Effects of the number of stations and time resolution on derivation

For at least 30 years now it has been well known that the Dst index can be modelled using the solar wind as input. Since then, many attempts have been made to improve the predictability of Dst using different approaches. These attempts are useful, for instance, to understand which features of the solar wind–magnetosphere interactions are most important in producing magnetospheric activity and how the Dst index would improve the space weather forecast. The Dst index is by far the most reliable and simple indication that a magnetic storm is in progress. In this work, the effect of using more than four magnetic stations and shorter time intervals than the hourly averages used in Sugiura's procedures is evaluated. The discussion is based on the results presented by Burton in 1975 and Feldstein in 1984 considering 4 or 12 magnetic stations and time averages of 2.5 min for a magnetic disturbed period that occurred from February 7–28, 1967, including two geomagnetic storms. The analysis has shown that the global representation of a magnetic storm by the standard Dst (Sugiura) is well preserved either using 4, 6, 12 magnetic stations or using 1 h, 2.5 min 1 min averages. A brief review of the current understanding of Dst has been included to support the discussions. The analysis performed has shown that a more refined Dst index (time and number of stations>4) would be useful to investigate the intrinsic processes and the different current systems involved in the ring current development during magnetic storms; the standard Dst, as it is conceived, is quite adequate to monitor geomagnetic storms and identify their overall features; concerning the magnetic stations normally considered, the inclusion of higher magnetic latitude stations (>35) may underestimate the observed Dst.     

集成Landsat OLI和机载LiDAR条带数据的亚热带森林生物量制图

以亚热带天然次生林为研究对象,借助一个条带的少量LiDAR点云数据和覆盖整个研究区的免费Landsat OLI多光谱数据,并结合地面实测数据,探索森林生物量低成本高精度制图方法。首先,提取了OLI和LiDAR特征变量,并与地上和地下生物量进行相关分析以筛选变量;然后,借助LiDAR数据覆盖区的样地和条带LiDAR数据构建"LiDAR生物量模型";再从LiDAR反演生物量的结果中进行采样,结合OLI特征变量构建"LiDAR-OLI模型";最后,与单独使用OLI多光谱数据建立的"OLI估算模型"结果进行比较,分析精度并验证新方法的效果。结果表明,"LiDAR-OLI模型"对地上和地下生物量的模型拟合效果较好且均优于"OLI模型",且其交叉验证的精度也较高并优于"OLI模型",从而证明了新方法的可靠性及有效性。本研究为主、被动遥感技术在中小尺度上协同反演森林参数提供了实验基础,也为基于全覆盖免费OLI多光谱数据及条带LiDAR数据的低成本森林生物量制图探索了技术路线。     

用辐射传输方程改进算法反演LandSAT8海表温度的效果检验和适用条件分析

为检验辐射传输方程改进算法推广用于反演LandSAT8 海表温度(SST)的可行性及适用条件,本研究在修订算法部分参数的基础上,分别反演出算法改进前后的LandSAT8 SST并进行比较。MODIS SST验证表明改进算法对大气透过率偏差和SST偏差均有明显改善,除2019-08-21图像外,其他3景图像SST偏差在0.5℃左右;浮标SST验证表明改进算法在近岸海域对SST偏差改善效果同样显著,其平均偏差bias和均方根误差rmse分别减少到0.14、0.18℃,基本可以忽略不计;进一步研究发现,改进算法SST反演精度与研究海域大气透过率分布均匀程度呈显著的正相关关系,R²[bias(SST)]=0.920 7,R²[rmse(SST)]=0.934 0。使用改进算法遥感监测电厂温排水：嵩屿电厂表层海水温升羽流不明显;而后石电厂表层温升现象最显著,温升幅度和扩散影响范围最大,在其排水口附近存在稳定的高温水体(温升＞3℃);晋江电厂表层温升羽流呈扇形分布,流轴短,主要集中在排水口附近。     

综合多特征的Landsat 8时序遥感图像棉花分类方法

传统的多时相遥感图像分类大多拘泥于单一特征,本文基于多时相的Landsat 8遥感数据,开展了综合多特征的特征提取与特征选择方法研究。综合了NDVI时间序列、最佳时相反射率光谱特征以及纹理特征作为初始分类特征,并采用基于属性重要度的粗糙集特征选择算法对其进行特征约简。分类结果表明:(1)利用初始分类特征,分类的总体精度达到92.81%,棉花提取精度达87.4%,与仅利用NDVI时间序列相比,精度分别提高5.53%和5.05%;(2)利用粗糙集选择后的特征分类,分类总体精度可达93.66%,棉花分类精度达92.73%,与初始分类特征提取结果相比,棉花分类精度提高5.33%。基于属性重要度的粗糙集特征选择不仅提高了分类精度,同时有效降低了分类器的计算复杂度。     

知识引导的稀疏时间序列遥感数据拟合

在多云多雨的地区,光学遥感存在着获取无云数据困难的难题,这会导致时间序列应用中可用数据匮乏。因此,本文面向稀疏时间序列遥感数据,根据噪声造成遥感影像上归一化差分植被指数(NDVI)被低估的事实,提出了一种知识引导的拟合方法。首先,在遥感影像预处理的基础上,利用先验知识和时序差分法对噪声进行识别和剔除;然后,采用高斯二阶模型对原始数据进行拟合;最后,根据拟合残差更新权重,进行迭代拟合,重复上述过程直至获得稳定的结果。本文以Landsat 8 OLI作为数据源,对浙江省杭州地区的森林数据进行拟合,结果表明:在稀疏时间序列数据的情况下,本文方法与MODIS数据拟合结果的相关系数达到0.92,关键时点(如NDVI峰值点等)的时间误差在5 d;相比当前主流方法的0.88与8 d具有更高的精度。     

