Spatial and Temporal Evolutionary Characteristics of Vegetation in Different Geomorphic Zones of Loess Plateau and Its Driving Factor Analysis

Abstract

Based on MODIS NDVI and a meteorological dataset, this study analyzed the spatial and temporal variation characteristics of vegetation cover in different geomorphic zones of Loess Plateau (LP) from 2000 to 2020 with trend analysis, partial correlation, residual analysis and the CA–Markov method and discussed the driving factors. The research results show that: (1) There are spatial differences in vegetation coverage in different geomorphic regions. The Loess Hills and Forests zone (LF) exhibits the highest coverage, with a multi-year average of 86.64%, and the Arid Grassland (AG) has the poorest vegetation with only 8.53%. Overall, there has been significant improvement in vegetation coverage over the past two decades, although certain geomorphic zones, particularly the Highland Steppe zone (HS) and Alluvial Plains zone (AP), show signs of degradation. (2) Relative humidity has the greatest impact on vegetation among the three climate factors, i.e., relative humidity, precipitation and temperature. Relative humidity predominantly promotes vegetation in all geomorphic zones. Temperature generally inhibits vegetation growth, except in the Wind Sandy zone (WA) and AG. The impact of precipitation on vegetation depends on the region. A lag effect is observed, with temperature and humidity showing a one-month lag and precipitation showing a two-month lag on vegetation response. (3) Human activities play a crucial role in promoting vegetation, particularly in the WA zone, in which the percentage of area where human activities contribute to vegetation has changed from 13.80% to 86.85%, an increase of 73.05%, while the HS experiences an inhibitory effect due to overgrazing and water resource overutilization. Similarly, the AP zone’s vegetation growth is hindered by urban development and land use changes. (4) Land use change significantly impacts vegetation dynamics on the LP. Over the past two decades, the area of forest lawn increased by 122,800 km2, which is 1.5 times more than the area of reduction. However, conversion to building land has hindered vegetation growth in certain regions. A comprehensive strategy is required to conserve land resources and promote healthy vegetation growth on the LP.

Vegetation–Lake–Sand Landscape of Northeast China Sandy Land between 1980 and 2022: Pattern, Evolution, and Driving Forces

“…Affected by various natural conditions such as time and region, the NDV I needs to be used to determine the NDV I soil and NDV I veg values of different images. By analyzing the NDV I data of Landsat series images, combined with the actual situation of the pine sand and the cumulative probability distribution table of the NDV I values, the confidence value was 0.5% [46].…”

Temporal and Spatial Variations in the Normalized Difference Vegetation Index in Shanxi Section of the Yellow River Basin and Coal Mines and Their Response to Climatic Factors

“…The Hurst Index can assume three different values: if 0.5 < H < 1, it indicates that the time series is a persistent sequence, characterized by long-term correlations; if H = 0.5, it signifies that the NDVI time series is a random sequence, lacking long-term correlations; if 0 < H < 0.5, it suggests that the NDVI time series exhibits anti-persistence [36]. The closer the H value is to 0, the stronger its anti-persistence; the closer to 1, the more persistent it is.…”