**Author details**

used traditional popular automatic methods and clearly showed its ability to extract different

The automatic lineament delineation using the LINE module of PCI Geomatica was deployed and found great ability of data extraction capacity, as it extracts sufficient numbers of lineaments from Landsat 8 OLI imageries. Different types of information extracted from the lineaments data of the two study areas, where number of lineaments, lineament length change, that is, mean and SD value, and directional change were observed. In both cases, their behav-

The present results also identified that the highest lineament fluctuations and abnormality exist within the anomaly phase, which marked as the highest anomaly (strong phase) just 4 days before earthquake strike. Lineaments behavior was observed quite normal (no anomaly, compared with abnormal situation) in 85 days before (Gorkha of Nepal) and 292 days

However, data comparison method and lineament fluctuations successfully identified the lineament anomaly change over the two study areas. Due to progress of Earth observing satellites in different parts of the world, similar experiments can also be tested and compared with another high-resolution imagery. From this analysis, the exact position of earthquake epicenter, magnitude, and timing of occurrences was quite difficult to predict, but the extracted data can only able to identify the abnormality before the earthquake strike at least 4–36 days before. Thereafter, this lineament abnormality along with cloud presence in the images over

Overall, the experimental results have shown positive output, as it has been observed anomaly in pre-earthquake stage. Therefore, the first output concept was considered which developed by theoretical model and regarded as possible earthquake. On the other hand, no abnormal behavior of lineament presents in before, compared to anomaly presence prior to earthquake strike; thus, it is considered as no anomaly and declared as no possible earthquake, which supports the second concept of theoretical model. From this research, it has been observed that Landsat 8 OLI data have some power to extract lineament and helpful for pre-earthquake anomaly detection through lineament change observation. That is the only reason of acceptance of those images for the present study, which also supports the theoretical model. However, present lineament change observation technique using Landsat 8 OLI time series data is found effective for pre-earthquake anomaly study and can be used as an alternative approach for future earthquake monitoring.

This work was supported by the Major State Basic Research Development Program of China (no. 2013CB733405) and the National High Technology Research and Development Program of China (863 Program) (no. 2014AA06A511) and received fellowship fund for PhD Program by Chinese Academy of Sciences and the World Academy of Sciences (CAS-TWAS) under CAS-TWAS President's Fellowship-2015 (no. 2015CTF024) awarded by the University of Chinese Academy of Sciences (UCAS) and give our sincere thanks to USGS earth explorer committee for freely acquisition of Landsat 8 Imageries from their archive. Finally, our special thanks to In Tech

ior is abnormal in the presence of earthquake event regarded as anomaly.

such time period can help to target the zone of probable earthquake epicenter.

kinds of information based on lineament data.

168 Multi-purposeful Application of Geospatial Data

before (Imphal of Manipur) the earthquake event.

**Acknowledgements**

Biswajit Nath1,2,3\*, Zheng Niu1,2\* and Shukla Acharjee<sup>4</sup>

\*Address all correspondence to: nath.gis79@gmail.com and niuzheng@radi.ac.cn

1 The State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences (CAS), Beijing, China

2 College of Resource and Environmental Studies, University of Chinese Academy of Sciences (UCAS), Beijing, China

3 Department of Geography and Environmental Studies, University of Chittagong, Chittagong, Bangladesh

4 Department of Applied Geology, Dibrugarh University, Dibrugarh, Assam, India
