CN110059122B - Wild animal resource data storage method based on cloud Web - Google Patents
Wild animal resource data storage method based on cloud Web Download PDFInfo
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- CN110059122B CN110059122B CN201910268026.7A CN201910268026A CN110059122B CN 110059122 B CN110059122 B CN 110059122B CN 201910268026 A CN201910268026 A CN 201910268026A CN 110059122 B CN110059122 B CN 110059122B
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Abstract
The invention belongs to the technical field of cloud computing, and particularly relates to a wild animal resource data warehousing method based on cloud Web, which comprises the following specific operation steps of: s1: the method for warehousing the wild animal resource data based on the cloud Web realizes the possibility of infinite expansion of business functions based on the flexible architecture design, realizes cross-platform, mobility and high efficiency of warehousing method services, integrates the specialties of ArcSDE and RMDS to space geographic data, combines the convenience of geographic processing tools, applies the flexibility of Python language, uses the cross-platform characteristics and other characteristics of Web AppBuilder, and forms a set of cloud data warehousing solution scheme which fully utilizes the existing resources and has complementary advantages.
Description
Technical Field
The invention relates to the technical field of cloud computing, in particular to a wild animal resource data storage method based on cloud Web.
Background
Cloud computing is an augmentation, usage, and interaction model for internet-based related services, typically involving the provision of dynamically scalable and often virtualized resources over the internet. Cloud is a metaphor of network and internet. In the past, telecommunications networks were often represented by clouds and later also by the abstraction of the internet and the underlying infrastructure. Therefore, cloud computing can enable you to experience even 10 trillion times per second computing power, and the powerful computing power can simulate nuclear explosion, forecast climate change and market development trend.
Along with the deep development of cloud computing and WebGIS technology and the cross fusion of scaffold concept, widget technology and space geographic processing technology, the development and the construction of the current WebApp platform become customizable and easy to expand, and the existing data storage scheme comprises the following steps: the method comprises the steps of establishing a full stack platform library scheme of an ArcEngine + ArcSDE scheme, an ArcGIS Desktop + Excel scheme, a Vue.js + ArcGIS Api for JavaScript + ArcGIS Server + Oracle database, establishing a WebApp application by utilizing ArcGIS Web Appebuilder and the like.
Existing approach, ArcEngine + ArcSDE scheme: the method has the advantages that certain software development knowledge is required, the architecture is heavy, the period is long, the method can only be operated in a single machine, the requirements on software and hardware equipment are high, and the method is not suitable for field investigation environments, and the ArcGIS Desktop + Excel scheme: the method is only suitable for simple data processing and storage, and is difficult to provide effective support for data information versioning processing, multi-batch data management and the like. The normative and intelligent of data management are not enough, and a full-stack platform library building scheme is as follows: the method has the advantages that the knowledge storage requirement is high, the development period is long, an application worker and a developer need to pay attention to a software environment and a hardware equipment environment at the same time, the technical requirement on configuration of system project personnel is high, and the WebApp application is built by utilizing ArcGIS Web App builder: the domestic related customized extension documents are few and are not used much, so that according to the prior art, the effect of the corresponding system can be exerted by complementing and integrating advantages, innovation and progress are realized, and in the field animal resource investigation, due to the particularity of the field environment, the field database building is complicated and troublesome, a stable platform system for instant access is lacked, data cannot be accessed immediately, the labor cost is saved, and the intellectualization and standardization of database building work cannot be realized.
Disclosure of Invention
The invention aims to provide a wild animal resource data warehousing method based on cloud Web, and aims to solve the problems that in the existing wild animal resource investigation proposed in the background art, due to the particularity of a field environment, field data database building becomes complicated and troublesome, a stable platform system for instant access is lacked, data cannot be accessed immediately, the labor cost is saved, and the intelligentization and standardization of database building work cannot be realized.
