Journal of Geo-information Science ›› 2020, Vol. 22 ›› Issue (6): 1307-1319.doi: 10.12082/dqxxkx.2020.190524
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CHEN Fangmiao1, HUANG Huiping1,2,*(), JIA Kun3
Received:
2019-09-16
Revised:
2019-12-24
Online:
2020-06-25
Published:
2020-08-25
Contact:
HUANG Huiping
E-mail:huanghp@aircas.ac.cn
Supported by:
CHEN Fangmiao, HUANG Huiping, JIA Kun. Study on the Administration and Construction of Urban Agglomeration with Spatiotemporal Big Data: A Progress Review[J].Journal of Geo-information Science, 2020, 22(6): 1307-1319.DOI:10.12082/dqxxkx.2020.190524
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Tab. 1
Types of big data in the administration of urban agglomeration"
类型 | 内容 | ||
---|---|---|---|
传统数据 | 基础地理数据 | 地貌、水系、植被等基础地理信息数据;居住地、交通境界、特殊地物地名等要素信息 | |
台站观测数据 | 中国科学院、水利部、农业农村部、生态环境部、自然资源部、国家林业局等部门等建立野外观测台站数据,如对农田、森林、草地、荒漠、沼泽、水体等生态系统以及生态站碳氮水通量等观测数据 | ||
社会经济统计数据 | 年鉴、普查中的城市人口和劳动力统计资料、城市经济发展主要指标统计资料、城市社会发展主要统计资料、城市环境与基础设施资料等 | ||
新型数据 | 遥感数据产品 | 多源遥感数据、遥感产品如土地覆盖、土地利用数据,各类遥感指数如植被指数、水体指数、建筑指数、不透水面指数、裸土指数、亮温及湿度指数等 | |
个体时空定位数据 | 手机信令数据、其他具有全球定位功能的个人终端数据 | ||
APP兴趣与消费数据 | 网购支付(淘宝、京东、亚马逊、当当等);生活消费类主题网站(携程、大众点评、58同城、赶集网、链家网等)数据 | ||
电子地图数据 | 电子地图提供商提供的POI信息、用户使用电子地图时获取到的有关用户位置等信息,如百度、高德、谷歌、搜狗、凯立德、天翼等地图服务产品 | ||
社交应用网络数据 | 微信、微博、QQ空间、人人网、Twitter、facebook、Flikr等社交网络数据 | ||
智能交通数据 | 智能交通设备和系统,如智能公交、电子警察、交通信号控制、卡口、交通视频监控、出租车信息服务管理、城市客运枢纽信息化、GPS与警用系统、交通信息采集与发布和交通指挥类平台等 | ||
物联网传感数据 | 服务于城市治安、交通、生态环境质量管理等的城市传感器网络数据。城市管理方面包括货物流跟踪、环境监测、气象监测、城市路灯控制、城市安防监控、车辆监控调度等。生态方面包括温度、湿度、光照度、空气质量、噪音等物理数据,含氧量、二氧化碳等化学数据,细菌数和植被等生物数据 |
Tab. 2
The methods and characteristics of spatiotemporal big data acquisition for urban agglomeration"
数据来源 | 获取方法 | 获取数据举例 | 特点 |
---|---|---|---|
公开数据库 | 网络下载与收集 | 政府公开的社会经济统计数据、常用的数据公开网站和部分共享遥感数据下载平台 | 数据多可免费,传统统计数据类型较多 |
部分网站平台 | 网络爬取、API接 | 网站的财经数据、公司年报、新媒体数据等有价值的信息,如谷歌地图、Facebook等 | 可获得大量有价值的数据,数据属性明确,部分需要付费 |
专业数据交易平台 | 购买 | 基于交易平台的政务、社会、社交、教育、消费、交通、能源、金融、健康等领域的数据资源 | 需要付费,可根据需求购买 |
派生数据 | 自行加工生产 | 如在已经下载的遥感数据基础上分析获取新的信息与知识 | 根据需要进行数据处理,灵活性强 |
其他 | 如通过合作等方式共享数据 |
Tab. 3
Methods of spatiotemporal big data mining for urban agglomeration"
挖掘方法 | 内容 | 城市/城市群建设中的应用示例 |
---|---|---|
遥感反演 | 对不同空间分辨率、时间分辨率、波段传感 器的数据进行分析获取更多地表参量信息 | 可用于城市热岛效应分析和生态环境监测;水质综合评价和生态承载力分析;城市群生态质量和生态安全评价[ |
时空聚类 | 指基于空间和时间相似度把具有相似行为 的时空对象划分到同一组中,使组间差别尽 量大,而组内差别尽量小 | 可进行精准功能区分类,如城市功能区、生态区等;识别异常区域,如生态功能退化区、受自然灾害影响区等[ |
分类 | 指基于训练样本数据确定未知样本数据类 别的过程 | 可用于土地覆盖/利用遥感分类以及特定土地覆盖类型的提取、网络爬取数据的分类等[ |
关联分析 | 也称关联规则挖掘,指从大量数据中挖掘关 联性、相关性,从而进一步提取不同事物间 关系出现的规律和模式 | 可通过开展产业、用地、人口、功能之间的关联分析,提取相应的规则和知识,从而为土地调控、用地协同和功能疏解提供决策支持[ |
机器学习 | 通过多层非线性变换对高复杂度数据建模 的算法的合集,能够处理图像、声音、文本等 多种数据 | 可用于在语言识别、图像分类及目标识别、人脸识别、视频分类和行为识别。在城市群规划中用于面向空间优化利用大数据的挖掘与知识发现技术[ |
数据可视化算法 | 指运用计算机图形学和图像处理技术,将数 据转换为图形或图像在屏幕上显示出来,并 进行交互处理的方法 | 可将遥感和地理信息系统提供的抽象化数据可视化,用于城市群时空发展变化的监测[ |
切片分析 | 指在给定的数据立方体的一个维度上进行的 选择操作 | 可从时间、空间、功能区类别等不同维度对城市群区域土地优化利用大数据等常见时空大数据进行切片分析[ |
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