Detection and mapping of bracken fern weeds using multispectral remotely sensed data: a review of progress and challenges

Bracken fern is one of the major invasive plants distributed all over the world currently threatening socio-economic and ecological systems due to its ability to swiftly colonize landscapes. The study aimed at reviewing the progress and challenges in detecting and mapping of bracken fern weeds using different remote sensing techniques. Evidence from literature have revealed that traditional methods such as field surveys and modelling have been insufficient in detecting and mapping the spatial distribution of bracken fern at a regional scale. The applications of medium spatial resolution sensors have been constrained by their limited spatial, spectral and radiometric capabilities in detecting and mapping bracken fern. On the other hand, the availability of most of these data-sets free of charge, large swath width and their high temporal resolution have significantly improved remote sensing of bracken fern. The use of commercial satellite data with high resolution have also proven useful in providing fine spectral and spatial resolution capabilities that are primarily essential to offer precise and reliable data on the spatial distribution of invasive species. However, the application of these data-sets is largely restricted to smaller areas, due to high costs and huge data volumes. Studies on bracken fern classification have extensively adopted traditional classification methods such as supervised maximum likelihood classifier. In studies where traditional methods performed poorly, the combination of soft classifiers such as super resolution analysis and traditional methods of classification have shown an improvement in bracken fern classification. Finally, since high spatial resolution sensors are expensive to acquire and have small swath width, the current study recommends that future research can also consider investigating the utility of the freely available recently launched sensors with a global footprint that has the potential to provide invaluable information for repeated measurement of invasive species over time and space.     

Influence of environmental, root, and stand parameters on soil surface CO2 efflux in a Populus euphratica of desert forest in extreme arid region

Spatial variation in soil surface CO2 efflux was measured in a stand of Populus euphratica in the Ejina Oasis of desert riparian forest in the extreme arid region in northwestern China from April 2007 through October 2007.Measurements were taken with a gas-exchange analyzer linked to a soil-respiration chamber.The mean soil CO2 efflux in the stand was 2.71 μmol/(m2·s) during the growing season and 1.38 μmol/(m2·s) in the nongrowing season.The seasonal maximum (end of May through early June) andminimum (October) CO2 efflux were 3.38 and 0.69 μmol/(m2·s),respectively.The diurnal fluctuation of CO2 efflux was relatively small (< 20 percent),with theminimum appearing around 05:00 and the maximum around 15:00.Linear regression analysis showed soil-surface CO2 efflux to be most highly correlated with soil temperature (R2=0.435) and soil moisture (R2=0.213).When all variables were considered simultaneously,only soil temperature (R2=0.378),soil moisture (R2=0.147),and root volume density (R2=0.021) explained a significant amount of variance in soil surface CO2 efflux.Stand volumes were not correlated with soil CO2 efflux on our sites.     

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由ERS-1波形重构确定我国近海平均海平面

近海岸区域平均海面高在大地测量学、物理海洋学以及地球物理学研究中具有非常重要的意义.受各种条件的制约和限制,目前卫星测高技术主要应用于深海区域,在近海区域尤其是海岸线附近区域的应用几乎为空白.本文根据ERS-1测高卫星回波波形特征,采用五参数线性模型,由最小二乘拟合方法,对近海区域尤其是靠近海岸线附近的ERS-1测高波形数据进行波形重构.比较波形重构前、后解算平均海面高,表明波形重构技术不仅明显改善了解算近海海面高的精度,而且增加了近海测高海平面的分辨率,并使卫星测高有效观测延伸至海岸线附近.随后,本文利用波形重构后海面高数据构造了近海多年平均海平面,并对我国近海海平面特征进行了初步分析.     

A method solving kepler's equation without transcendental function evaluations

We developed two approximations of the Newton-Raphson method. The one is a sort of discretization, namely to search an approximate solution on pre-specified grid points. The other is a Taylor series expansion. A combination of these was applied to solving Kepler's equation for the elliptic case. The resulting method requires no evaluation of transcendental functions. Numerical measurements showed that, in the case of Intel Pentium processor, the new method is three times as fast as the original Newton-Raphson method. Also it is more than 2.5 times as fast as Halley's method, Nijenhuis's method, and others.     

