Fast Approximate Energy Minimization via Graph Cuts
IEEE Transactions on Pattern Analysis and Machine Intelligence
Using penalized contrasts for the change-point problem
Signal Processing
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pattern Recognition and Machine Learning (Information Science and Statistics)
On the identification of intra-seasonal changes in the Indian summer monsoon
Proceedings of the Third International Workshop on Knowledge Discovery from Sensor Data
Spatially coherent clustering using graph cuts
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
An online kernel change detection algorithm
IEEE Transactions on Signal Processing - Part II
Detecting precursory events in time series data by an extension of singular spectrum transformation
ACS'10 Proceedings of the 10th WSEAS international conference on Applied computer science
Characterizing sensor datasets with multi-granular spatio-temporal intervals
Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Exploring multivariate spatio-temporal change in climate data using image analysis techniques
Proceedings of the 3rd International Conference on Computing for Geospatial Research and Applications
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The changes in rainfall and temperature patterns over India were detected using Mann-Kendall trend test, Bayesian change point analysis, and a hidden Markov model. A regionalization method was developed to identify homogeneous regions that experience similar weather states. The regionalization helped in finding contiguous regions with strong change signals. The data were investigated at different temporal and spatial resolution to explore the nature of changes. The study found that all India summer monsoon is stable, but the winter or the north-east monsoon is gradually intensifying. It also detected an abrupt drop in the winter and spring temperature over north-central India and a gradual increase in the summer temperature over the peninsular India. Robustness of the detected changes were evaluated using recent reanalysis datasets.