A global urban microwave backscatter time series data set for 1993-2020 using ERS, QuikSCAT, and ASCAT data

Area of Science:

• Earth Observation
• Urban Studies
• Remote Sensing

Background:

• Global urban expansion presents significant environmental and public health challenges.
• Quantifying urban growth trajectories requires consistent, well-calibrated data.
• Microwave backscatter offers insights into vertical built-up area, a key aspect of urban growth.

Purpose of the Study:

• To develop a multi-decadal, global dataset of urban microwave backscatter from 1993-2020.
• To provide a consistent data source for understanding and predicting global urban expansion.
• To characterize changes in vertical built-up areas worldwide.

Main Methods:

• Utilized multi-sensor data (ERS, ASCAT, QuikSCAT) for microwave backscatter analysis.
• Developed a gridded (0.05° lat/lon) dataset covering 1993-2020.
• Validated urban backscatter against building volume data in Europe, China, and the USA.

Main Results:

• Established a strong linear correlation (R² = 0.69) between ASCAT urban backscatter and building volume.
• Created a time series dataset characterizing global urban change over three decades.
• Demonstrated the utility of microwave backscatter for monitoring upward urban growth.

Conclusions:

• The developed urban microwave backscatter dataset is a valuable tool for global urban change analysis.
• This data can improve our understanding of the consequences of urban expansion.
• Consistent, long-term remote sensing data is crucial for monitoring dynamic urban environments.