 SAR波模数据开发的双参数模型的基础上,加入经度、纬度、方位向截断波长(λ_c)、图像偏斜(skewness,skew)、图像峰度(kurtosis,kurt)、卫星平台距目标物的距离与卫星飞行速度之比(β)等其他参数信息,根据不同输入参数的组合,建立了14个模型用于Hs反演,旨在分析各参数对有效波高反演的影响。通过分析表明,14个N_N模型相关系数都在0.8以上。随着λ_c、β参数的加入,N_N模型性能均大幅上升,且λ_c参数对模型性能的改善作用更加明显,相关系数提升0.06左右,均方根误差(Root Mean Squared Error,RMSE)下降0.12m左右。另外,skew与kurt的加入也使N_N模型性能有所改善,RMSE下降0.03m左右,相关系数提升0.01左右。其中,N_N10模型效果最佳且性能最稳定,与欧洲中程天气预测中心(the European Centre for Medium-Range Weather Forecasts,ECMWF)数据对比,相关系数(CORR)达到0.905,散射指数(Scattering Index,SI)与RMSE最低,分别为18.74%、0.502m,与独立测量的浮标数据的相关系数达到了0.894。