An On-Demand Scalable Model for Geographic Information System (GIS) Data Processing in a Cloud GIS

Abstract

With the rapid development of information processing technology and continuously evolving technological hardware and software, the scale of spatial data has grown exponentially. This has necessitated that stricter requirements be placed on the way data is processed. The traditional single-machine centralized data processing method is gradually being replaced by the network-based cloud geographic information system (GIS) mode. However, the information processing method of the business system in the existing spatial information network environment is difficult to expand, which limits the application of the business system. This paper proposes an on-demand and extended model for the GIS data processing procedure that considers the three-way separation of algorithm development, business processes, and the operational interface, and can implement an on-demand expansion of business processes by process modeling the business and task scheduling the workflow engine. This can expand the scope of business systems and improve the efficiency of business system construction.

Dynamic Update Exploration and Discussion of Basic Geographic Information Data Based on Multi-Source Data Fusion

“…Spatial resolution calculation: Spatial resolution refers to the smallest spatial unit size that can be resolved in remote sensing images, usually measured in meters. [7] The calculation formula for spatial resolution is as follows:…”

PQ-Mist: Priority Queueing-Assisted Mist–Cloud–Fog System for Geospatial Web Services

“…When many GWSs are available online, researchers integrate various services to fulfill the requirements of more complicated applications. As a result, geospatial analysis and the deployment of GWS are both commonly carried out on the cloud (for example, on Amazon Web Services (AWS), Microsoft Azure, and Google Cloud) [2,41,42].…”

Aplicação de geotecnologias na elaboração de índices socioeconômicos associados às ocorrências de desastres naturais no entorno da ferrovia entre as estações Caieiras e Francisco Morato.

“…Devido ao aumento no volume e na variedade de dados, o banco de dados tradicional é propenso a baixa eficiência de armazenamento e fraca capacidade de acesso simultâneo (LI et al, 2015;LI et al, 2016). Além disso, o sistema SIG tradicional executa somente as tarefas de computação na fila de trabalhos; portanto é preciso desenvolver novas tecnologias de armazenamento de dados espaciais (WANG; ZHONG; WANG, 2019) e para se adaptar às necessidades da era de Big Data, também é importante um SIG baseado em nuvem; mas o processo de negócios de um SIG na nuvem é mais complicado em relação ao SIG tradicional (NG et al, 2018), já que as extensões de processos de negócios de SIG na nuvem apresentam deficiências significativas em versatilidade e flexibilidade (ZHANG et al, 2019).…”