The RVI/CVI database is derived from the CanEcumene 3.0 GDB (Eddy, et. al. 2023) using a selection of socio-economic variables identified in Eddy and Dort (2011) that aim to capture the overall state of socio-economic conditions of communities as ‘human habitats’. This dataset was developed primarily for application in mapping socio-economic conditions of communities and regions for environmental and natural resource management, climate change adaptation, Impact Assessments (IAs) and Regional Assessments (RAs), and Cumulative Effects Assessment (CEA). The RVI/CVI is comprised of five sub-indicators: 1) population change, 2) age structure, 3) education levels, 4) employment levels, and 5) real estate values. Index values are based on percentile ranks of each sub-indicator, and averaged for each community, and for three ranked groups: 1) all of Canada, 2) by province, and 3) by population size. The data covers the Census periods of 2001, 2006, 2011 (NHS), 2016, and 2021. The index is mapped in two ways: 1) as ‘points’ for individual communities (CVI), and 2) as ‘rasters’ for spatial interpolation of point data (RVI). These formats provide an alternative spatial framework to conventional StatsCan CSD framework. (For more information on this approach see Eddy, et. al. 2020). ============================================================================================ Eddy, B.G., Muggridge, M., LeBlanc, R., Osmond, J., Kean, C., and Boyd, E. 2023. The CanEcumene 3.0 GIS Database. Federal Geospatial Platform (FGP), Natural Resources Canada. https://gcgeo.gc.ca/viz/index-en.html?keys=draft-3f599fcb-8d77-4dbb-8b1e-d3f27f932a4b Eddy B.G., Muggridge M, LeBlanc R, Osmond J, Kean C, Boyd E. 2020. An Ecological Approach for Mapping Socio-Economic Data in Support of Ecosystems Analysis: Examples in Mapping Canada’s Forest Ecumene. One Ecosystem 5: e55881. https://doi.org/10.3897/oneeco.5.e55881 Eddy, B.G.; Dort, A. 2011. Integrating Socio-Economic Data for Integrated Land Management (ILM): Examples from the Humber River Basin, western Newfoundland. Geomatica, Vol. 65, No. 3, p. 283-291. doi:10.5623/cig2011-044.

This performance indicates Austin's overall creative vitality in comparison to other cities across the United States.

This statistic displays the consumption vitality index of selected developed cities in China in 2018. The capital city Beijing ranked first with a consumption vitality index of ******, followed by Shanghai and Guangzhou.

China New Kinetic Energy Index of Economic Development: Economic Vitality data was reported at 402.600 2014=100 in 2022. This records an increase from the previous number of 388.800 2014=100 for 2021. China New Kinetic Energy Index of Economic Development: Economic Vitality data is updated yearly, averaging 233.800 2014=100 from Dec 2014 (Median) to 2022, with 9 observations. The data reached an all-time high of 402.600 2014=100 in 2022 and a record low of 100.000 2014=100 in 2014. China New Kinetic Energy Index of Economic Development: Economic Vitality data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Business and Economic Survey – Table CN.OF: New Kinetic Energy Index of Economic Development.

Due to rapid urbanization over the past 20 years, many newly developed areas have lagged in socio-economic maturity, creating an imbalance with older cities and leading to the rise of "ghost cities". However, the complexity of socio-economic factors has hindered global studies from measuring this phenomenon. To address this gap, a unified framework based on urban vitality theory and multi-source data is proposed to measure the Ghost City Index (GCI), which has been validated using various data sources. The study encompasses 8,841 natural cities worldwide with areas exceeding 5 km², categorizing each into new urban areas (developed after 2005) and old urban areas (developed before 2005). Urban vitality was gauged using the density of road networks, points of interest (POIs), and population density with 1 km resolution across morphological, functional, and social dimensions. By comparing urban vitality in new and old urban areas, we quantify the GCI globally using the theory of urban vitality for the first time. The results reveal that the vitality of new urban areas is 7.69% that of old ones. The top 5% (442) of cities were designated as ghost cities, a finding mirrored by news media and other research. This study sheds light on strategies for sustainable global urbanization, crucial for the United Nations' Sustainable Development Goals.The code file gives the calculation process of data respectively, and the excel file gives the obtained data. For the explanation of the fields in “citypoint.shp”, please refer to the Supplementary Information of the paper (https://doi.org/10.1016/j.habitatint.2025.103350).Ref: Zhang, Y., Tu, T., & Long, Y. (2025). Inferring ghost cities on the globe in newly developed urban areas based on urban vitality with multi-source data. Habitat International, 158, 103350. https://doi.org/10.1016/j.habitatint.2025.103350

CoreLogic Dwelling Prices MoM in Australia remained unchanged at 0.60 percent in July. This dataset includes a chart with historical data for Australia CoreLogic Dwelling Prices MoM.