In order to achieve the purpose, the invention provides the following technical scheme: a wild animal resource data warehousing method based on cloud Web comprises the following specific operation steps:
s1: applying for a cloud service virtual machine, installing postgreSQL, ArcSDE, ArcGIS Desktop, Web AppBuilder, ArcGIS Server and other software and service platforms, deploying a software development environment, a system online production environment and a spatial database platform;
s2: in a spatial database platform, according to field survey document data and spatial data needing to be put in storage, a table structure of a database is created;
s3: compiling data type recognition algorithm codes for the csv data and the spatial data respectively, realizing automatic recognition of the system on the uploaded csv data and the spatial data, classifying and marking the uploaded data according to specified business logic, and preparing for data storage;
s4: integrating a data type recognition algorithm and a data storage function in geographic processing by using a Model Builder Model construction tool to construct a customized geographic processing Model;
s5: releasing a geographic processing model as geographic processing service and hosting by an ArcGIS Server;
s6: building a foreground UI (user interface) by using the Web AppBuilder, and modifying the style of the Web App;
s7: registering the issued geographic processing service in the Web AppBuilder by using a widget processing mechanism of the Web AppBuilder;
s8: and releasing the website manufactured in the Web AppBuilder to a production environment, and providing system service for a terminal user by using the IAAS characteristic of the cloud platform.
Compared with the prior art, the invention has the beneficial effects that: based on the flexible architecture design, according to the actual business logic requirement, the existing and packaged geographic processing tools are utilized, the method has the advantages that the possibility of unlimited expansion of service functions is realized by bonding through a glue language Python, the code development amount is small, the core service and tool delivery are convenient and quick to use, the warehousing method realizes cross-platform, mobility and high efficiency of service, can support software calling of a Web end or a single client, uses the Web AppBuilder as a platform interface, reduces workload of front-end UI design and deployment, provides a beneficial technical scheme example for rapid deployment and convenient delivery of future online service, integrates the specialties of ArcSDE and RMDS on spatial geographic data, combines the convenience of a geographic processing tool, applies the flexibility of the Python language, uses the cross-platform characteristics and other characteristics of the Web AppBuilder, and forms a set of cloud data warehousing solution scheme which fully utilizes existing resources and has complementary advantages.
Drawings
FIG. 1 is a schematic diagram of a sample area and sample line warehousing model of the present invention;
FIG. 2 is a schematic diagram of a csv data-warehousing model according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention provides a technical scheme that: a wild animal resource data warehousing method based on cloud Web comprises the following specific operation steps;
s1: applying for the cloud service virtual machine, installing software and service platforms such as postgreSQL, ArcSDE, ArcGIS Desktop, Web AppBuilder and ArcGIS Server, deploying software development environment, the production environment that the system came on line to and spatial database platform, concrete operation is: creating a cloud database server virtual machine, installing PostgreSQL as a database and ArcSDE as a spatial data engine on the virtual machine; deploying ArcGIS Desktop 10.X, configuring Python 2.7.X development environment at the same time, defining the system as a database Server, building a spatial database on a cloud database Server virtual machine, building data communication of PostgreSQL, ArcSDE and ArcGIS Desktop, building a WebGIS Server virtual machine by using a cloud platform, deploying an ArcGIS Server map service platform to provide common GIS Server service and serve as a hosting platform of customized geographic processing service (GP service), building a WebApp Server virtual machine by using the cloud platform, and installing Server software of IIS or Tomcat, wherein the system is defined as a WebApp platform Server;
s2: in a spatial database platform, according to field survey document data and spatial data needing to be put in storage, a table structure of a database is created, and the method specifically comprises the following operations: converting field survey document data (csv format) into a data table which can be identified by RMDS, installing attribute fields of the csv data, constructing a corresponding data table, performing pre-storage processing on spatial data (shp format) to obtain a data structure of the spatial data, and building a spatial database through ArcSDE and PostgreSQL;
s3: compiling data type recognition algorithm codes for the csv data and the spatial data respectively, realizing automatic recognition of the system on the uploaded csv data and the spatial data, classifying and marking the uploaded data according to specified business logic, and preparing for data storage;
s4: integrating a data type recognition algorithm and a data storage function in geographic processing by using a Model Builder Model construction tool to construct a customized geographic processing Model, wherein the specific operation is as follows: for the space vector data, subdividing the space vector data into sample area surface data and sample line linear data, identifying algorithm codes, automatically judging the type of the space vector data according to the geometric type of the uploaded vector data, and then guiding the uploaded data into a corresponding space database; the data flow chart is used for judging field survey data (csv format) according to information such as attribute fields, data structures and the like of the csv data, and can subdivide the animal type of the currently uploaded csv format data through judging a recognition algorithm code, so that the currently uploaded csv format data enter the data recognition flow chart in a database;
s5: the method comprises the following steps of releasing a geographic processing model as geographic processing service, hosting the geographic processing service by an ArcGIS Server, and specifically operating as follows: in the ArcGIS Desktop, pre-operating the created geographic processing model, releasing the operation result to a cloud platform virtual machine in a sharing mode, deploying the service of the ArcGIS Server, realizing the hosting of the ArcGIS Server to the geographic processing service model, configuring parameter modes such as service description, scheme inspection, user definition and the like according to specified requirements when the geographic processing service is released, and providing convenience for the GIS Server service citation in the next step;
s6: the method comprises the following steps of building a foreground UI (user interface) by using a Web AppBuilder, and modifying the style of a Web App, wherein the specific operation is as follows: starting the Web AppBuilder, using a dashboard style, and using commonly-used widgets carried by the Web AppBuilder, so that the performance of the webGIS service platform is enriched, for example, widgets carried by a map zoom, a scale, a layer management and the like are introduced;
s7: registering the issued geographic processing service in the Web AppBuilder by using a widget processing mechanism of the Web AppBuilder, wherein the method specifically comprises the following steps: introducing a URL address of a geographic processing service which is already issued to an ArcGIS Server into the geographic processing widget of the Web AppBuilder by using the geographic processing widget of the Web AppBuilder, storing the operation, starting the Web App, and testing the function of uploading data online and entering the data in a warehouse in a computer under a local development environment;
s8: and releasing the website manufactured in the Web AppBuilder to a production environment, and providing system service for a terminal user by using the IAAS characteristic of the cloud platform.