FY-4A GIIRS高时间分辨率温湿度廓线反演及其在台风中的应用

针对2020年第9号台风"美莎克"期间FY-4A 高光谱红外干涉式大气垂直探测仪GIIRS每15 min一次的目标区跟踪加密观测资料,用三维卷积神经网络算法反演的全天空大气温度、湿度廓线分析了台风处于生命史不同阶段时暖心结构和湿度场结构的演变特征。结果表明:卷积神经网络的深度机器学习算法可以用来反演全天空的三维大气温度和湿度垂直廓线,不光适用范围广(晴空和有云视场)、反演精度高,而且反演速度快。利用静止卫星平台高时间分辨率的特性,反演得到的温度、湿度廓线可以细致追踪台风处于发展、成熟和登陆等阶段时暖心结构和湿度场的时空演变特征。台风从发展阶段(热带风暴和强热带风暴)到成熟阶段至登陆消亡时,暖心首先出现在对流层中高层较薄的区域,随着台风强度的加强,深厚的暖心结构明显、强度增加,水平面积增大且垂直往下延伸。由于对流云中强上升气流的输送水汽正距平区逐渐上传至300 hPa,台风最强时密闭云区与四周下沉气流区比湿差高到8 K·kg^-1。暖心结构和高湿度中心随着台风登陆而逐渐消失。     

广东省气象卫星遥感数据资源池设计与应用

气象卫星数据是遥感应用的核心基石,遥感业务平台是遥感应用的重要技术手段。本文利用广东省气象局数据中心分布式NAS存储,分设FY 3D、FY 4A数据资源池,通过数据同步和用户管理技术,设计了面向桌面级业务应用的广东省气象卫星数据资源池V1.0。利用SMART和SWAP两大气象遥感应用系统,各级业务人员可快速制作气象卫星遥感监测和评估产品。通过上述“云+端”的遥感业务架构,有效解决气象遥感数据不易获取的难题和遥感应用的技术壁垒,为推进省、市、县级气象卫星遥感业务一体化提供了一定的应用示范和参考价值。     

利用卫星云图资料制作热带气旋预报路径的一种算法

根据台风生成后在云场中移动的环境条件,引入一个环境作用于台风中心的热力梯度力方向,用该热力梯度力方向与当前台风的移动方向相结合,研究台风移动过程的变化规律,寻找一种简易可行的台风路径预报方法．经过多年实践,本文揭示出台风中心未来沿着当前移动方向与环境作用于台风中心的热力方向合成移动的基本规律：当前台风中心移向与前方晴空区中轴线相交时,台风沿着当前移向前进到与阻挡轴线相交点相距4个纬距的位置时便发生偏转,逐渐与阻挡轴线走向趋于一致;若当前台风中心距相交点的距离小于或等于4个纬距时,则从当前位置发生偏转．文中利用以上规律研制出台风移向变化方程和移动轨迹方程．     

缓倾斜煤层走向长壁式工作面地表沉陷盆地模型

为准确描述地表沉陷盆地分布形态,基于幂指数函数模型,结合缓倾斜煤层走向长壁式工作面地表沉陷盆地的特征,采用理论分析与数值模拟相结合的方法,建立适用于缓倾斜煤层走向长壁式工作面的沉陷盆地模型,分析模型参数的影响因素及参数的变化规律,并验证模型的适用性和预计精度。研究表明：模型参数n反映下沉盆地底部范围大小,主要与采动程度有关,取值范围为1~3,其取值精度取决于观测点个数;参数k反映下沉盆地边缘的收敛速度和下沉影响范围,主要与采煤方法、顶板管理方法及松散层厚度有关,其值可通过地表最大下沉值或煤厚进行确定;在对常村煤矿地表沉陷进行预计时,预计值与实测值的差值平方和为3.08×10⁶,中误差为267.59 mm,为最大下沉值的6.47%。研究缓倾斜煤层走向长壁式工作面地表沉陷盆地模型旨在对常村煤矿地表沉陷的预测和预防工作提供理论基础。