Evaluating the Potential of SDGSAT-1 Glimmer Imagery for Urban Road Detection

Sustainable Development Science Satellite 1 (SDGSAT-1), an innovative satellite engineered by the Chinese Academy of Sciences, focuses on achieving sustainable development goals (SDGs) by using high-resolution low-light imaging for urban planning and environmental monitoring. Although its potential to provide substantial information relevant to various SDG indicators has been demonstrated across multiple domains, a comprehensive analysis of the potential of SDGSAT-1 glimmer imagery for urban road detection has not yet conducted. To address this gap, we aimed to evaluate the applicability of SDGSAT-1 glimmer imagery in road detection across five cities with well-developed road networks in China, namely Chengdu, Guangzhou, Hangzhou, Shanghai, and Wuhan. Watershed segmentation and optimal thresholding algorithms were applied to extract the road network data of these five cities. We observed that the large connecting roads, including highways (<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Motorway</i>), urban expressways (<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Trunk</i>), urban main roads (<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Primary</i>), urban secondary roads (<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Secondary</i>), and urban tertiary roads (<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Tertiary</i>), were visible in the SDGSAT-1 glimmer data. Watershed segmentation and optimal thresholding algorithms demonstrated a remarkable precision of approximately 80% for road extraction across all cities. Approximately, 64% of urban roads were detectable within the SDGSAT-1 glimmer imager data. Our study suggests that the SDGSAT-1 glimmer data have great potential for extracting urban roads.