Improved Priority‐Flood method for depression filling by redundant calculation optimization in local micro‐relief areas

Depression filling is a critical step in distributed hydrological modeling using digital elevation models (DEMs). The traditional Priority‐Flood (PF) approach is widely used due to its relatively high efficiency when dealing with a small‐sized DEM. However, it seems inadequate and inefficient when dealing with large high‐resolution DEMs. In this work, we examined the relationship between the PF algorithm calculation process and the topographical characteristics of depressions, and found significant redundant calculations in the local micro‐relief areas in the conventional PF algorithm. As such calculations require more time when dealing with large DEMs, we thus propose a new variant of the PF algorithm, wherein redundant points and calculations are recognized and eliminated based on the local micro‐relief water‐flow characteristics of the depression‐filling process. In addition, depressions and flatlands were optimally processed by a quick queue to improve the efficiency of the process. The proposed method was applied and validated in eight case areas using the Shuttle Radar Topography Mission digital elevation model (SRTM‐DEM) with 1 arc‐second resolution. These selected areas have different data sizes. A comparative analysis among the proposed method, the Wang and Liu‐based PF, the improved Barnes‐based PF, the improved Zhou‐based PF, and the Planchon and Darboux (P&D) algorithms was conducted to evaluate the accuracy and efficiency of the proposed algorithm. The results showed that the proposed algorithm is 43.2% (maximum) faster than Wang and Liu's variant of the PF method, with an average of 31.8%. In addition, the proposed algorithm achieved similar performance to the improved Zhou‐based PF algorithm, though our algorithm has the advantage of being simpler. The optimal strategies using the proposed algorithm can be employed in various landforms with high efficiency. The proposed method can also achieve good depression filling, even with large amounts of DEM data.     

Simulation of landscape spatial layout evolution in rural-urban fringe areas: a case study of Ganjingzi District

In recent years, the rapid expansion of urban spaces has accelerated the mutual evolution of landscape types. Analyzing and simulating spatio-temporal dynamic features of urban landscape can help to reveal its driving mechanisms and facilitate reasonable planning of urban land resources. The purpose of this study was to design a hybrid cellular automata model to simulate dynamic change in urban landscapes. The model consists of four parts: a geospatial partition, a Markov chain (MC), a multi-layer perceptron artificial neural network (MLP-ANN), and cellular automata (CA). This study employed multivariate land use data for the period 2000–2015 to conduct spatial clustering for the Ganjingzi District and to simulate landscape status evolution via a divisional composite cellular automaton model. During the period of 2000–2015, construction land and forest land areas in Ganjingzi District increased by 19.43% and 15.19%, respectively, whereas farmland, garden lands, and other land areas decreased by 43.42%, 52.14%, and 75.97%, respectively. Land use conversion potentials in different sub-regions show different characteristics in space. The overall land-change prediction accuracy for the subarea-composite model is 3% higher than that of the non-partitioned model, and misses are reduced by 3.1%. Therefore, by integrating geospatial zoning and the MLP-ANN hybrid method, the land type conversion rules of different zonings can be obtained, allowing for more effective simulations of future urban land use change. The hybrid cellular automata model developed here will provide a reference for urban planning and policy formulation.     

Semantic segmentation of high spatial resolution images with deep neural networks

Availability of reliable delineation of urban lands is fundamental to applications such as infrastructure management and urban planning. An accurate semantic segmentation approach can assign each pixel of remotely sensed imagery a reliable ground object class. In this paper, we propose an end-to-end deep learning architecture to perform the pixel-level understanding of high spatial resolution remote sensing images. Both local and global contextual information are considered. The local contexts are learned by the deep residual net, and the multi-scale global contexts are extracted by a pyramid pooling module. These contextual features are concatenated to predict labels for each pixel. In addition, multiple additional losses are proposed to enhance our deep learning network to optimize multi-level features from different resolution images simultaneously. Two public datasets, including Vaihingen and Potsdam datasets, are used to assess the performance of the proposed deep neural network. Comparison with the results from the published state-of-the-art algorithms demonstrates the effectiveness of our approach.     

Sentinel-1A SAR影像及其在矿区地面沉降监测中的应用研究

详细介绍了Sentinel-1A SAR影像数据的基本参数、工作模式、应用领域等。利用2016.11.09—2017.03.09的5景Sentinel-1A C波段SAR影像数据进行矿区地面沉降监测试验。基于SARscape利用双轨D-In SAR技术进行差分干涉处理,得到了研究区地面沉降分布图,直观地再现了研究区在2016.11.09—2017.03.09的沉降分布、沉降量级等。结果表明济宁某矿区在监测期间地面相对稳定,未有大面积和大量级的地面沉降发生,4个干涉对监测到的最大沉降都未超过3 cm。     

基于Landsat遥感数据武汉地区植被覆盖度动态变化监测分析

旨在研究受人类经济活动影响的植被资源及其动态变化趋势的程度,采用基于归一化植被指数的像素二分模型,利用2002—2010年(武汉市每年8月)的卫星遥感数据,对武汉地区6年间的植被覆盖变化进行监测分析。结果表明,植被覆盖度变化与武汉GDP增长率有着紧密联系:2002—2007年,武汉经济较缓慢上升,植被覆盖度基本维持在55%左右;而2007—2008年武汉GDP总值增长率高达26.06%,但随之而来的是植被覆盖度由高峰期的61.68%下降到49.18%,是历年来的最低水准; 2008—2010年经济发展放缓,植被指数有小幅度回升。人类经济活动是影响植被资源的重要因素。     