Tracking Austin's "score" on the Creative Vitality Suite Index (CVI Value) is a primary measure of the sustainability of Austin's creative industry ecosystem and the sector's share of the local economy. The CVI Value determines the per-capita concentration of creativity to determine how Austin compares, creatively to the US average and other regions within the US.

The Creative Vitality Index compares the per capita concentration of creative activity in two regions. Data on creative industries, occupations, and cultural nonprofit revenues are indexed using a population-based calculation. The resulting CVI Value shows a region’s creative vitality compared to another region.

The data is calculated and prepared by the Western States Arts Federation (WESTAF) for the CVSuite. www.cvsuite.org

Vibrancy index, calculated by the Shannon's diversity index based on the Points of Interest obtained from OpenStreetMap (methodology of Botta & Gutiérrez-Roig, 2021).

Psychological well-being (energy and vitality index) by sex, age and educational attainment level (average score)

Psychological well-being (energy and vitality index) by sex, age and educational attainment level (average score) Copyright notice and free re-use of data on: https://ec.europa.eu/eurostat/about-us/policies/copyright

Root density was determined as root mass per liter of soil volume. Significant differences are indicated by different letters (ANOVA, followed by TukeyHSD, p≤0.05). Values indicate mean ± SE, (n = 7–9). CCR, COMT and CAD refer to transgenic poplar lines with suppressed activities of cinnamoyl coenzyme A reductase, caffeic acid O-methyl transferase, and cinnamyl alcohol dehydrogenase, respectively. *no significant differences were detected by TukeyHSD.

109 Pingpu Ethnic Settlement Vitality Project-obtained implementation qualifications and subsidy list of funds approved by the local government

The average vitality index values for the different subspace types.

The vitality of urban parks reflects the intensity of green space utilization, gauging visitors’ overall perception of the parks, facilitating integrated park management, and ensuring the parks’ sustainable development. But, the park’s spatial vitality characteristics change over time, and the factors influencing the differences in vitality have not been conclusively established. Therefore, This study employs Baidu heat map data to examine the spatial and temporal distribution patterns of park visitor vitality on holidays and weekdays in urban parks located in the core urban region of Fuzhou City. Meanwhile, this will be achieved by utilizing a geo-detector and MGWR model to examine the factors influencing visitor vitality and analyze the spatial variations in the impact coefficients. The conclusions are as follows: (1)Park vitality varied dramatically between different periods, with park vitality being higher on holidays than on weekdays. The peaks of vitality are all concentrated at 10:00 and 16:00. The park’s vitality on holidays had a pattern of many peaks, with a wave-like fluctuation. On weekdays, there was a notable M-shaped feature. (2)The spatial distribution of vitality has a "bimodal" pattern with two distinct cores and numerous fragmented fragments. There are notable variations in the spatial liveliness of different parks, characterized by a distinct "long-tail effect." In other words, there are just a few parks with high vitality, while many parks have low vitality. (3)The peripheral location features (G2) and the characteristics of transportation infrastructure (G3)are the main factors affecting park vitality; X11 amenities have the highest coefficient of impact on park vitality (0.501 on weekdays and 0.491 on holidays). The factors within the Park attributes (G1) and the park’s social media level (G4) showed a two-way interaction strength increase. (4)The coefficients of influence of impact factors on the space heterogeneity of vacation park vitality exhibit significant variation. The positive indicators have a spatial distribution that decreases from the northwest to the southeast, with the old city district having higher coefficients than the new city district. The negative indicators display the reverse pattern. This study offers scientific methodologies and recommendations for improving and designing urban park landscapes.