A Comprehensive Measurement of Progress toward Local SDGs with Geospatial Information: Methodology and Lessons Learned
Abstract
:1. Introduction
2. Methodology
- (1)
- SGIF-Aligned Indicator Adoption
- Adaptability: Referring to the analysis of whether each indicator of the Global Indicator Framework has a practical significance for the local context or adapts to the local development priorities;
- Comprehensiveness: Meaning that the selected indictors should cover the major aspects of local SDGs;
- Measurability: Used for determining whether each selected indicator can be quantified with reliable geospatial and statistical data.
- (2)
- Spatiotemporal Data Processing
- (3)
- Data-Driven Indicator Calculation
- (4)
- Evidence-Supported Progress Assessment
- (5)
- Study Area
3. Comprehensive Measurement of SDGs with a Geographic Lens
3.1. Adoption of 102 Indicators with an AERS Strategy
- Adoption means that the original indicator, including metadata (the indicator name, definition, and calculation method), was not changed. An example is indicator “3.2.1: Under-five mortality rate”. The definition is same as the statistical yearbook [42] and the numerical values can be used directly. There were 47 indicators of this type (i.e., adoption).
- Extension means that the name, definition, and calculation method of the original indicator were basically applicable, but the connotation or calculation method was extended somehow. There were six indicators in this category. An example is indicator “6.6.1: Change in the extent of water-related ecosystems over time”. Based on its definition, it was extended into four sub-indicators to quantitatively describe this indicator, i.e., (a) rate of change in the spatial extent of water-related ecosystems; (b) rate of change in the water quantity characteristic of water-related ecosystems; (c) rate of change in the water quality of water-related ecosystems; (d) health status of the typical wetland ecosystem.
- Revision was to modify the calculation method of the indicator in order to better satisfy the needs of local SDGs monitoring. Forty-two indicators were revised. An example is indicator “3.8.1 Coverage of essential health services”. The original definition contained multiple aspects which were too complicated for a county. Therefore, the definition was revised to how fast people can access health services with geospatial view.
- Substitution took place when the original indicator was not applicable. In this case, a new indicator was proposed. Seven indicators were substituted. An example is indicator “2.3.2: Per capita disposable income of rural residents”. The original indicator was the average income of small-scale food producers by sex and indigenous status with no metadata, which was substituted according to the local characteristics.
3.2. Geospatial Di-aggregation and Change Mapping
3.3. Measuring Local Indicators with a Geospatial Lens
4. Comprehensive Assessment of SDG Indicators at Three Levels
4.1. Ranking of Indicators
4.2. Evaluation of Individual Goals
4.3. Evaluation of Goals in Three Clusters
4.4. Overall Assessment
5. Discussion: Lessons Learned and Experience Gained
5.1. Discussion: Lessons Learned and Experience Gained
5.2. Availability of Reliable Geospatial Information
5.3. Moving to Transformative Actions
5.4. Engagement of Stakeholders and Innovative Partnership
6. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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SDG | Num. of SGIF Indicators | Num. of Deqing Indicators | Indicators |
---|---|---|---|
1 | 14 | 5 | 1.1.1; 1.3.1; 1.4.1; 1.a.2; 1. b.1 |
2 | 13 | 9 | 2.1.1; 2.1.2; 2.2.1;2.2.2; 2.3.1; 2.3.2; 2.4.1; 2.a.1; 2.c.1 |
3 | 27 | 15 | 3.1.1; 3.1.2; 3.2.1; 3.2.2; 3.3.1; 3.3.2; 3.3.3; 3.3.4; 3.4.1; 3.6.1; 3.7.1; 3.8.1; 3.b.1; 3.b.2; 3.c.1 |
4 | 11 | 7 | 4.1.1; 4.2.2; 4.3.1; 4.5.1; 4.6.1; 4.a.1; 4.c.1 |
5 | 14 | 4 | 5.1.1; 5.5.1; 5.5.2; 5.c.1 |
6 | 11 | 7 | 6.1.1; 6.2.1; 6.3.1; 6.3.2; 6.4.1; 6.4.2; 6.6.1 |
7 | 6 | 3 | 7.1.1; 7.1.2; 7.3.1 |
8 | 17 | 6 | 8.1.1; 8.2.1; 8.5.2; 8.6.1; 8.9.1; 8.9.2 |
9 | 12 | 9 | 9.1.1; 9.1.2; 9.2.1; 9.2.2; 9.3.1; 9.5.1; 9.5.2; 9.b.1; 9.c.1 |
10 | 11 | 2 | 10.1.1; 10.2.1 |
11 | 15 | 9 | 11.1.1; 11.2.1; 11.3.1; 11.4.1; 11.5.1; 11.5.2; 11.6.1; 11.6.2; 11.7.1; |
12 | 13 | 5 | 12.2.2; 12.4.2; 12.5.1; 12.6.1; 12.7.1 |
13 | 8 | 4 | 13.1.1; 13.1.3; 13.3.1; 13.3.2 |
15 | 14 | 7 | 15.1.1; 15.1.2; 15.2.1; 15.3.1; 15.4.1; 15.4.2; 15.a.1 |
