Earth

摘要： Earth, a blue planet in the Solar System, is the only home of human beings. Frequently we consume resources excessively on the Earth. However, if the Earth were driven away from the Solar System, where could we go? There was a film about the dilemma: The Wandering Earth.

摘要： Earth Hour is an annual event which asks people to switch off all lights and use no electricity for an hour.The aim is to get people thinking about the planet they live on and the energy they use.

摘要： Donald V.Helmberger was an unparalleled observational seismologist,and theoretician.His pioneering work in seismic waveform modeling,and the numerical methods he developed to simulate seismograms to study the structure of the Earth and the nature of earthquake sources have become techniques that are now commonplace.

摘要： Domestic Production and Use:Rare earths were mined domestically in 2021.Bastnaesite(or bastnasite),a rare earth fluorocarbonate mineral,was mined as a primary product at a mine in Mountain Pass,CA.Monazite,a phosphate mineral,was produced as a separated concentrate or included as an accessory mineral in heavy-mineral concentrates in the southeastern United States.

摘要： 1.Introduction Recently,the name of Journal of Geological Research has been changed to“Advances in Geological and Geotechnical Engineering Research”.The scope of this journal covering all disciplines of earth sciences and geotechnical engineering research.This journal aims at pioneering research techniques and analysis and is dedicated to deliver theoretical and practical practices for who are engaging in earth sciences and geotechnical engineering research.The journal has been already indexed in Google Scholar,Crossref,CNKI Scholar,MyScienceWork,National Library Board of Singapore,WorldCat,Scilit,BASE,J-Gate,and CiteFactor.

摘要： Domestic Production and Use:Ytrium is one of the rare earth elements.Bastnaesite(or bastnasite),a rare earth fluorocarbonate mineral,was mined in 2020 as a primary product at the Mountain Pass Mine in California,which was restarted in the first quarter of 2018 after being put on care-and-maintenance status in the fourth quarter of 2015.

摘要： It has been more than a year since Don left us.He left us so suddenly.We planned to have a phone call after he settled down at his new house.However,it never happened.Although he had some medical issues persistently in his last year,he had been so dedicated to science that he kept working on multiple papers about Earth’s deep interior.Our unfinished paper is about to provide an alternative explanation of the anomalous SPdKS+SKPdS,which has been routinely used to image the Ultralow Velocity Zone(ULVZ).I am so grateful to Don that he brought me into the deep Earth,taught me how to read seismograms,and always inspired and supported me as my family.

摘要： Seismic waveform modeling is one of the most powerful tools for understanding Earth's structure,since it allows waveforms to be quantitatively predicted using physical source representations and a velocity model.In the late 1960s,Don Helmberger developed the foundations of generalized ray theory(GRT)using the Cagniard-de Hoop method(Helmberger,1968).This advance ushered in a new era of computing synthetic seismograms at local to teleseismic distances in applications ranging from studying strong motions generated by earthquakes to modeling Earth’s interiors from basin to core.

摘要： My journey on the wiggles with Don started from February 2008,when I got an opportunity to visit the Caltech Seismolab as a visiting PhD student,which was made possible via Dr.Sidao Ni’s recommendation.A previous student of Don,Sidao was a professor at the School of Earth and Space Sciences(ESS)at the University of Science and Technology of China(USTC)at that time.Sidao offered the“Computational Seismology”class at USTC where I learned a lot about the modern developments in seismology.I also met Sidao many times to discuss a wide range of research topics,I believe it is a style he inherited from his experiences with Don and other professors in Seismolab.

摘要： MIIT promotes the sustainable development of rare earth industry The Ministry of Industry and Information Technology(MIIT)takes actions to promote the sustainable development of rare earth industry.MIIT organized a symposium to promote the development of rare earth application industry on January 26^(th),2022.The meeting was chaired by Mr.Chang Guowu,Deputy Director of the Raw Material Industry Department of MIIT.

摘要： 本发明公开了一种基于Google Earth Engine云平台的地表水体产品生成方法和系统，该方法利用Google Earth Engine遥感大数据云平台获取全时序Landsat8卫星遥感影像，通过人工选取高精度训练样本，形成不同类型水体和非水体典型样本库，采用归一化植被指数、归一化水体指数和地形坡度等多种指数和影像原始波段构建特征波段，结合高精度训练样本和特征波段，采用随机森林分类器实现全时序地表水体智能提取，构建地表水体出现频率模型，实现了地表水体产品自动化生成；本发明生成的水体产品具有较高的时空分辨率，能够反映地表水体季节动态变化规律，可应用于全国或全球尺度长时序地表水体产品自动生产。

摘要： 本发明基于Google Earth的后台配电监控系统涉及后台配电监控系统，尤其是一种适用于发电、变电或配电站的监控系统。包括依次相联的前置服务层、接入层、应用管理层、存储层和接口层；桌面客户端对核心业务数据库数据信息的操作，包括数据信息的添加、修改和删除，包括1）在底图上进行图元标注，根据地理形态进行图像命名；2）将底图层进行类型标注，同时保存对应的经度和纬度数值；3）打开图元编辑器，对相应的底图层进行进一步详细描述；4）将不同类型线路标注，绘制图元，最后保存；5）对已绘制图元进行参数设定，保存；6）对步骤5）中的图元进行故障或缺陷记录，上传故障或缺陷照片，保存。