基于Landsat 8 OLI数据与面向对象分类的昆嵛山地区土地覆盖信息提取

利用2015年Landsat 8 OLI遥感影像和DEM作为分类数据源,结合野外调查数据,采用面向对象的分类方法对昆嵛山地区土地覆盖信息进行提取,并对分类结果进行精度评价与比较分析。研究表明：面向对象分类方法提取的各地类连续且边界清晰,分类效果与实际情况基本吻合。昆嵛山地区占主导地位的土地覆盖类型是针叶林,面积为1 546.81 km²。研究区土地覆盖分类的总体精度和Kappa系数分别为91.5%和0.88,其中针叶林、草地、水体和建设用地的生产者精度均达到87%以上。相对于监督分类方法,本研究提出的土地覆盖信息提取方法的总体分类精度和Kappa系数分别提高14.7%和0.17。基于面向对象的中分辨率遥感影像,能够获取较高精度的土地覆盖信息,为大范围土地覆盖分类研究提供方法参考。     

Episodic fluid flow as a trigger for Miocene‐Pliocene slope instability on the Utgard High,Norwegian Sea

Mass wasting is triggered on many continental slopes by a number of mechanisms, including seismic shaking, high sedimentation rates, the presence of weak geological units and gas hydrate dissociation. In this study, the morphology of a Late Miocene–Early Pliocene mass‐transport complex (MTC) on the Utgard High is unravelled and discussed in relation to possible trigger mechanisms. The approach used here includes 3D seismic interpretation and the analysis of variance attribute maps. The interpreted MTC is located on the crest and flanks of the Utgard High and is composed of three mass‐transport deposits with seismic characters varying from transparent and chaotic seismic facies at the base to slightly deformed layers composed of mounds and rafted blocks in the middle and chaotic to transparent reflections at the top. Lithologically, the MTC consists predominantly of claystone with high gamma ray and low density and resistivity values, demonstrating that the associated mounds represent remobilized ooze sediments. A vertical stack of six magmatic sills emplaced from 55.6 to 56.3 Ma into the Upper Cretaceous shales is interpreted at depths of 3,000–5,500 ms two‐way travel time (TWTT). In association with these magmatic sills are several hydrothermal vent complexes that interacted with the top MTC horizon, signifying that episodic and secondary fluid‐venting events might be the principal mechanism facilitating mass wasting in the study area. In addition, the remobilization of ooze sediments into mounds is hypothesized to be dependent on fluids and clayey layers. As a corollary of this work, the importance of relict and recurrent episodes of fluid flow in the Vøring Basin and their influence on the geotechnical integrity of the overburden and later mass wasting is established.     

基于葵花8卫星的上海市夏季对流初生预报研究

参考Mecikalski et al(2010a;2010b)提出的基于GOES系列卫星的对流初生预报方法,针对上海市夏季对流天气特征建立了基于高时空分辨率的静止气象卫星数据的上海市对流初生判识及预报方法。利用该方法对上海市的一次对流初生个例进行了分析,并对2016年7-8月的12次对流初生事件进行了预报试验,结果表明:方法提取的各个指标能够很好地体现对流初生过程中云团的发展变化特征并能剔除掉成熟对流云团边缘像元的干扰;在12次对流初生事件中,成功地预报了其中的11次,预报时间较对流初生时间平均提前了约30 min,但是对于局地弱对流过程该方法仍有一定的缺陷。     

基于潮汐动态淹没过程的长江口潮滩地形信息反演研究

潮滩是陆地与海洋之间重要的生态过渡地带,具有复杂的生态过程和重要的服务功能。受陆海交互作用及人类活动的影响,潮滩处于高度动态变化过程中,而传统测绘技术受到潮滩可达性影响无法快速获取潮滩地形信息。为解决潮滩高程数据获取困难的问题,本文提出一种基于潮汐动态淹没过程和时序遥感影像的潮滩地形信息提取算法,利用K-means++聚类方法实现水域提取,并通过时序淹没特征计算潮滩淹没频率提取潮滩范围信息,最终综合区域潮汐特征反演潮滩地形。研究以崇明东滩为例,利用2016—2020年所有可用Sentinel-2和Landsat-8时序遥感影像,实现潮滩范围提取与高程反演,并通过实测高程数据进行精度验证。研究结果表明,潮滩范围提取总体精度为97.73%,F1_score为0.98;高程反演平均绝对误差为0.15 m,潮滩高程的反演精度与可用影像的数量呈正相关。研究利用该算法进一步反演长江口地区主要潮滩地形特征,结果表明区域内潮滩面积为346.93 km²,高程范围为1.00~3.84 m,且与现有潮滩范围数据集相比,本研究提取的长江口潮滩范围更为完整。该算法为潮滩地形的快速反演提供了可能,对潮滩资源动态监测和管理具有重要意义。