16 | 23 | 5 | 16.1.1; 16.1.3; 16.3.2; 16.5.1; 16.6.1 |
17 | 25 | 5 | 17.1.1; 17.2.1; 17.3.1; 17.8.1; 17.11.1 |
Total | 234 | 102 |
No | Indicator | Type 1 | |
---|---|---|---|
1 | 1.4.1 | Population and proportions living in households with access to basic services | A |
2 | 2.4.1 | Proportion of agricultural area under productive and sustainable agriculture | B |
3 | 3.8.1 | Coverage of essential health services | A |
4 | 6.2.1 | Proportion of population using safely managed sanitation services | A |
5 | 6.3.2 | Proportion of bodies of water with good ambient water quality | B |
6 | 6.6.1 | a Change in the extent of water-related ecosystems over time d Health status of the typical wetland ecosystem | A |
7 | 9.1.1 | a Proportion of rural population living within 2 km of an all-season road b Road density c Weighted average travel time | A |
8 | 11.2.1 | Proportion of population that has convenient access to public transport, by sex, age and persons with disabilities | A |
9 | 11.3.1 | Ratio of land consumption rate to population growth rate | A |
10 | 11.7.1 | Average share of the built-up area of cities that is open space for public use for all, by sex, age, and persons with disabilities | B |
11 | 15.1.1 | Forest area as a proportion of total land area | B |
12 | 15.1.2 | Proportion of important sites for terrestrial and freshwater biodiversity covered by protected areas, by ecosystem type | B |
13 | 15.2.1 | Proportion of forest change | B |
14 | 15.3.1 | Proportion of land that is degraded over total land area | B |
15 | 15.4.1 | Protected area coverage of import. sites for mountain biodiversity | B |
16 | 15.4.2 | Mountain vegetation cover | B |
Indicators | Quantitative Result | Evaluation Reference | |
---|---|---|---|
6.1.1 Proportion of population using safely managed drinking water services | Urban: 100% Rural: 99.6% | Green: ≥98% | I |
6.2.1.a Penetration rate of sanitary toilets in rural areas | 98% | Green: ≥95% | I |
6.2.1.b Service convenience of urban public toilets | From all parts of town, the nearest public toilet can be reached within 16 min | ||
6.3.1 Proportion of wastewater safely treated | Urban domestic sewage: 91.06% | Municipal domestic sewage: 92.4%; | IV |
Rural domestic sewage: 80.68% | Coverage rate of the treatment of domestic wastewater (upper-middle-income countries):59% | III | |
Trade effluent: N/A | |||
6.3.2 Proportion of bodies of water with good ambient water quality | 68.75%, 100% ** | 76.9% | IV |
6.4.1 Change in water-use efficiency over time | The water consumption per 10,000 CNY of GDP in 2017 was 65.7 m3, dropped 23.52% from 2015 | By 2020, the efficiency of water use will be 23% lower than that of 2015 | II |
6.4.2 Level of water stress: freshwater withdrawal as a proportion of available freshwater resources | 25.08% | Green: ≤25% Yellow: 25% < x ≤ 50% | I |
6.6.1 Change in the extent of water-related ecosystems over time | 6.47% | 0–20%: Highly sustainable; 21–40%: Locally sustainable but threatens global stability; 41–60%: Border-line sustainability. Corrective actions are strongly recommended; 61–100%: Unsustainable Urgent renewal is required. | III |
6.6.1.a Rate of change in the spatial extent of water-related ecosystems | 11.14% | ||
6.6.1.b Rate of change in the water quantity characteristic of water-related ecosystems | 8.26% | ||
6.6.1.c Rate of change in the water quality of water-related ecosystems | 0% | ||
6.6.1.d Health status of the typical wetland ecosystem | Xiazhu Lake wetland: In good condition |
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Chen, J.; Peng, S.; Chen, H.; Zhao, X.; Ge, Y.; Li, Z. A Comprehensive Measurement of Progress toward Local SDGs with Geospatial Information: Methodology and Lessons Learned. ISPRS Int. J. Geo-Inf. 2020, 9, 522. https://doi.org/10.3390/ijgi9090522
Chen J, Peng S, Chen H, Zhao X, Ge Y, Li Z. A Comprehensive Measurement of Progress toward Local SDGs with Geospatial Information: Methodology and Lessons Learned. ISPRS International Journal of Geo-Information. 2020; 9(9):522. https://doi.org/10.3390/ijgi9090522
Chicago/Turabian StyleChen, Jun, Shu Peng, Hao Chen, Xuesheng Zhao, Yuejing Ge, and Zhilin Li. 2020. "A Comprehensive Measurement of Progress toward Local SDGs with Geospatial Information: Methodology and Lessons Learned" ISPRS International Journal of Geo-Information 9, no. 9: 522. https://doi.org/10.3390/ijgi9090522