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International Journal of Digital Earth 2022年第1期15卷 975-1000页

作者： Long Zhao Guoqing Li xiaochuang yao Yue Ma Qianqian Cao Aerospace Information Research Institute Chinese Academy of SciencesBeijingPeople’s Republic of China School of Electronic Electrical and Communication EngineeringUniversity of Chinese Academy of SciencesBeijingPeople’s Republic of China College of Land Science and Technology China Agricultural UniversityBeijingPeople’s Republic of China

Although research on the discrete global grid systems (DGGSs) has become an essential issue in the era of big earth data,there is still a gap between the efficiency of current encoding and operation schemes for hexagonal DGGSs and the needs of practical applications. This paper proposes a novel and efficient encoding and operation scheme of an optimized hexagonal quadtree structure (OHQS) based on aperture 4 hexagonal discrete global grid systems by translation transformation. A vector model is established to describe and calculate the aperture 4 hexagonal grid system. This paper also provides two different grid code addition algorithms based on induction and ijk coordinate transformation. We implement the transformation between OHQS codes and geographic coordinates through the ij,ijk and IJK coordinate systems. Compared with existing schemes,the scheme in this paper greatly improves the efficiency of the addition operation,neighborhood retrieval and coordinate transformation,and the coding is more concise than other aperture 4 hexagonal DGGSs. The encoding operation based on the ijk coordinate system is faster than the encoding operation based on the induction and addition table. Spatial modeling based OHQS DGGSs are also provided. A case study with rainstorms demonstrated the availability of this scheme.

关键词： Discrete global grid systems hexagon quadtree encoding

A unified representation method for interdisciplinary spatial earth data

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Big Earth Data 2023年第1期7卷 126-145页

作者： Shuang Wang Jian Wang Qin Zhan Lianchong Zhang xiaochuang yao Guoqing Li Aerospace Information Research Institute Chinese Academy of SciencesBeijingChina School of Electronic Electrical and Communication EngineeringUniversity of Chinese Academy of SciencesBeijingChina College of Land Science and Technology China Agricultural UniversityBeijingChina

Unified representation of spatial earth data is an essential scientific issue.The analysis and mining of interdisciplinary spatial earth data resources can help discover hidden scientific knowledge,and even reveal the intrinsic relationship among different disciplines.However,the different description methods and inner structures among interdisciplinary spatial earth data bring significant chal-lenges to unified data management and collaborative analysis in earth environment research.To address this issue,this paper pro-poses a unified representation method for interdisciplinary spatial earth data.First,this paper establishes a general metadata model and realizes the unified description of interdisciplinary data.Second,an entity data organization model is presented,which can realize the unified organization of entity data with different inner structures.Finally,we introduce the Spatial Earth Data Format(SEDF),a data format based on HDF5 for implementing the data organization model of interdisciplinary spatial earth data.Data representation experiments and validation are conducted to verify the availability and practicability of the proposed data representa-tion method.The results suggest the powerful ability to represent spatial earth data efficiently and ensure data integrity,which is convenient for data management and application.

关键词： Unified representation spatial earth data general metadata model data organization model Spatial Earth Data Format

A Ceph-based storage strategy for big gridded remote sensing data

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Big Earth Data 2022年第3期6卷 323-339页

作者： Xinyu Tang xiaochuang yao Diyou Liu Long Zhao Li Li Dehai Zhu Guoqing Li College of Land Science and Technology China Agricultural UniversityBeijingChina Key Laboratory of Remote Sensing for Agri-Hazards Ministry of Agriculture and Rural AffairsBeijingChina Aerospace Information Research Institute Chinese Academy of SciencesBeijingChina School of Electronic Electrical and Communication EngineeringUniversity of Chinese Academy of SciencesBeijingChina

When using distributed storage systems to store gridded remote sensing data in large,distributed clusters,most solutions utilize big table index storage strategies.However,in practice,the performance of big table index storage strategies degrades as scenarios become more complex,and the reasons for this phenomenon are analyzed in this paper.To improve the read and write performance of distributed gridded data storage,this paper proposes a storage strategy based on Ceph software.The strategy encapsulates remote sensing images in the form of objects through a metadata management strategy to achieve the spatiotemporal retrieval of gridded data,finding the cluster location of gridded data through hash-like calculations.The method can effectively achieve spatial operation support in the clustered database and at the same time enable fast random read and write of the gridded data.Random write and spatial query experiments proved the feasibility,effectiveness,and stability of this strategy.The experiments prove that the method has higher stability than,and that the average query time is 38%lower than that for,the large table index storage strategy,which greatly improves the storage and query efficiency of gridded images.

