A unified representation method for interdisciplinary spatial earth data

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.

Big spatial vector data management: a review

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.

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

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.

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

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.

An optimized hexagonal quadtree encoding and operation scheme for icosahedral hexagonal discrete global grid systems

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.