This paper analyzes four practical change detection algorithms with Landsat-8 data on landslide mapping in the Kaikoura earthquake happened on November 14, 2016. Eleven band groups built from seven reflective bands of Landsat-8 data were used in the experiment. Total 21 change detection results based on various combinations of band groups and algorithms were obtained. The results were qualitatively and quantitatively analyzed based on manual interpretation and the ROC curve. It shows that all results have high false alarm rates and the accuracy varies for different combinations. Further analysis indicates that false alarms are those being easily affected by phenology factors and human activities, such as cropland, river, snow, and shadow etc. The high false alarm rate indicated by the ROC curve is additionally due to small but hard to avoid errors in the preparation of ground truths. Furthermore, change vector analysis offers plenty of information but does not directly enhance landslide. Based on above analysis, several possible ways to improve the change detection based landslide monitoring method are given at the end of the paper.