Monitoring Deforestation Using Multivariate Bayesian Online Changepoint Detection with Outliers
含异常值的多元贝叶斯在线变点检测:森林砍伐监测
Near real time change detection is important for a variety of Earth monitoring applications and remains a high priority for remote sensing science. Data sparsity, subtle changes, seasonal trends, and the presence of outliers make detecting actual landscape changes challenging. Adams and MacKay (2007) introduced Bayesian Online Changepoint Detection (BOCPD), a computationally efficient, exact Bayesian method for change detection. Incorporation of prior information allows for…