Regional soil organic carbon prediction model based on a discrete wavelet analysis of hyperspectral satellite data

Most studies have the achieved rapid and accurate determination of soil organic carbon (SOC) using laboratory spectroscopy; however, it remains difficult to map the spatial distribution of SOC. To predict and map SOC at a regional scale, we obtained fourteen hyperspectral images from the Gaofen-5 (GF-5) satellite and decomposed and reconstructed the original reflectance (OR) and the first derivative reflectance (FDR) using discrete wavelet transform (DWT) at different scales. At these different scales, as inputs, we selected the 3 optimal bands with the highest weight coefficient using principal component analysis and chose the normalized difference index (NDI), ratio index (RI) and difference index (DI) with the strongest correlation with the SOC content using a contour map method. These inputs were then used to build regional-scale SOC prediction models using random forest (RF), support vector machine (SVM) and back-propagation neural network (BPNN) algorithms. The results indicated that: 1) at a low decomposition scale, DWT can effectively eliminate the noise in satellite hyperspectral data, and the FDR combined with DWT can improve the SOC prediction accuracy significantly; 2) the method of selecting inputs using principal component analysis and a contour map can eliminate the redundancy of hyperspectral data while retaining the physical meaning of the inputs. For the model with the highest prediction accuracy, the inputs were all derived from the wavelength range of SOC variations; 3) the differences in prediction accuracy among the different prediction models are small; and 4) the SOC prediction accuracy using hyperspectral satellite data is greatly improved compared with that of previous SOC prediction studies using multispectral satellite data. This study provides a highly robust and accurate method for predicting and mapping regional SOC contents.     

BDS卫星钟差半参数平差模型异常数据探测与处理

针对北斗卫星钟差数据中出现钟跳、粗差等异常数据频次较高的问题,将半参数平差模型引入BDS的钟差数据的处理过程中。首先,在考虑系统误差的同时,改进了常用的钟差模型;其次,综合考虑异常数据和系统误差,利用补偿最小二乘原理和极值求解方法,详细推导了分离异常数据前后参数和非参数估计值与相应观测值改正数的关系表达式,实现了异常数据的定值、参数求解和系统误差分离。在此基础上,引入Cook距离,给出了利用参数分量和非参数分量的Cook距离及混合Cook距离,去判断异常值的位置,并给出了一些参数的选取方法及相应的处理措施,实现了卫星钟差异常数据的定位和定值以及部分系统误差的分离。最后,采用武汉大学GNSS中心提供的采样间隔为5 min的北斗卫星精密钟差数据,将本文方法与常用方法进行了试验对比。试验结果表明,本文方法能够有效地识别并处理卫星钟差数据中的异常值,有效克服了基于经验阈值钟差异常数据探测方法的不足,且该方法对于量级较小的异常钟差数据也有很好的探测效果,一定程度丰富了现有的BDS钟差数据质量控制方法。     

微型全极化SAR海洋监测应用技术研究

我国作为海洋大国,近年来海洋事业进入快速发展时期,合成孔径雷达以其自身的技术特点在海洋遥感监测中发挥了重要的作用。在以往的海洋监测中大多采用星载合成孔径雷达获取海洋数据,但因星载SAR受到卫星搭载平台和运行轨道等因素影响,对局部地区高时效的数据获取还存在一定的制约因素。本文通过对无人机机载微型全极化合成孔径雷达对海岸带、海岛礁、海洋动目标高分辨率成像和应用分析研究,为无人机机载SAR在海洋监测中的应用提供了全新的技术手段。     

利用GLAS激光测高数据评估DSM产品质量及精度优化

提出了一种利用卫星激光测高数据直接优化提升数字表面模型（DSM）产品精度的方法。选取境外中亚地区的资源三号DSM开展试验，通过采用多准则约束方法提取激光高程控制点，分别利用偏度、中值、线性、二次多项式等进行DSM误差修正，发现4种模型均能有效消除DSM系统误差，其中基于二次多项式的方法更适用于平地和丘陵地貌，线性模型更适用于高山地貌。试验验证了采用卫星激光测高数据优化境外DSM技术流程的可行性，最终可提高DSM的绝对高程精度。     

