Temporal Analysis for Detection of Anomalies in Precipitation Patterns over a Selected Area in the Indus Basin of Pakistan

Ali, Akhtar; Farid, Hafiz Umar; Khan, Zahid Mehmood; Ahmad, Ijaz; Anjum, Muhammad Naveed; Mubeen, Muhammad; Shakoor, Aamir

doi:10.1007/s00024-021-02671-9

Cited by 3 publications

(2 citation statements)

References 54 publications

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“…The LC algorithm is based on contrast-based saliency detection, which compares three levels of saliency description, the three levels are: salient point, salient area, salient view [21]. In this algorithm, the color statistics of the image are used to display the color contrast information of the scene.…”

Section: Lc Algorithmmentioning

confidence: 99%

Saliency area detection algorithm of electronic information and image processing based on multi-sensor data fusion

Zhang

2021

EURASIP J. Adv. Signal Process.

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Researched in the 1980s, multi-sensor data convergence has become a hot issue. Not only does it differ from general signal processing, or single to multiple sensor surveillance and measurement, on the other hand, it is a higher level of integrated decision-making processes based on multiple sensor measurement outcomes, this paper is based on the study of the saliency area detection algorithm of electronic information and image processing based on multi-sensor data fusion, based on the improved FT algorithm and LC algorithm using multi-sensor data fusion technology, a new LVA algorithm is proposed, and these three algorithms are evaluated in an all-round way through various algorithm evaluation indicators such as PR curve, PRF histogram, MAE index, and recognition image rate. The research results show that the LVA algorithm proposed in this paper improves the detection rate of saliency maps by 5–10%.

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Section: Lc Algorithmmentioning

confidence: 99%

Saliency area detection algorithm of electronic information and image processing based on multi-sensor data fusion

Zhang

2021

EURASIP J. Adv. Signal Process.

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“…Using the RClimdex 1.0 program, dos Santos et al (2011) discovered that rainfall varied greatly over Utah (United States) from 1930 to 2006. At 12 selected meteorological stations, Ali et al (2021), using Innovative Trend Methodology (ITM), revealed significant rising trends over the summer, with trend values ranging from 0.22 to 2.46. Furthermore, at a specific significance level, the ITM's performance was shown to be compatible with both MK and Sen's slope estimator tests.…”

Section: Introductionmentioning

confidence: 99%

Improving the visualization of rainfall trends using various innovative trend methodologies with time–frequency-based methods

et al. 2022

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In this paper, the Innovative Trend Methodology (ITM) and their inspired approaches, i.e., Double (D-ITM) and Triple (T-ITM), were combined with Hilbert Huang transform (HHT) time frequency-based method. The new hybrid methods (i.e., ITM-HHT, D-ITM-HHT, and T-ITM-HHT) were proposed and compared to the DWT-based methods in order to recommend the best method. Three total annual rainfall time series from 1920 to 2011 were selected from three hydrological basins in Northern Algeria. The new combined models (ITM-HHT, D-ITM-HHT, and T-ITM-HHT) revealed that the 1950–1975 period has significant wet episodes followed by a long-term drought observed in the western region of Northern Algeria, while Northeastern Algeria presented a wet period since 2001. The proposed approaches successfully detected, in a visible manner, hidden trends presented in the signals, which proves that the removal of some modes of variability from the original rainfall signals can increase the accuracy of the used approaches.

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Classic trend analysis methods’ paradoxical results and innovative trend analysis methodology with percentile ranges

Birpınar¹,

Kizilöz

Şişman

2023

Theor Appl Climatol

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Temporal Analysis for Detection of Anomalies in Precipitation Patterns over a Selected Area in the Indus Basin of Pakistan

Cited by 3 publications

References 54 publications

Saliency area detection algorithm of electronic information and image processing based on multi-sensor data fusion

Saliency area detection algorithm of electronic information and image processing based on multi-sensor data fusion

Improving the visualization of rainfall trends using various innovative trend methodologies with time–frequency-based methods

Classic trend analysis methods’ paradoxical results and innovative trend analysis methodology with percentile ranges

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