摘要： 本发明涉及一种基于Google Earth Engine的区域地表水体快速提取方法，包括如下步骤：（1）基于GEE的Assets模块上传研究区域的矢量数据；（2）选取数据源，本研究选取GEE平台上Sentinel‑2遥感影像集；（3）遥感影像预处理：为了提高遥感影像利用率以及研究区域地表水体提取精度，借助影像的QA波段，去除云、雪、阴影等造成的低质量像素，筛选出研究区云量较少的Sentinel‑2遥感影像；（4）筛选所需范围的遥感影像；借助步骤（1）上传的研究区矢量数据，利用GEE的filterBounds、filterDate等命令，整合目标区域、目标时间段遥感影像。通过本发明，可对任意范围、任意时间段的地表水体进行快速准确提取，且提取时所依据的阈值更趋于稳定，提取效果好，便捷简单。

摘要： 本发明公开的属于水稻面积提取技术领域，具体为一种基于GoogleEarthEngine的水稻面积提取方法，基于谷歌地球引擎云平台，利用Sentinel‑1SAR、Sentinel‑2多光谱和SRTMDEM数据，提取后向散射系数、波段反射率、光谱特征、地形特征和波段/参数直方图特征，利用实测采样数据，采用随机森林分类器，绘制10m分辨率水稻种植分布图，本发明采用自动分类流程，能够准确、高效地提水稻种植面积范围，有效规避我国南方湿、热气候条件下，云层对光学遥感影像的遮挡，且无需额外的人工干预，在样本不足的情况下也能够得到稳定的数据结果，云端处理数据的方式也使其具备大规模推广的条件。

摘要： 本发明公开了一种基于Google Earth Engine的大尺度大豆种植区域提取算法，包括：对遥感影像数据Sentinel‑2进行预处理，从预处理后的遥感影像数据中选取对提取大豆有利的G个波段；计算归一化植被指数和归一化水指数，Sentinel‑2数据中包含G+2个数据；利用GEE平台提供某一年的USDA进行预处理；利用包含G+2个数据的Sentinel‑2数据和预处理后的USDA进行训练集和测试集的构建；将训练集输入三种分类器中进行训练，将测试集输入训练后的分类器中进行分类，根据分类结果得到大豆种植区域。用于解决遥感数据量巨大导致算法效率低、耗时久的问题以及单一算法提取大豆精度不够的问题。

摘要： 本发明提供一种基于Google Earth Engine的湖泊面积动态变化快速遥感估算方法，包括步骤：获取近30年不同时期研究区的Landsat系列2A级影像产品数据集；提取相应的水体指数和植被指数；获得基于所述水体指数的水体信息图，和获得基于所述植被指数的水体信息图；根据基于所述水体指数的水体信息图作出基于所述水体指数的二值化掩模图，和根据基于所述植被指数的水体信息图作出基于所述植被指数的二值化掩模图，并获得最优掩模图；应用掩模提取所述目标水体的水体信息和地物信息；筛除所述水体信息外的其他地物信息；提取水面栅格数据，并将所述水面栅格数据转换成所述目标水体的边界矢量数据；以及计算在所述不同时期所对应的湖泊面积及其动态变化。

摘要： 本发明公开了一种基于Google Earth Engine云平台的地表水体产品生成方法和系统，该方法利用Google Earth Engine遥感大数据云平台获取全时序Landsat8卫星遥感影像，通过人工选取高精度训练样本，形成不同类型水体和非水体典型样本库，采用归一化植被指数、归一化水体指数和地形坡度等多种指数和影像原始波段构建特征波段，结合高精度训练样本和特征波段，采用随机森林分类器实现全时序地表水体智能提取，构建地表水体出现频率模型，实现了地表水体产品自动化生成；本发明生成的水体产品具有较高的时空分辨率，能够反映地表水体季节动态变化规律，可应用于全国或全球尺度长时序地表水体产品自动生产。

摘要： 本发明涉及一种基于Google Earth的辅助野外放样方法，包括如下步骤：拾取Google Earth墨卡托投影坐标值、相关性计算、回归拟合和计算待放样点坐标X、Y对应的墨卡托投影坐标值。本发明利用Google Earth软件将施工区高级控制点进行目视解译并提取坐标值。建立施工区高级控制点坐标与目视解译后坐标值之间的函数关系。将待放样点计算后的坐标标注在Google Earth中后，便可掌握具体待放样点的位置信息，可提高常规放样的效率，达到缩减时间、节约成本的目的。

摘要： 本发明公开了一种将风机点位信息转化到Google Earth软件的方法，包括如下步骤：1)：读取AutoCAD软件中的风机坐标信息；2)：将风机坐标信息导入到Excel中；3)：处理Excel导入的风机坐标信息，并输出.csv格式文件；4)：将输出.csv格式文件导入到Global Mapper软件中；5)：对导入的文件进行坐标系统转换；6)：输出.kml/.kmz格式文件并导入到Google Earth软件中。本发明提出的方法可以在短时间内准确、快速、批量化的将AutoCAD软件风机点位信息转化到Google Earth软件，这样不仅大大提高了工作效率，且操作简单、适用广泛，有效保障了风机布置方案的质量和进度。

摘要： 一种基于Google Earth Engine云平台的潮间带滩涂快速遥感提取方法，涉及潮间带滩涂快速提取方法，本发明是为了解决现有的遥感技术无法准确探测获得潮间带滩涂分布的问题而提出的。筛选Sentinel‑2MSI影像形成一个影像集；计算影像集中每一个影像的水体指数NDWI得到空间上的NDWI图像；形成最大NDWI像元组成的图像；利用mask函数去掉没有水体的区域；形成最大8A反射率的像元组成的图像；利用mask函数去掉非水面的区域；对高潮能够覆盖的所有水面区域低潮时的非水面区域进行空间求交，得到潮间带滩涂的分布图。本发明能准确快速地探测潮间带滩涂分布。