Abstract—As urbanization accelerates, environmental
challenges such as air pollution, noise, urban heat islands, and
biodiversity loss have intensified. Urban greening is widely
recognized as a key strategy for improving environmental
quality. This study introduces the Urban Greening
Environmental Quality Index (UGEQI), a multi-source data
fusion model integrating the Green View Index (GVI),
Normalized Difference Vegetation Index (NDVI), Air Quality
Index (AQI), Land Surface Temperature (LST), and noise
pollution. Applied to Hitachi City, Japan, results show an
average GVI of 22.40%, below the 25% satisfaction threshold,
with notable differences across road types (e.g., highways: 25%,
residential roads: 17.6%). NDVI exhibits substantial seasonal
variation, peaking at 0.31 in summer and dropping to 0.18 in
winter. The UGEQI model assigns weights using the entropy
method: NDVI (24.7%), GVI (24.6%), LST (19.2%), noise
(16.9%), and AQI (14.5%). Regression analysis (R² = 0.690)
confirms a strong correlation between GVI and NDVI,
highlighting their interdependence. These findings emphasize
the need for targeted greening strategies, particularly in dense
urban areas. The UGEQI model serves as a replicable
framework for cities facing similar environmental challenges,
aiding in developing more effective urban greening strategies to
enhance environmental quality and residents’ well-being.
Keywords—urban greening, environmental quality,
multi-source data fusion, green view index, NDVI, UGEQI
Cite: Dongmin Yin and Terumitsu Hirata, "Comprehensive Assessment of Urban Greening and Environmental Quality Based on Multi-Source Data Fusion: A Case Study of Hitachi City," International Journal of Environmental Science and Development vol. 16, no. 4, pp. 293-305, 2025.
Copyright © 2025 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).