Beijing Institute of Big Data Research

Need-responsive accessibility supports equitable sustainable development and reshapes migration as evolving human needs

Realizing the Sustainable Development Goals’ commitment to “leave no one behind” requires accessibility that responds to evolving human needs, yet prevailing accessibility assessments remain static and sector-specific, overlooking hierarchical need evolution and behavioral feedba...

High-Precision Visual Absolute-Localization Method for Deep-Space Probes Based on Salient Landmarks

To address the scarcity of high-precision control points on planetary surfaces and the accumulated drift of conventional relative-localization methods in deep-space exploration missions, this paper proposes a visual absolute-localization method based on salient-landmark contour m...

Evolution of water clarity across the Beijing-Tianjin-Hebei region over the past four decades (1984–2024): Driven by hydrological expansion and anthropogenic intervention

Given escalating water scarcity and rapid urbanization, characterizing the long-term evolution of surface water environments across the Beijing-Tianjin-Hebei (BTH) region is vital for coordinated regional development. Using Landsat imagery spanning 1984–2024, this study quantifie...

Automated Extraction of Long-Term Cyanobacteria Blooming Series from Landsat Imagery Using Deep Learning

Cyanobacterial harmful algal blooms (CyanoHABs) pose serious threats to inland water ecology and environmental security. Despite advances, accurately capturing their long-term dynamics for effective governance remains challenging due to limited datasets and segmentation model acc...

Exploring the role of place visitation big data on small area health measure estimation

Population-level health measures at small geographic scales (e.g., census tracts), including health conditions, preventive behaviors, risk factors, and overall health status, are crucial for guiding effective health planning and policymaking. It has been well established that dem...