基于钻进状态监测的智能工况识别

钻进过程状态监测旨在实时描述钻进工况，判断运行性能优劣程度进行非优追溯，及时指导司钻人员调整作业操作,保证钻进过程安全、高效、稳定开展。钻进工况是钻进系统运行状态的反映，因此开展面向状态监测技术的钻进工况识别研究具有重要的理论和应用价值。本文针对钻进工况识别问题，基于状态监测数据，建立基于支持向量机的钻进工况识别模型，对钻进工况进行识别。综合工况识别结果，对钻进效率进行评估，并对影响钻进效率的因素进行讨论，寻找提升钻进效率的手段。最后，采用钻进现场实钻数据进行仿真实验,验证所提方法的可行性和有效性。     

Digital mapping of coastal boulders – high-resolution data acquisition to infer past and recent transport dynamics

Coastal boulder fields provide clues to long-term frequency-magnitude patterns of coastal flooding events and have the potential to play an important role in coastal hazard assessment. Mapping boulders in the field is time and labour-intensive, and work on intertidal reef platforms, as in the present study, is physically challenging. By addressing coastal scientists who are not specialists in remote sensing, this contribution reports on the possibilities and limitations of digital applications in boulder mapping in Eastern Samar, Philippines, where recent supertyphoons Haiyan and Hagupit induced high waves, coastal flooding and boulder transport. It is demonstrated how satellite imagery of sub-metre resolution (from Pléiades and WorldView-3 imagery) enables efficient analysis of transport vectors and distances of larger boulders, reflecting variation in latitudes of both typhoon tracks and approaching angles of typhoon-generated waves. During the investigated events, boulders with a-axes of up to 8 m were clearly identified to have been shifted for up to 32 m, mostly along the seaward margin of the boulder field. It is, however, hard to keep track of smaller boulders, and the length of a-axes and b-axes including their orientation is often impossible to map with sufficient accuracy. Orthophotographs and digital surface models created through the application of an unmanned aerial vehicle and the ‘Structure from Motion’ technique provide ultra-high-resolution data, and have the potential to not only improve the results of satellite image analysis, but also those from field mapping and may significantly reduce overall time in the field. Orthophotographs permit unequivocal mapping of a-axes and b-axes including their orientation, while precise values for c-axes can be derived from the respective digital surface models. Volume of boulders is best inferred from boulder-specific Structure from Motion-based three-dimensional models. Battery power, flight speed and altitude determine the limits of the area covered, while patches shielded by the boulders are difficult to resolve. For some tasks, field mapping remains mandatory and cannot be replaced by currently available remote sensing tools: for example, sampling for rock type, density and age dating, recording of lithological separation of boulders from the underlying geological unit and of geomorphic features on a millimetre to decimetre-scale, or documentation of fine-grained sediment transport in between the boulders in supratidal settings. In terms of future events, the digital products presented here will provide a valuable reference to track boulder transport on a centimetre to decimetre-scale and to better understand the hydrodynamics of extreme-wave events on a fringing reef coastline.     

基于TCP-InSAR的采动区铁路动态沉降监测与时序分析

为高效获取采动区长时间序列形变，监控煤炭开采对矿区铁路的影响，研究一种基于TCP-InSAR(temporarily coherent point interferometric synthetic aperture radar)的采动区铁路形变监测方法。该方法根据时间序列SAR影像间的相干性，选取临时相干点构建Delaunay三角网，并通过离群值探测去除具有相位模糊度的TCP间的弧段，最后采用最小二乘解算得到区域地表变形。实验使用2016-10~2017-04时间段内的15景Sentinel-1A数据，利用TCP-InSAR技术获得某矿区的铁路形变。结果表明，受采动影响，该时间段内铁路最大下沉值为95 mm，最大倾斜坡度为0.37‰。利用TCP-InSAR技术可实现采动区内铁路长时间的动态形变监测。     

