基于无人机多源遥感数据海岛植被叶面积指数协同反演研究

无人机多源遥感数据的获取、融合以及应用是当今研究的热点和难点。文中以城洲岛为例,针对海岛特殊的地理生态环境,获取无人机多源遥感数据。结合无人机多光谱遥感数据定量分析各遥感植被指数与植被叶面积指数(Leaf Area Index, LAI)的响应关系,构建单因子遥感反演模型;基于无人机激光LiDAR点云提取海岛植被冠层高度模型(Canopy Height Model,CHM),并将其作为自变量引入到多源统计回归分析中,从而构建多源遥感数据协同反演模型,对区域尺度下海岛叶面积指数(LAI)进行估算,开展验证和精度评价。结果显示,加入植被冠层高度因子的协同反演模型的判定系数R2为0.92,绝对平均误差系数为12.29%,预测精度要优于单因子反演模型(判定次数R2为0.86,绝对平均误差系数19.95%)。研究表明,加入了植被冠层高度因子的协同反演模型能在一定程度上提高乔木植被LAI的预测精度。实践证明,无人机多源遥感技术在生态学定量研究中具有巨大的潜力和广阔的应用前景。     

基于GNSS方位辅助惯性导航系统的水下地形精密测量技术

多波束测深技术是目前水下地形测量的主要技术手段,测量平台的瞬时姿态及方位是影响多波束测深系统最终成果准确度的重要因素。GNSS方位辅助惯性导航系统,作为目前应用较为广泛的方位、姿态、及位置综合测量系统,不仅能够提供高精度位置信息,同时也能提供测量平台的瞬时姿态及方位数据,而且因为具有GNSS方位辅助测量,使得最终方位测量结果比传统方位测量精度大大提高,这对于多波束最终测量成果精度提高具有重要意义。文中从GNSS方位辅助惯性导航系统原理及技术优势出发,结合Trimble RTX后处理技术,从姿态测量、方位测量及辅助高程测量方面分析了在多波束水下地形测量中的应用,并以实际测量成果来展现其在水下地形精密测量技术方面的优势,结果显示,定位精度可以达到优于2 cm级别,方位精度可以优于0.01°(依赖于双GNSS天线之间的基线长度),该技术对水下地形测量准确度提升作用显著。     

我国经营性海洋牧场产业链延伸研究

我国经营性海洋牧场产业目前主要以育苗、养殖、捕捞、生产、加工的产业链形式存在,文章在分析经营性海洋牧场发展制约因素的基础上,对于海产品产业链的延伸进行研究并提出建议:在苗种培育产业的基础上延伸出"参与式观光业",在开展养殖业的同时兼并实施新产业"DIY养殖业",产品收获后进行"精深加工业"的同时开展"观光旅游业",销售行业采取线上线下与企业之间结合的"O2O+B2B"模式,面向客户方面鼓励新机构即"反馈机构"的建立与推广,拓展休闲渔业产业,发展新型休闲渔业。通过产业链延伸,旨在开拓海产品的市场空间,以期获取更多的经济效益,提升海洋牧场综合效益。     

Relationships between body weight and other morphological traits in young sea cucumbers Apostichopus japonicas

Correlation, multiple regression, and path analyses were used to investigate the relationships between body weight and three other morphological traits in juvenile Japanese sea cucumbers Apostichopus japonicus . We measured live body weight (BW), body length (BL), numbers of papillae (NP), and numbers of tube feet (NF) at 60, 80, 100, and 130 days post-hatching (dph). We calculated path correlation coefficients, correlation indices ( R 2 ), and coefficients of determination with BW as the dependent variable and the other morphological traits as independent variables. The coefficient of variation for BW was high across all age groups, and all measured morphological traits were significantly correlated ( P < 0.01). BL had the greatest direct eff ect on BW across all age groups (60 dph, 0.526;80 dph, 0.404;100 dph, 0.620;and 130 dph, 0.681), while NF had the greatest indirect eff ect on BW across all age groups (60 dph, 0.528;80 dph, 0.452;100 dph, 0.666;and 130 dph, 0.603). Regression analyses between morphological traits and BW indicated that R 2 was greater than 0.85 only in the 100-dph specimens. The indirect eff ects of the other measured morphological traits on BW were age-dependent. The optimal regression equations, as determined with stepwise regression, were, for 60-dph specimens: BW 60 =10 (-3.04+0.092BL+0.014NP+0.014NF)( R 2 =0.632);for 80-dph specimens: BW 80 =10 (- 3.035+0.056BL+0.017NP+0.02NF)( R 2 =0.686);for 100-dph specimens: BW 100 =10 (- 3.742+0.069BL+0. 633 · lg (NP)+0. 464 · lg (NF))( R 2 =0.893);and for 130-dph specimens: BW 130 =10 (- 2.472+0.065BL+0.012NP)( R 2 =0.774). Our work clarified the correlation between various morphological traits and body weight of a commercially-important sea cucumber species ( A . japonicus ). Our predictive models for body weight might be useful for the aquaculture and selective breeding of A . japonicus . These models might also provide theoretical support for the indirect selection of traits that are difficult to select directly.     

基于2D地图的城市户外ARGIS视觉辅助地理配准技术

针对当前便携式位姿传感器获取的户外6DOF绝对位姿精度通常不足,致使基于位姿传感器的户外AR地理配准精度不高,提出了一种以2D地图作为参考数据进行户外视觉辅助定位进而提高ARGIS系统地理配准精度的方法和技术框架。在位姿传感器获取初始位姿的基础上,详细阐述了基于2D地图进行图像位姿优化和辅助校正的基本原理;并通过试验验证了该方法可以对位姿传感器获取的初始位姿进行优化,进而提高户外AR地理配准精度的有效性。     

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.     

CCD astrometric observations of 2017 VR12, Camillo and Midas

We have observed three near-Earth objects(NEOs), 2017 VR12, Camillo and Midas, during 2018.The observations were made with the 1-m telescope, operated by Yunnan Observatories, over two nights.Their precise astrometric positions are derived from 989 CCD observations. The theoretical positions of asteroids are retrieved from the Jet Propulsion Laboratory(JPL) Horizons System and Institut de M′ecanique C′eleste et de Calcul des ′Eph′em′erides(IMCCE). The positions of three asteroids are measured with respect to stars in the Gaia DR2 star catalog. For 2017 VR12, the means(O-C) of right ascension and declination are -0.090′′and-0.623′′respectively based on the published JPL ephemeris, but the corresponding means(O-C) are 3.122′′and-0.636′′based on the published IMCCE ephemeris. The great difference in declination could be explained by several factors.(1) The degraded CCD images caused by the fast apparent motion of the objects lead to a reduction in positioning accuracy.(2) The poor timing system may introduce systematic errors, especially in the high speed direction.(3) The asteroid may be perturbed by Earth when it approaches the Earth too closely. These astrometric results demonstrate that the centroid centering method can reduce the dispersion of non-Gaussian images as compared with the PSF modeling method.For Camillo and Midas, the astrometric results are consistent based on the two ephemerides. Implementing a high-precision timing system, and analyzing some astronomical effects and geometric distortions in CCD images should be carefully considered in future works.     

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.     

海洋环境对猎雷声呐探测识别的影响及对策建议

猎雷是各海军强国重点发展方向,猎雷作战中首要的就是探测识别水雷。从传播损失、混响、 目标强度以及海流、潮汐等多个方面分析了海洋环境对猎雷声呐探测识别的影响,并从猎雷作战角度提出了有关参数设置、作战方式、数据处理等对策建议,可为部队探测识别水雷等目标提供有效参考。