Estimation of consumption potentiality using VIIRS night-time light data

Area of Science:

• Earth Observation
• Urban Socioeconomic Analysis
• Geospatial Data Science

Background:

• Satellite-derived night-time light (NTL) data serve as a proxy for urbanization and socioeconomic variables.
• New-generation NTL data, like that from the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi NPP satellite, offer improved spatial resolution, timeliness, and reduced noise.
• NTL data are crucial for understanding urban social economy development and disparities.

Purpose of the Study:

• To propose and validate a hybrid model for estimating urban consumption potentiality.
• To leverage comprehensive human activity information from VIIRS NTL data.
• To predict consumption potential in urban areas dynamically.

Main Methods:

• Development of a hybrid model integrating VIIRS NTL data and residential consumption data.
• Application of a flexible geographically weighted regression (GWR) based estimation model.
• Dynamic time-series prediction of urban consumption potential.

Main Results:

• The proposed hybrid model demonstrated higher accuracy compared to traditional regression models in the experimental area.
• The model effectively utilizes VIIRS NTL data for estimating urban consumption potential.
• The study successfully predicted consumption potential in Guiyang, China.

Conclusions:

• The hybrid model provides a robust method for estimating urban consumption potential using VIIRS NTL data.
• This approach can offer valuable guidance for business management and profit enhancement.
• Satellite NTL data are powerful tools for socioeconomic analysis and urban planning.