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Kate Carlson, Barbara P. Buttenfield and Yi Qiang
Quantification of all types of uncertainty helps to establish reliability in any analysis. This research focuses on uncertainty in two attribute levels of wetland classification and creates visualization tools to guide analysis of spatial uncertainty pat...
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Deepanjal Shrestha, Tan Wenan, Deepmala Shrestha, Neesha Rajkarnikar and Seung-Ryul Jeong
This study introduces a data-driven and machine-learning approach to design a personalized tourist recommendation system for Nepal. It examines key tourist attributes, such as demographics, behaviors, preferences, and satisfaction, to develop four sub-mo...
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Su-Hoon Choi, So-Yeon Park, Ung Yang, Beomseon Lee, Min-Soo Kim and Sang-Hyun Lee
Typhoons, which are a common natural disaster in Korea, have seen a rapid increase in annual economic losses over the past decade. The objective of this study was to utilize historical crop insurance records to predict fruit drop rates caused by typhoons...
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Aibing Jin, Prabhat Basnet and Shakil Mahtab
In deep engineering, rockburst hazards frequently result in injuries, fatalities, and the destruction of contiguous structures. Due to the complex nature of rockbursts, predicting the severity of rockburst damage (intensity) without the aid of computer m...
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Zhu Liang, Weiping Peng, Wei Liu, Houzan Huang, Jiaming Huang, Kangming Lou, Guochao Liu and Kaihua Jiang
Shallow landslides pose serious threats to human existence and economic development, especially in the Himalayan areas. Landslide susceptibility mapping (LSM) is a proven way for minimizing the hazard and risk of landslides. Modeling as an essential step...
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Surabhi Upadhyay, Priya Silwal, Rajaram Prajapati, Rocky Talchabhadel, Sandesh Shrestha, Sudeep Duwal and Hanik Lakhe
High spatio-temporal resolution and accurate long-term rainfall estimates are critical in sustainable water resource planning and management, assessment of climate variability and extremes, and hydro-meteorology-related water system decisions. The recent...
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Athanasios Davvetas, Iraklis A. Klampanos, Spiros Skiadopoulos and Vangelis Karkaletsis
Evidence transfer for clustering is a deep learning method that manipulates the latent representations of an autoencoder according to external categorical evidence with the effect of improving a clustering outcome. Evidence transfer?s application on clus...
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Qin Jiang, Weiyue Li, Jiahong Wen, Can Qiu, Weiwei Sun, Qilin Fang, Ming Xu and Jianguo Tan
Satellite-based rainfall products have extensive applications in global change studies, but they are known to contain deviations that require comprehensive verification at different scales. In this paper, we evaluated the accuracies of two high-resolutio...
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Franklin Javier Paredes Trejo,Humberto Álvarez Barbosa,Marcos A. Peñaloza-Murillo,Maria Alejandra Moreno,Asdrubal Farias
Pág. 323 - 342
Satellite-derived rainfall products are useful for both drought and environmental monitoring, and they also allow for tackling the problem of sparse, unevenly distributed and erratic rain gauge observations provided their accuracy is well known. Venezuel...
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