IU Cancri:a solar-type contact binary with mass transfer

We present new CCD photometry of the solar-type contact binary IU Cnc, which was observed from November 2017 to March 2018 with three small telescopes in China. BV light curves imply that IU Cnc is a W-type contact binary with total eclipses. The photometric solution indicates that the mass ratio and fill-out factor are q = 4.104 ± 0.004 and f = 30.2%± 0.3%, respectively. From all available light minimum times, the orbital period may increase at a rate of dP/dt =+6.93(4)× 10^-7 d yr^-1, which may result from mass transfer from the secondary component to the primary one. With mass transferring,IU Cnc may evolve from a contact configuration into a semi-detached configuration.     

基于容器技术的天文应用软件自动部署方法

平方千米阵列即将开始建设,各子工作包也进入关键设计评估阶段。基于云与容器技术是平方千米阵列科学数据处理器未来可能采用的平台技术。针对超大规模海量数据处理面临的天文应用软件快速部署、运行与实测要求,充分考虑天文应用软件运行环境复杂、云计算环境下超大规模计算集群部署困难等问题,系统研究并给出了一种使用容器技术的天文应用软件通用自动部署方法。以目前较为常用的可见度函数校准软件SAGECaL为例,首先分析了SAGECaL的相关特性和分布式部署方面存在的困难,进而给出了基于容器技术的SAGECaL分布式集群的自动部署方法。实验结果表明,自动部署方法极大地提高了SAGECaL分布式集群的部署效率,满足项目组承担平方千米阵列科学数据处理器相关测试工作所需要的基础平台部署与切换等需求,同时也为其它天文软件在云端的快速部署与执行提供了有益的思路。     

The relationship between the radio core-dominance parameter and spectral index in different classes of extragalactic radio sources(Ⅱ)

Active galactic nuclei(AGNs) can be divided into two major classes, namely radio-loud and radio-quiet AGNs. A small subset of the radio-loud AGNs is called blazars, which are believed to be unified with Fanaroff-Riley type Ⅰ/Ⅱ(FRI/Ⅱ) radio galaxies. Following our previous work(Fan et al.), we present a sample of 2400 sources with measured radio flux densities of the core and extended components. The sample contains 250 BL Lacs, 520 quasars, 175 Seyferts, 1178 galaxies, 153 FRI or FRⅡ galaxies and 104 unidentified sources. We then calculate the radio core-dominance parameters and spectral indices, and study their relationship. Our analysis shows that the core-dominance parameters and spectral indices are quite different for different types of sources. We also confirm that the correlation between core-dominance parameter and spectral index exists for a large sample presented in this work.     

The galaxy luminosity function in the LAMOST Complete Spectroscopic Survey of Pointing Area at the Southern Galactic Cap

We present optical luminosity functions(LFs) of galaxies in the~(0.1) g,~(0.1) r,~(0.1) i bands, calculated using data in~40 deg~2 sky area of the LAMOST Complete Spectroscopic Survey of Pointing Area(LaCoSSPAr) in the Southern Galactic Cap. Redshifts for galaxies brighter than r = 18.1 were obtained mainly with LAMOST. In each band, LFs derived using both parametric and non-parametric maximum likelihood methods agree well with each other. In the0.1 r band, our fitting parameters of the Schechter function are φ_*=(1.65 ± 0.36) × 10~(-2) h~3 Mpc~(-3), M_*=-20.69 ± 0.06 mag and α =-1.12 ± 0.08,which agree with previous studies. Separate LFs are also derived for emission line galaxies and absorption line galaxies. The LFs of absorption line galaxies show a dip at~(0.1) r ~18.5 and can be fitted well by a double-Gaussian function, suggesting a bimodality in passive galaxies.     

Unusual infrared emission toward Sgr B2: possible planar C_(24)

Interstellar graphene could be present in the interstellar medium(ISM), resulting from the photochemical processing of polycyclic aromatic hydrocarbon(PAH) molecules and/or collisional fragmentation of graphitic particles. Indeed, by comparing the observed ultraviolet(UV) extinction and infrared(IR) emission of the diffuse ISM with that predicted for graphene, as much as ～ 2% of total interstellar carbon could be locked up in graphene without violating the observational constraints. While the possible detection of planar C24, a small piece of a graphene sheet, has been reported towards several Galactic and extragalactic planetary nebulae, graphene has not yet been detected in interstellar environments. In this work, we search for the characteristic IR features of C24 at ～ 6.6, 9.8 and 20 μm toward Sgr B2, a high-mass star formation region, and find a candidate target toward R.A.(J2000) = 267.05855?and Decl.(J2000) =-28.01479?in Sgr B2 whose Spitzer/IRS spectra exhibit three bands peaking at ～ 6.637, 9.853 and 20.050 μm which appear to be coincident with those of C24. Possible features of C60 are also seen in this region. The candidate region is a warm dust environment heated by massive stars or star clusters, associated with a WISE spot(a tracer of star formation activity), close to the HII region candidate IRAS 17450–2759, and is surrounded by seven young stellar object candidates within ～ 5′, suggesting that the creation and/or excitation of C24 could be related to star formation activities.