By integrating the above, the wild animal resource data warehousing method based on the cloud Web is based on the flexible architecture design, utilizes the existing and packaged geographic processing tools according to the actual business logic requirements, is bonded through the glue language Python, realizes the possibility of infinite expansion of business functions, has less code development amount, convenient and quick delivery and use of core business and tools, realizes cross-platform, mobility and high efficiency of warehousing method services, can support software calling of a Web end or a single client, uses the Web App builder as a platform interface, reduces the workload of front-end UI design and deployment, provides a beneficial technical scheme example for quick deployment and convenient delivery of future online services, integrates the specialties of ArcSDE and RMDS on spatial geographic data, combines the convenience of the geographic processing tools, applies the flexibility of the Python language, uses the cross-platform characteristics of the Web build builder and the like, a cloud data storage solution scheme which fully utilizes existing resources and has complementary advantages is formed.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (1)
1. A wild animal resource data storage method based on cloud Web is characterized by comprising the following steps: the method for putting wild animal resource data into a database based on cloud Web comprises the following specific operation steps:
s1: applying for a cloud service virtual machine, installing PostgreSQL, ArcSDE, ArcGIS Desktop, Web AppBuilder and ArcGIS Server software and service platforms, deploying a software development environment, a production environment of system online and a spatial database platform;
s2: in a spatial database platform, according to field survey document data and spatial data needing to be put in storage, a table structure of a database is created, and the method specifically comprises the following operations: converting field survey document data into a data table which can be identified by RMDS, installing attribute fields of csv data, constructing a corresponding data table, pre-warehousing spatial data to obtain a data structure of the spatial data, and building a spatial database through ArcSDE and PostgreSQL;
s3: compiling data type recognition algorithm codes for the csv data and the spatial data respectively, realizing automatic recognition of the system on the uploaded csv data and the spatial data, classifying and marking the uploaded data according to specified business logic, and preparing for data storage;
s4: integrating a data type recognition algorithm and a data storage function in geographic processing by using a Model Builder Model construction tool to construct a customized geographic processing Model, wherein the specific operation is as follows: for the space vector data, subdividing the space vector data into sample area surface data and sample line linear data, identifying algorithm codes, automatically judging the type of the space vector data according to the geometric type of the uploaded vector data, and then guiding the uploaded data into a corresponding space database; the data flow chart is used for judging field survey data according to the attribute field and the data structure information of the csv data, subdividing the currently uploaded csv format data into which animal type the data belong through the judgment of the identification algorithm code, and finally entering the data identification flow chart in the database;
s5: releasing a geographic processing model as geographic processing service and hosting by an ArcGIS Server;
s6: building a foreground UI (user interface) by using the Web AppBuilder, and modifying the style of the Web App;
s7: registering the issued geographic processing service in the Web AppBuilder by using a widget processing mechanism of the Web AppBuilder;
s8: and releasing the website manufactured in the Web AppBuilder to a production environment, and providing system service for a terminal user by using the IAAS characteristic of the cloud platform.
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| CN112434117B (en) * | 2020-11-05 | 2021-07-30 | 广州和辰信息科技有限公司 | WebGIS visualization configuration method and system based on Vue |
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