@inproceedings{97829199351c4a9385d732426816c32a,
title = "Online Change Detection Algorithm for Noisy Time-Series: An Application Tonear-Real Time Burned Area Mapping",
abstract = "Lack of the global knowledge of land-cover changes limits our understanding of the earth system, hinders natural resource management and also compounds risks. Remote sensing data provides an opportunity to automatically detect and monitor land-cover changes. Although changes in land cover can be observed from remote sensing time series, most traditional change point detection algorithms do not perform well due to the unique properties of the remote sensing data, such as noise, missing values and seasonality. We propose an online change point detection method that addresses these challenges. Using an independent validation set, we show that the proposed method performs better than the four baseline methods in both of the two testing regions, which has ecologically diverse features.",
keywords = "Burned area detection, Time series, change detection, noise and outlier",
author = "Chen, {Xi C.} and Vipin Kumar and Faghmous, {James H.}",
year = "2016",
month = jan,
day = "29",
doi = "10.1109/ICDMW.2015.237",
language = "English (US)",
series = "Proceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1536--1537",
editor = "Xindong Wu and Alexander Tuzhilin and Hui Xiong and Dy, {Jennifer G.} and Charu Aggarwal and Zhi-Hua Zhou and Peng Cui",
booktitle = "Proceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015",
note = "15th IEEE International Conference on Data Mining Workshop, ICDMW 2015 ; Conference date: 14-11-2015 Through 17-11-2015",
}