Our findings reveal: (1) temperature series become stationary after first-order differencing, validating their suitability for time series modeling; (2) both SARIMA and O-U models produce predictions closely aligned with observed data; (3) SARIMA exhibits lower forecasting errors for. .
Our findings reveal: (1) temperature series become stationary after first-order differencing, validating their suitability for time series modeling; (2) both SARIMA and O-U models produce predictions closely aligned with observed data; (3) SARIMA exhibits lower forecasting errors for. .
y zone supporting the sustained growth of economy 100 of the nation, takes the lead in the urbanization development. Meanwhile due to 101 differences in natural resources and economic development, there are obvious temporal 102 and spatial differences in the urbanization process of urban. .
National Engineering Center of Eco-Environments in Pan-Yangtze Basin, Wuhan 430014, China YANGTZE Eco-Environment Engineering Research Center, China Three Gorges Corporation, Wuhan 430014, China State-Owned Assets Supervision and Administration Commission of the State Council, Social Responsibility. .
We examined atmospheric humidity changes by trend and change point analyses of humidity and heat content indicators of three representative urban agglomerations in the Yangtze River Economic Belt, China during 1965–2017, and found the evident urban dry island (UDI) effects which are characterized. .
In the Yangtze River Economic Belt, climate variability significantly affects sectors such as agriculture, energy, and related industries, making accurate temperature forecasting essential. This study develops and compares Seasonal Autoregressive Integrated Moving Average (SARIMA) and. .
The People’s Republic of China (PRC), in its Fourteenth Five-Year Plan, 2021–2025, promotes rural vitalization and ecological civilization as a green development model and identifies development of the Yangtze River Economic Belt (YREB) as a high priority. The YREB crosses nine provinces and two. .
This study analyzes the spatiotemporal dynamics of LST and the Kernel Normalized Difference Vegetation Index (KNDVI) in 11 provinces along the Yangtze River and their response to climate change based on MODIS Terra satellite data from 2000 to 2020. The linear regression showed a significant KNDVI.
