Flood-drought shifts monitoring on arid Xinjiang, China using a novel machine learning based algorithm

Flood-drought shifts monitoring on arid Xinjiang, China using a novel machine learning based algorithm

This study addresses the growing challenges of climate extremes and their impact on flood-drought shifts in Xinjiang, China, a region highly sensitive to climate variations. While existing classification models such as logistic regression (LR), support vector machines (SVMs), and geographically weig...

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Bibliographic Details
Main Authors: Sulei Naibi, Anming Bao, Ye Yuan, Jiayu Bao, Rafiq Hamdi, Tao Yu, Xiaoran Huang, Ting Wang, Tao Li, Jingyu Jin, Gang Long, Piet Termonia
Format: Article
Language:English
Published: Elsevier 2025-05-01
Series:Ecological Informatics
Subjects:
Climate extremes
Classification
Spatial nonstationarity
Flood-drought index
Online Access:http://www.sciencedirect.com/science/article/pii/S1574954125000391
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