Comprehensive Analysis and Forecasting of Near-Earth Objects Using CNEOS Data (1900-2030)

Abstract

This thesis reviews current knowledge on the origins, dynamical evolution, detection history, and planetary defence context of near-Earth objects (NEOs), followed by a quantitative analysis and a multi-modal forecast of discovery trends. The significance of NEOs has been emphasised by events such as the 2013 Chelyabinsk meteor, causing building damage and injuring more than 1,200 people. Recent advances in survey capabilities have increased detection rates, yet long-term statistical analysis and near-future forecasting remain areas of active research. NEO discovery data (1900-2024) from NASA’s CNEOS database were modelled using exponential, logistic, and 3-segments piecewise linear fits to forecast trends through 2030. Close-approach data (≤0.05 AU) were used only for proximity, diameter and velocity analysis. Therefore, this study provides one of the first direct fits of multi-model forecasts using full-century CNEOS data and compares their performance in projecting future discovery rates. The results show that annual NEO detections have increased exponentially since the late 1990s, reaching over 3,000 in 2024, while close approaches within 0.01 AU have more than quadrupled since 2010. Mean encounter velocities have remained statistically stable (~10.2 km/s), though this reflects a known observational bias against faster objects. The logistic model predicts that cumulative detections will plateau at ~115,000, reflecting the anticipated onset of survey completeness, with the inflection point occurring around 2030. By contrast, the exponential model produces overestimated forecasts, predicting over 77,000 NEOs by the end of 2030, whereas the piecewise model captures past shifts but lacks predictive power beyond 2024, its breakpoints (2001, 2016) were further validated through bootstrap resampling, confirming their robustness. Taken together, these findings underscore the need for bias-corrected forecasting and sustained monitoring, particularly for small, low-albedo, and high-velocity NEOs.