Special Issue "Measuring and Monitoring Progress towards SDGs by Integrating Geospatial and Statistical Information"

A special issue of ISPRS International Journal of Geo-Information (ISSN 2220-9964).

Deadline for manuscript submissions: 31 August 2020.

Special Issue Editors

Prof. Dr. Chen Jun
Website
Guest Editor
National Geomatics Center of China, 28 Lianhuachi West Road, Beijing 100830, China
Interests: geospatial data modeling and updating; spatial relation; global land cover mapping; SDGs monitoring
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Prof. Dr. Songnian Li
Website
Guest Editor
Department of Civil Engineering Ryerson University, 350 Victoria Street, Toronto, ON, M5B 2K3 Canada
Interests: geospatial big data; spatio-temporal analysis; moving object and LBS data; geo-collaboration; geospatial web and web services
Special Issues and Collections in MDPI journals
Prof. Yifang Ban
Website
Guest Editor
Division of Geoinformatics and Department of Urban Planning and Environment at KTH Royal Institute of Technology in Stockholm, Sweden
Interests: EO big data analytics; multitemporal remote sensing; SAR-based classification and change detection; urban mapping and wildfire monitoring
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

The United Nations 2030 Agenda defines 17 Sustainable Development Goals (SDGs) and 169 targets, aiming to end poverty, promote prosperity and people’s well-being while protecting the environment by 2030, and representing a new coherent way of embracing economic growth, social inclusion, and environmental protection as an “indivisible whole”. The United Nations further proposed and promoted a systematic follow-up and review of the implementation of this global agenda, including indicators and evidence-based reporting of the progress towards SDGs at national, regional, and global levels.

It was with this background that the First United Nations World Geospatial Information Congress (UN WGIC), held from 19–21 November 2018 in Deqing, China, had taken “Measuring and Monitoring SDGs” as one of its major six themes. Several plenary and parallel sessions were organized to present the latest development and case studies in this field. In particular, the results of a comprehensive measurement of progress towards 2030 SDGs in Deqing County using geospatial and statistical information were presented at the congress and released with an online knowledge portal. It demonstrated that the comprehensive progress towards SDGs in an entire administrative region can best be measured and assessed by integrating geospatial and statistical information.

The integrated utilization of geospatial and statistical information in measuring and monitoring progress towards SDGs presents a number of theoretical, technological, and operational challenges. More efforts should be devoted to this emerging research and application topic, including the exploration of new methodologies and algorithms, the development of monitoring systems and good practices, as well as the formulation of technical standards.

This Special Issue aims to examine these fundamental and operational issues related to the integrated utilization of geospatial and statistical information in measuring and monitoring progress towards 2030 SDGs. We cordially invite original research contributions on topics including, but not limited to, the following:

  • Concepts and models for integrating geospatial and statistical information in supporting 2030 SDGs;
  • Geospatial and statistical information-based comprehensive or thematic measurement and monitoring of progress towards 2030 SDGs at global/national or local levels;
  • Deriving SDGs indicator(s) through the integration of geospatial and statistical information;
  • Geospatial disaggregation and aggregation in supporting SDGs;
  • SDGs analysis and assessment with indicators and geospatial evidence;
  • Data quality and uncertainty issues in measuring and analyzing SDG indicators
  • Visualizing SDG indicators and SDGs progress from a geographical perspective;
  • Geospatial knowledge-supported SDGs service portal;
  • And more.

Papers must be original contributions, not previously published or submitted to other journals. Papers published or submitted for publication in conference proceedings may be considered if they are considerably extended and improved. Authors must use the provided Microsoft Word template or LaTeX template to prepare their manuscript, and must follow the Instructions for Authors at https://www.mdpi.com/journal/ijgi/instructions.

 

Prof. Jun Chen
Prof. Songnian Li
Prof. Yifang Ban
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. ISPRS International Journal of Geo-Information is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • SDG indicators
  • geospatial and statistical integration
  • disaggregation and aggregation
  • measurement and monitoring
  • analysis, assessment and visualization
  • technical standards and guidelines

Published Papers (2 papers)

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Research

Open AccessArticle
Measuring SDG 15 at the County Scale: Localization and Practice of SDGs Indicators Based on Geospatial Information
ISPRS Int. J. Geo-Inf. 2019, 8(11), 515; https://doi.org/10.3390/ijgi8110515 - 13 Nov 2019
Cited by 2
Abstract
To achieve the goal of worldwide sustainable protection and utilization of terrestrial ecosystems, it is necessary to quantitatively assess the implementation of Sustainable Development Goal 15 (SDG 15) at all administrative levels, especially at the grass-roots level, using the indicator framework of the [...] Read more.
To achieve the goal of worldwide sustainable protection and utilization of terrestrial ecosystems, it is necessary to quantitatively assess the implementation of Sustainable Development Goal 15 (SDG 15) at all administrative levels, especially at the grass-roots level, using the indicator framework of the UN SDGs. However, in the SDG 15 indicator system, the relationship between goal and indicators is ambiguous, and the results of the indicators cannot be visualized to show the differences within regions. Moreover, its design scale is country-oriented, which suggests that the indicator system cannot be applied directly to the county levels. In light of these issues, this paper used four modalities of localization to form an indicator system of localization, and applied it in the quantitative evaluation of meeting the objectives of SDG 15 in Deqing County, China. The localized indicator system for county level based on geospatial information included six indicators, which were clustered into three categories: sustainable forest management, halt and reverse land degradation, and conservation of biodiversity. By comparing and evaluating the quantitative results of SDG 15 in Deqing, 70% of the comparable indicators in the localization indicator system were at the forefront of those in China or the world. The results showed that grouped analysis of the targets and indicators could clarify the relationship between the implications of the goal and indicators, and the indicator system based on the geographic information was conducive to displaying the spatial distribution of the results of the indicators and clarifying the internal differences. Full article
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Open AccessArticle
Geospatial Disaggregation of Population Data in Supporting SDG Assessments: A Case Study from Deqing County, China
ISPRS Int. J. Geo-Inf. 2019, 8(8), 356; https://doi.org/10.3390/ijgi8080356 - 13 Aug 2019
Cited by 3
Abstract
Quantitative assessments and dynamic monitoring of indicators based on fine-scale population data are necessary to support the implementation of the United Nations (UN) 2030 Agenda and to comprehensively achieve its 17 Sustainable Development Goals (SDGs). However, most population data are collected by administrative [...] Read more.
Quantitative assessments and dynamic monitoring of indicators based on fine-scale population data are necessary to support the implementation of the United Nations (UN) 2030 Agenda and to comprehensively achieve its 17 Sustainable Development Goals (SDGs). However, most population data are collected by administrative units, and it is difficult to reflect true distribution and uniformity in space. To solve this problem, based on fine building information, a geospatial disaggregation method of population data for supporting SDG assessments is presented in this paper. First, Deqing County in China, which was divided into residential areas and nonresidential areas according to the idea of dasymetric mapping, was selected as the study area. Then, the town administrative areas were taken as control units, building area and number of floors were used as weighting factors to establish the disaggregation model, and population data with a resolution of 30 m in Deqing County in 2016 were obtained. After analyzing the statistical population of 160 villages and the disaggregation results, we found that the global average accuracy was 87.08%. Finally, by using the disaggregation population data, indicators 3.8.1, 4.a.1, and 9.1.1 were selected to conduct an accessibility analysis and a buffer analysis in a quantitative assessment of the SDGs. The results showed that the SDG measurement and assessment results based on the disaggregated population data were more accurate and effective than the results obtained using the traditional method. Full article
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