关键词： Gridded images distributed storage system metadata management Ceph remote sensing

Big spatial vector data management: a review

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Big Earth Data 2018年第1期2卷 108-129页

作者： xiaochuang yao Guoqing Li Institute of Remote Sensing and Digital Earth Chinese Academy of SciencesBeijingChina

Spatial vector data with high-precision and wide-coverage has exploded globally,such as land cover,social media,and other data-sets,which provides a good opportunity to enhance the national macroscopic decision-making,social supervision,public services,and emergency capabilities.Simultaneously,it also brings great challenges in management technology for big spatial vector data(BSVD).In recent years,a large number of new concepts,parallel algorithms,processing tools,platforms,and applications have been proposed and developed to improve the value of BSVD from both academia and industry.To better understand BSVD and take advantage of its value effectively,this paper presents a review that surveys recent studies and research work in the data management field for BSVD.In this paper,we discuss and itemize this topic from three aspects according to different information technical levels of big spatial vector data management.It aims to help interested readers to learn about the latest research advances and choose the most suitable big data technologies and approaches depending on their system architectures.To support them more fully,firstly,we identify new concepts and ideas from numerous scholars about geographic information system to focus on BSVD scope in the big data era.Then,we conclude systematically not only the most recent published literatures but also a global view of main spatial technologies of BSVD,including data storage and organization,spatial index,processing methods,and spatial analysis.Finally,based on the above commentary and related work,several opportunities and challenges are listed as the future research interests and directions for reference.

关键词： Big data vector data big spatial vector data(BSVD) big data management review

A novel method of determining the optimal polyhedral orientation for discrete global grid systems applicable to regionalscale areas of interest

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International Journal of Digital Earth 2020年第12期13卷 1553-1569页

作者： Jianbin Zhou Jin Ben Rui Wang Mingyang Zheng xiaochuang yao Lingyu Du PLA Strategic Support Force Information Engineering University ZhengzhouPeople’s Republic of China College of Land Science and Technology China Agricultural UniversityBeijingPeople’s Republic of China Troops of 31617 FuzhouPeople’s Republic of China

The polyhedral discrete global grid system(DGGS)is a multi-resolution discrete earth reference model supporting the fusion and processing of multi-source geospatial information.The orientation of the polyhedron relative to the earth is one of its key design choices,used when constructing the grid system,as the efficiency of indexing will decrease if local areas of interest extend over multiple faces of the spherical polyhedron.To date,most research has focused on global-scale applications while almost no rigorous mathematical models have been established for determining orientation parameters.In this paper,we propose a method for determining the optimal polyhedral orientation of DGGSs for areas of interest on a regional scale.The proposed method avoids splitting local or regional target areas across multiple polyhedral faces.At the same time,it effectively handles geospatial data at a global scale because of the inherent characteristics of DGGSs.Results show that the orientation determined by this method successfully guarantees that target areas are located at the center of a single polyhedral face.The orientation process determined by this novel method reduces distortions and is more adaptable to different geographical areas,scales,and base polyhedrons than those employed by existing procedures.

关键词： Discrete global grid systems single polyhedral face convex polygons rotate and translate cost function

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正二十面体六边形全球离散格网编码运算

地球信息科学学报 2023年第2期25卷 239-251页

作者：赵龙李国庆姚晓闯马跃中国科学院空天信息创新研究院北京100094 中国科学院大学电子电气与通信工程学院北京100049 中国农业大学土地科学与技术学院北京100193

全球离散格网系统是指把地球表面按照一定规则离散分割成多分辨率层次结构的格网单元,广泛应用于海量多源空间数据的组织、管理和分析中。六边形全球离散格网具有优良的几何特性,非常适合于空间数据的处理,如何进一步提高六边形全球离... 详细信息

