A Geo-spatial Classification Time Series Change Detection Using Remote Sensing Images of Seshachalam Region
DOI:
https://doi.org/10.32628/CSEIT206443Keywords:
Time series change Analysis, Geo-spatia,l Landsat Time Series, Seshachalam Region, Multi-Temporal, Supervised ClassificationAbstract
Time series is a scientific process of determining an ordered sequence of values of a variable within equally spaced time intervals. Mostly this is applied when looking at technical data and its influences on the neighboring surroundings. This type of scientific analysis that can be applied twofold. Firstly, it can be used to obtain a knowledge of the triggering forces and structure that produced the observed data. Additionally, it can be used to fit a model and to predict, monitor the area of interest. This scientific form of analysis can be applied in various sectors so long as the data can be measured over time. The following are some of the applications: Economic and sales forecasting, Crop Yield prediction, Forest cover changes, urbanization, among many other uses. In this analysis, we will focus on time series change detection using image differencing of a classified image and representing the outcome area in a bar graph. The area of study is Seshachalam Hills, Tirupathi an ecological zone in Andhra Pradesh, India.
References
- Masek, J., Goward, S., Kennedy, R., Cohen, W., Morrison, G., Schleeweis, K., and Huang, C. 2013. “United States forest disturbance trends observed using Landsat time series.” Ecosystems, Vol.16(No. 6): pp. 1078-1184. doi:10.10007/s10021-013-9669-9.
- Frank Thonfeld, Antje Hecheltjten& Gunter Menz, Bonn, “Bi-temporal Change Detection, Change trajectories and Time Series Analysis for Forest Monitoring”, PFG 2/2015,0219-0141, Stuttgart, April 2015.
- Cook, Diane. "A Survey Of Methods For Time Series Change Point Detection". International Journal On Remote Sensing, vol 45, no. 34, 2017, pp. 5-6., Accessed 22 July 2020.
- Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W. and Campbell, L.B.2016 Mass data processing of time series Landsat imagery: pixels to data products for forest monitoring. Int. J. Digit. Earth 9, 1035-1054.doi: 10.1080/17538947.2016.1187673.
- Yan, Jining. "A Time-Series Classification Approach Based On Change Detection For Rapid Land Cover Mapping". Journal Of Photogrammetry And Remote Sensing, vol 158, no. 3, 2019, pp. 249-262., Accessed 22 July 2020.
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