An Enhanced Interval Type-2 Fuzzy C-Means Algorithm for Fuzzy Time Series Forecasting of Vegetation Dynamics: A Case Study from the Aksu Region, Xinjiang, China

Accurate prediction of the Normalized Difference Vegetation Index (NDVI) is crucial for regional ecological management and precision decision-making. Existing methodologies often rely on smoothed NDVI data as ground truth, overlooking uncertainties inherent in data acquisition and processing. Fuzzy...

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Bibliographic Details
Published in:	Land (Basel) Vol. 14; no. 6; p. 1242
Main Authors:	Chen, Yongqi, Liu, Li, Cao, Jinhua, Wang, Kexin, Li, Shengyang, Yin, Yue
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 01.06.2025
Subjects:	Accuracy Algorithms Arid zones Climate change Clustering Comparative analysis Cost analysis Data acquisition Data processing Datasets Decision making Desertification ecological monitoring Environmental aspects Environmental management Environmental restoration Forecasting Forecasts and trends Fuzzy algorithms Fuzzy logic Fuzzy sets Fuzzy systems fuzzy time series modeling interval type-2 fuzzy C-means clustering Land use Measurement NDVI Normalized difference vegetative index Parameter uncertainty Precipitation Prediction models Remote sensing Statistical models Time series Time-series analysis Trends Vegetation vegetation dynamic Vegetation dynamics China
ISSN:	2073-445X, 2073-445X
Online Access:	Get full text
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