全球离散格网系统是指把地球表面按照一定规则离散分割成多分辨率层次结构的格网单元,广泛应用于海量多源空间数据的组织、管理和分析中。六边形全球离散格网具有优良的几何特性,非常适合于空间数据的处理,如何进一步提高六边形全球离散格网编码运算的效率仍是当前研究的重点。本文采用正二十面体施耐德投影四孔径六边形全球离散格网模型,基于六边形三轴坐标与编码的二进制数的对应关系构建四孔六边形的基础编码结构,将二十面体划分为32个基础六边形,并将之分为3种基础六边形剖分瓦片,在每个六边形剖分瓦片采用基础编码结构进行编码,建立了四孔六边形全球离散格网编码,同时设计了并实现了四孔六边形编码与六边形三轴坐标之间的快速转换,基于此构建了一种高效的四孔六边形全球离散格网编码运算方案,包括编码的算数运算、空间拓扑运算和邻域检索运算及跨面运算。与现有的六边形全球离散格网编码运算方案相比,本文的方案进一步提高了编码算数运算、空间拓扑运算和邻域检索运算的效率,编码加法运算是HLQT的2~3倍,邻域检索运算分别是HLQT的3~5倍和H3的2~3倍,且受格网编码层次的影响较小,编码的跨面邻域检索运算时间略高于面内的运算,可以为全球离散格网系统的研究应用提供支撑。

关键词：全球离散格网系统正二十面体六边形格网编码编码运算六边形三轴坐标系坐标转换格网邻域检索

农业病虫害知识问答意图识别与槽位填充联合模型研究

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农业机械学报 2023年第1期54卷 205-215页

作者：郭旭超郝霞姚晓闯李林中国农业大学信息与电气工程学院北京100083 山东农业大学信息科学与工程学院泰安271018 中国农业大学土地科学与技术学院北京100083

农业病虫害领域的意图识别和槽位填充研究仍处于起步阶段,除语料严重匮乏外,还面临任务相互独立、忽略彼此相关性和未充分利用意图嵌入信息等问题。为此,提出了一种基于意图嵌入信息和槽位门控机制的意图识别与槽-位填充联合模型(AgIG-I... 详细信息

农业病虫害领域的意图识别和槽位填充研究仍处于起步阶段,除语料严重匮乏外,还面临任务相互独立、忽略彼此相关性和未充分利用意图嵌入信息等问题。为此,提出了一种基于意图嵌入信息和槽位门控机制的意图识别与槽-位填充联合模型(AgIG-IDSF)。首先,该模型在共享编码模块引入了注意力机制用于丰富上下文语义特征;其次,提出了一种融合意图嵌入表示和槽位门控机制的意图-槽位交互方法用以增强意图信息指导槽位填充任务的能力,进而提高模型的整体识别性能。在包含22个意图类别、10个槽位类别和11 976条标注样本的自构建语料上进行了实验。结果表明,在该语料上AgIG-IDSF模型的意图识别准确率为94.41%,槽位填充F1值为94.01%,整体识别准确率高达88.07%,显著优于包含双向关联模型在内的多种基准模型,表明了该模型在识别农业病虫害意图与槽位方面的有效性。此外,在公共数据集上的实验结果还表明了该模型具有一定的泛化能力。

关键词：农业病虫害意图识别槽位填充意图嵌入表示门控机制注意力机制

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遥感影像样本数据集研究综述

遥感学报 2022年第4期26卷 589-605页

作者：冯权泷陈泊安李国庆姚晓闯高秉博张连翀中国农业大学土地科学与技术学院北京100083 农业部农业灾害遥感重点实验室北京100083 资源与环境信息系统国家重点实验室北京100101 中国科学院空天信息创新研究院北京100094

随着机器学习、深度学习等人工智能技术在遥感领域的不断应用与发展,基于海量样本的数据驱动模型已经成为遥感影像信息提取的一种新的研究范式,其对样本数据的规模、质量、多样性等提出了更高要求。最近,国内外众多学者和研究机构相继... 详细信息