2018年秦皇岛风暴潮前后岸基站及浮标主要水质参数变化分析

对2018年8月秦皇岛风暴潮期间3个入海口岸基站及邻近海域浮标的监测数据进行分析,结果显示:风暴潮导致入海口水体中COD、总磷、总氮和氨氮含量均明显升高;风暴潮2 d之后,3个入海口邻近海域均发生赤潮,此次赤潮的发生与风暴潮导致陆源入海污染物骤然大幅升高有关。此次风暴潮导致秦皇岛人造河口、大蒲河口和七里海3个岸基监测站的COD监测日均值最高分别达到15.83 mg/L、8.70 mg/L和7.92 mg/L,约升高至前期的2倍、1.5倍和2倍;人造河口总氮变化不大,大蒲河口和七里海总氮升高30%左右;大蒲河口总磷变化不大,人造河口总磷为前期的3.5倍,升高幅度最大,七里海总磷为风暴潮之前两日的2倍,但未超过前一周的最高浓度;风暴潮当天及第二天,人造河口、大蒲河口、七里海氨氮日均值陆续达到最高,分别为2.34 mg/L、1.11 mg/L和0.12 mg/L,分别为风暴潮前两日的7倍、3.5倍和10倍。风暴潮过后,入海口临近海域发生赤潮,浮标监测到叶绿素a最高值为76.4μg/L,pH和溶解氧也大幅升高。分析表明,此次风暴潮导致的入海口污染物突然大幅升高为风暴潮之后的赤潮发生提供了充足的营养基础。     

Long‐term temporal and spatial patterns in bioeroding sponge distribution at the Abrolhos Bank,Brazil, Southwestern Atlantic

Bioeroding sponges belong to the most dominant bioeroders, significantly contributing to the erosion of coral reefs. Some species are tolerant or even benefit from environmental conditions such as ocean warming, acidification, and eutrophication. In consequence, increases in sponge bioerosion have been observed on some coral reefs over the last decades. The Abrolhos Bank is the largest coral reef system in the South Atlantic. It has been affected by sedimentation, eutrophication, overfishing, and climate change, mainly affecting coastal reefs, and at lesser intensity outer ones as well. This study aimed to describe spatial and temporal patterns in bioeroding sponge distribution in carbonate substrates in the Abrolhos Bank. Photo‐quadrats were used to compare bioeroding sponge abundance between two shallow reefs: a coastal, Pedra de Leste (PL), and an outer reef, Parcel dos Abrolhos (PAB). Each individual was delimitated over the substrate by determining the sponge surface through a line connecting the outermost papillae. The study was conducted over 6 years in 2008–2009 and 2013–2016. Four species of bioeroding sponges were identified: Cliona carteri Ridley, 1881, C. delitrix Pang, 1973, C. cf. schmidtii Ridley, 1881, and Siphonodictyon coralliphagum Rützler, 1971. The distribution and abundance of species varied between the inner and outer reefs and across the years, and displayed certain selectivity for the calcareous substrates recorded. Crustose coralline algae (CCA) were the main substrate excavated by the most abundant bioeroding species, C. carteri, and represented 70% of the substrate types occupied by this sponge (CCA, coral overgrown by CCA and plain coral). The highest abundance of bioeroding sponges observed in photo‐quadrats was 21.3 individuals/m² at the outer reefs (PAB) in 2014. The abundances or areal extents of bioeroding sponges were up to 10 times greater on the outer reefs than on the coastal ones, where sedimentation is higher and more strongly influenced by siliciclastic material. Moreover, a higher herbivorous fish biomass has been reported on outer reefs which could also influence the higher abundance of bioeroding sponges in outer reefs. During the study period of 6 years, an increase in bioeroding sponge abundance was observed at the outer reefs (PAB), with the sea surface temperature increase. As CCA have an important role in reefal cementation and carbonate production in the Abrolhos reefs, a bioerosion impact might be expected, in particular, on the outer reefs.     

基于散射计风场数据的台风强度诊断方法——以海洋二号卫星数据为例

本文提出了一种基于散射计风场数据的台风定强方法。该方法定义了台风所在海区的一个圆形区域上的风速平均值来对台风进行定强，并使用海洋二号卫星散射计历史数据对该方法进行了验证。验证结果表明，该台风定强方法可以克服散射计反演台风风速过低的问题。与台风强度监测的历史记录比较的结果显示，在台风强度低于"强台风"这一强度等级时，该方法能够有效估算台风强度。