文献类型：期刊文献

中文题名：大数据技术在生态环境领域的应用综述

英文题名：Application of Big Data Technology in Ecological Environment: A Review

作者：熊丽君[1];袁明珠[2];吴建强[1]

机构：[1]上海市环境科学研究院,上海200233;[2]华东理工大学资源与环境工程学院,上海200237

年份：2019

卷号：28

期号：12

起止页码：2454

中文期刊名：生态环境学报

外文期刊名：Ecology and Environmental Sciences

收录：CSTPCD;;北大核心:【北大核心2017】；CSCD:【CSCD2019_2020】；

基金：国家自然科学面上基金项目(51979168;51679141);上海市自然科学面上基金项目(19ZR1443900);上海市科委“科技创新行动计划”社会发展领域项目(18DZ1204900)

语种：中文

中文关键词：大数据技术;生态环境;监测评价;模拟预测;优化管理

外文关键词：big data technology;ecological environment;monitoring and evaluation;simulation prediction;optimization management

摘要：大数据技术能够有效处理多来源、多类型、多尺度数据,在生态环境领域受到广泛关注,但中国仍处于起步阶段,探索大数据技术在生态环境领域的应用对推动大数据发展具有重要意义,对生态环境精准监管和综合决策具有显著参考价值。基于国内外最新研究,文章将生态环境大数据技术体系分为数据采集、数据处理和实践应用3个部分,数据采集包括地面监测、卫星遥感监测、地理信息、社会统计及网络抓取,数据处理包括存储管理、预处理、深入处理与整合挖掘4个流程,主要应用于生态环境的监测评价、模拟预测与优化管理3个方面。在监测评价方面,大数据技术有利于实时监控、长期跟踪、网格化评价生态环境质量,提高了生态环境监测评价的有效性,但多领域监测数据的耦合分析、智能纠错、评价方法优化能力有待提升;在模拟预测方面,大数据技术与专业模型整合增加了不同时空尺度下复杂环境要素的模拟精度和预测速度,实现动态预警和生态风险评估,但仍缺乏基于大数据技术的高精度存储、分析和集成模型,缺少更专业、更开放的大数据分析系统支撑模型库;在优化管理方面,促进污染的有效溯源、科学控制与全过程监管,但新型污染物和特征污染物时空分布特征尚不明确,系统性数学模型与风险评价管理体系尚不完善,给基于大数据平台的优化管理带来局限性。因此,应有效集成多领域生态环境监测数据,提升数据处理技术能力,推进大数据应用,以满足政府多源管控需求,提升政府科学决策效果。
The application of big data technology in ecological environment can effectively process multi-source, multi-type and multi- scale data, attracting wide attention at home and abroad, but it is still in early stage in China. Exploring the application of big data technology in ecological environment is of great significance for promoting the development of big data technology, and has reference value for precise supervision and comprehensive decision-making of ecological environment. Based on the latest reports, in this paper, the big data technology in ecological environment was divided into three parts: data collection, processing and application. Data collection includes ground monitoring, remote sensing monitoring, geographic information, social statistics and web crawlers. Data processing includes storage management, preprocessing, further processing and integration mining. Big data technology can be mainly applied to the monitoring and evaluation, simulation prediction and optimization management for ecological environment. It can be conducive to real-time monitoring, long-term tracking and grid evaluation of ecological environment quality, improving the effectiveness of ecological environment monitoring and evaluation, however, the performance of coupling analysis, intelligent correction for errors and optimization of evaluation methods for multi-field monitoring data needs to be improved. The integration of big data technology and professional models can increase the simulation accuracy and prediction speed of complex environmental factors in different time and space scales, and realize the dynamic pre-alarm of environmental pollution and ecological risk assessment. However, the models with high-precision storage, analysis and integration based on big data technology are still lacking, as well as the model library supported by more professional and open big data analysis system. For the optimization management, big data technology can promote the effectiveness of pollution tracing, control and whole process supervision. However, the spatial and temporal distribution characteristics of new pollutants are not clear, and the systematic mathematical model and risk assessment management system are not perfect, which will bring limitations to the optimization management based on big data platform. Therefore, it is necessary to effectively integrate ecological environment monitoring data for multi-field, improve the technical ability of data processing, and promote the application of big data technology, so as to meet the needs of multi-source management, and improve the government’s decision-making.