随着机器学习、深度学习等人工智能技术在遥感领域的不断应用与发展,基于海量样本的数据驱动模型已经成为遥感影像信息提取的一种新的研究范式,其对样本数据的规模、质量、多样性等提出了更高要求。最近,国内外众多学者和研究机构相继发布了一系列遥感影像样本数据集,为大数据时代下遥感影像的信息提取和智能解译等奠定了研究基础。然而目前尚缺乏对上述影像样本数据集的综合分析,针对这一问题,本文在文献检索与分析的基础上,归纳总结了124个具有一定影响力且应用广泛的遥感影像样本数据集并对其元数据进行了分析,并提供了数据来源、应用领域与关键词的发展变化,分析了数据集在空间、时间、光谱分辨率上的差异,以应用领域为依据将其划分为场景识别、土地覆被/利用分类、专题要素提取、变化检测、目标检测、语义分割等8个类别并以部分数据为例进行了具体分析,总结了深度学习模型在数据集上的研究进展,并针对稀疏样本导致的模型过拟合问题,探讨了样本时空迁移、小样本和零样本学习、样本主动发现、样本生成等在遥感影像信息提取中的应用前景。本文首次对遥感影像样本数据集进行了综述研究,可为相关领域科研人员提供数据参考。

关键词：遥感影像样本数据集机器学习深度学习

基于多源光学雷达数据融合的黄淮海平原冬小麦识别

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农业机械学报 2023年第2期54卷 160-168页

作者：冯权泷任燕姚晓闯牛博文陈泊安赵圆圆中国农业大学土地科学与技术学院北京100193 自然资源部农用地质量与监控重点实验室北京100193

遥感技术能够快速准确地获取农作物空间分布信息,为探究2021年黄淮海平原冬小麦空间分布信息,基于Google Earth Engine(GEE)云平台,以Sentinel-1 SAR雷达影像和Sentienl-2光学遥感影像为数据源,通过计算极化特征、光谱特征和纹理特征,... 详细信息

遥感技术能够快速准确地获取农作物空间分布信息,为探究2021年黄淮海平原冬小麦空间分布信息,基于Google Earth Engine(GEE)云平台,以Sentinel-1 SAR雷达影像和Sentienl-2光学遥感影像为数据源,通过计算极化特征、光谱特征和纹理特征,运用随机森林等4种机器学习方法和深度循环神经网络模型,对研究区冬小麦空间分布信息进行提取,并对比各分类器和网络架构的分类精度。结果表明,黄淮海平原冬小麦总面积约为16226667 hm^(2),占研究区总面积的49.17%,其中冬小麦种植面积最大的是河南省,约为4647334 hm^(2),研究区冬小麦种植分布呈现由东向西、由南向北递减的趋势;随机森林是4种机器学习方法中识别精度最高的分类器,总体分类精度为94.30%;在随机森林算法中仅使用Sentinel-1雷达数据总体精度为87.38%,仅使用Sentinel-2光学数据总体精度为93.95%,而融合时序Sentinel主被动遥感数据总体精度为94.30%;在大范围的冬小麦分类上,深度学习模型的泛化性高于机器学习方法。

关键词：冬小麦遥感分类多源数据融合 Google Earth Engine 机器学习深度学习

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矢量大数据管理关键技术研究

测绘学报 2018年第3期47卷 423-423页

作者：姚晓闯中国科学院遥感与数字地球所北京100094 中国农业大学信息与电气工程学院北京100083

在大数据时代,数据已成为国家基础性战略资源的重要组成部分。随着空间信息技术的飞速发展,空间数据的采集手段日趋多元化,地理信息技术在各行各业当中的应用也更加广泛和深入,由此也促使GIS大数据时代的到来。大数据是一把“双刃剑”,... 详细信息

在大数据时代,数据已成为国家基础性战略资源的重要组成部分。随着空间信息技术的飞速发展,空间数据的采集手段日趋多元化,地理信息技术在各行各业当中的应用也更加广泛和深入,由此也促使GIS大数据时代的到来。大数据是一把“双刃剑”,高精度、广覆盖的矢量数据爆炸式地增长,在提升国家级宏观科学决策、社会监管、公共服务以及应急决策管理能力等方面提供了良好的契机;但同时如何有效地进行组织与管理大规模的矢量数据,使其发挥最大的效益,成为了目前实际应用当中迫切需要解决的难题。

关键词：空间信息技术矢量数据数据管理地理信息技术组成部分战略资源空间数据科学决策