Detecting Spatially Non-Stationary between Vegetation and Related Factors in the Yellow River Basin from 1986 to 2021 Using Multiscale Geographically Weighted Regression Based on Landsat

Abstract

As an important ecological barrier in northern China, the ecological environment of the Yellow River Basin (YRB) has been greatly improved in recent decades. However, due to spatially non-stationarity, the contribution of human activities and natural factors to vegetation restoration may exhibit different coupling effects in various areas. In this paper, the Normalized Difference Vegetation Index (NDVI) of the YRB from 1986 to 2021 was used as the dependent variable, and terrain, meteorological, and socioeconomic factors were used as independent variables. With the help of Multiscale Geographically Weighted Regression (MGWR), which could handle the scale difference well, combined with Ordinary Least Squares (OLS) and traditional Geographically Weighted Regression (GWR), the spatial non-stationary relationship between vegetation and related factors was discussed. The results showed that: (1) The vegetation was subject to fluctuating changes from 1986 to 2021, mainly improving, with a growth rate of 0.0018/year; the spatial distribution pattern of vegetation in the basin was high in the southeast and low in the northwest. (2) Compared with the OLS and GWR, the MGWR could better explain the relationship between vegetation and various factors. (3) The response scale of vegetation and related factors was significantly variant, and this scale changed with time. The effect scale of terrain factor is lower than climate and social factors. (4) There was obvious spatial heterogeneity in the effects of various influencing factors on vegetation. The vegetation of the upstream was mainly positively affected by mean annual temperature (coefficients ∈ [1.507, 1.784]); while potential evapotranspiration was the dominant factor of vegetation in the middle and lower reaches of the basin (coefficients ∈ [−1.724, −1.704]); it was worth noting that the influence of social factors on vegetation was relatively small. This study deeply explores the spatial non-stationarity of vegetation and various related factors, thereby revealing the evolution law of vegetation pattern and providing scientific support for monitoring and improving the ecological environment quality of the YRB.

Detection and Attribution of Vegetation Dynamics in the Yellow River Basin Based on Long-Term Kernel NDVI Data

“…Different conditions of water, heat, and light have shaped the spatial variability of vegetation landscapes in the YRB [71]. Water availability is the primary limit to vegetation growth in the YRB since most of it features arid and semi-arid climates [72,73].…”

The Response of Carbon Storage to Multi-Objective Land Use/Cover Spatial Optimization and Vulnerability Assessment

“…The influencing values from large to small are altitude, nighttime light, evapotranspiration, slope, precipitation (with a decline from the southeast to northwest), SSD, etc. Flat terrain, fertile soil, abundant land resources, and favorable hydrothermal properties in the middle and lower reaches of the YRB make it a crucial agricultural zone and a major source of commodity grain production in China [47]. Nighttime light, precipitation, evapotranspiration, SSD, and altitude mainly promote cropland's decline.…”

Human activities significantly impact China’s net primary production variation from 2001 to 2020

“…Moreover, the interactions between drivers were not profoundly explored. We will attempt to use a combination of machine learning and geographically weighted regression (Wang et al, 2022a) to gain a deeper understanding of the mechanisms behind NPP variation by depicting the interactions between multiple factors more accurately.…”