顾及地理空间视角的区域SDGs综合评估方法与示范

doi:10.11947/j.AGCS.2019.20180563

测绘学报 ›› 2019, Vol. 48 ›› Issue (4): 473-479.doi: 10.11947/j.AGCS.2019.20180563

顾及地理空间视角的区域SDGs综合评估方法与示范

陈军¹, 彭舒¹, 赵学胜², 葛岳静³, 李志林⁴

1. 国家基础地理信息中心, 北京 100830;
2. 中国矿业大学(北京)地球科学与测绘工程学院, 北京 100083;
3. 北京师范大学地理科学学部, 北京 100875;
4. 香港理工大学土地测量与地理资讯学系, 香港九龙

收稿日期:2018-12-03 修回日期:2019-01-17 出版日期:2019-04-20 发布日期:2019-05-15
作者简介:陈军(1956-),男,教授,研究方向为基础地理信息建模、更新与服务。E-mail:chenjun@nsdi.gov.cn
基金资助:
中国工程科技知识中心建设项目（CKCEST-2018-2-1）

Measuring regional progress towards SDGs by combining geospatial and statistical information

CHEN Jun¹, PENG Shu¹, ZHAO Xuesheng², GE Yuejing³, LI Zhilin⁴

1. National Geomatics Center of China, Beijing, 100830, China;
2. College of Geoscience and Surveying Engineering, China University of Mining & Technology(Beijing), Beijing 100083, China;
3. Faculty of Geographical Sciences, Beijing Normal University, Beijing 100875, China;
4. Department of Land Surveying and Geo-Informatics, Hong Kong Polytechnic University, Hong Kong, China

Received:2018-12-03 Revised:2019-01-17 Online:2019-04-20 Published:2019-05-15
Supported by:
The Project of Chinese Knowledge Center for Engineering Science and Technology(No. CKCEST-2018-2-1)

摘要/Abstract

摘要： 目前世界各国正积极落实联合国《2030年可持续发展议程》及其17项可持续发展目标（Sustainable Development Goals，英文缩写为SDGs），重要举措之一是利用统计和地理信息进行SDGs进展评估监测。就总体而言，国内外这方面研究尚处于概念设计、方法探讨和单指标、小范围试点阶段。究其原因，主要是涉及因素众多、技术过程复杂，既面临全球指标体系的科学理解、海量时空数据的融合处理、顾及地理视角的指标计算、基于事实的SDGs分析评估等诸多技术难题，还要实现跨学科的综合分析、多机构的沟通协调等。针对这一国际前沿课题，笔者研究提出了统计和地理信息相结合的综合评估方法，完成了浙江省德清县践行2030议程情况的定量综合评估。既为总结当地践行SDGs经验、发现存在问题、制定改进方案提供了重要科学依据，也为国内外其他区域开展SDGs定量评估监测提供了可借鉴的方法与范例。

关键词: 2030年议程, 可持续发展目标, 地理信息, 指标, 综合评估

Abstract: The 17 Sustainable Development Goals (SDGs) defined by the Transform our World:2030 Agenda for Sustainable Develepment represents a new coherent way of embracing economic prosperity, social inclusion, and environmental protection as an "indivisible whole". In order to ensure the implementation of this global agenda, the United Nations had proposed a systematic follow-up and review through indicators-based tracking and reporting of the progress with statistical and geospatial information towards SDGs at national, regional and global levels. This has posed many technical and coordination challenges, such as selection of appropriate indicators for a given nation or sub-nation regions, availability and acquisition of reliable data sets, spatio-temporal analysis with a geographical perspective, interaction between SDGs and cross-sector coordination. Although the international society has devoted great attention to this hot topic, most of them remain on the conceptual design and preliminary testing. There are very few good practices for a comprehensive measurement and assessment of progress towards SDGs with integration of statistical and geospatial information at nation or sub-national level. This paper presents the methodology and results of a pioneer project which measured the progress towards SDGs at a county level in China by combining integration of statistical and geospatial information. The major conclusions are ① the comprehensive progress towards SDGs in an entire administrative region can best be measured and assessed by integrating geospatial and statistical information; ② the Deqing county has made significant economic and social advances while maintaining a good ecological environment over the past few years. The results were released at the first United Nations World Geospatial Information Congress as a good practice and a live example to stimulate discussions and further actions on better supporting SDGs with geospatial information.

Key words: 2030 agenda, Sustainable Development Goals (SDGs), geospatial information, indicators, measurement

中图分类号:

P208

陈军, 彭舒, 赵学胜, 葛岳静, 李志林. 顾及地理空间视角的区域SDGs综合评估方法与示范[J]. 测绘学报, 2019, 48(4): 473-479.

CHEN Jun, PENG Shu, ZHAO Xuesheng, GE Yuejing, LI Zhilin. Measuring regional progress towards SDGs by combining geospatial and statistical information[J]. Acta Geodaetica et Cartographica Sinica, 2019, 48(4): 473-479.

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顾及地理空间视角的区域SDGs综合评估方法与示范

Measuring regional progress towards SDGs by combining geospatial and statistical information

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