Vegetation dynamic analysis based on multisource remote sensing data in the east margin of the Qinghai-Tibet Plateau, China

Abstract

This study focuses on the vegetation dynamic caused by global environmental change in the eastern margin of the Qinghai-Tibet Plateau (EMQTP). The Qinghai–Tibet Plateau (QTP) is one of the most sensitive areas responding to global environmental change, particularly global climate change, and has been recognized as a hotspot for coupled studies on changes in global terrestrial ecosystems and global climates. An important component of terrestrial ecosystems, vegetation dynamic has become a key issue in global environmental change, and numerous case studies have been conducted on vegetation dynamic trends using multi-source data and multi-scale methods across different study periods. The EMQTP is regarded as a transitional area located between the QTP and the Sichuan basin, and has special geographical and climatic conditions. Although this area is ecologically fragile and sensitive to climate change, few studies about vegetation dynamics have been carried out in this area. Thus, in this study, we used long-term series datasets of GIMMS 3g NDVI and VGT/PROBA-V NDVI to analyze the vegetation dynamics and phenological changes from 1982 to 2018. Validation was performed based on Landsat NDVI and Vegetation Index & Phenology (VIP) data. The results reveal that the year 1998 was a vital turning point in the start of growing season (SGS) in vegetation ecosystems. Before this turning point, the SGS had an average slope of 9.2 days/decade, and after, the average slope was 3.9 days/decade. The length of growing season (LGS) was slightly prolonged between 1982 to 2015. Additionally, the largest national alpine wetland grassland experienced significant vegetation degradation; in autumn, the degraded area accounted for 63.4%. Vegetation degradation had also appeared in the arid valleys of the Yalong River and the Jinsha River. Through validation analysis, we found that the main causes of vegetation degradation are the natural degradation of wetland grassland and human activities, specifically agricultural development and residential area expansion.

Temporal Pattern Analysis of Cropland Phenology in Shandong Province of China Based on Two Long-Sequence Remote Sensing Data

“…Land-use change may also be an important explanation for the greening trend in some regions [30][31][32]. Unlike the present study, a clear inflection point of the greening trend was also found in the eastern part of the Tibetan Plateau, which may be due to the different vegetation types and altitudes [33]. Seasonally, both datasets showed a comparable number of growing cycles in most regions but with diverse amplitudes.…”

Evaluating Natural Ecological Land Change in Function-Oriented Planning Regions Using the National Land Use Survey Data from 2009 to 2018 in China

“…Comparing with Figure 1, it could be seen that the forest land de-creased by 6.53% and 6.37% from 2009 to 2018 KDZs around Zhengzhou and APZs around Jinan and Zhengzhou, respectively. Interestingly, forest land area had significantly decreased in KEFZs around Lhasa which was always ecologically fragile [31]. This was due to the fact that the total area of the forest land was small, and a few changes would cause the overall ratio to change.…”

How Does Spring Phenology Respond to Climate Change in Ecologically Fragile Grassland? A Case Study from the Northeast Qinghai-Tibet Plateau

“…Based on Systeme Probatoire d'Observation de la Terre (SPOT)/normalized difference vegetation index (NDVI) data, Ding et al [12] found that the spatial and temporal distribution of alpine grassland phenology from 1999 to 2009 was closely related to hydrothermal conditions, and the SOS was delayed with the gradual deterioration of hydrothermal conditions. Wang et al [13] used Global Inventory Modeling and Mapping Studies (GIMMS)/NDVI and SPOT/NDVI data to analyze vegetation phenology trends on the eastern edge of the Tibetan Plateau and found that the SOS in the region showed an early trend from 1982 to 1998, while a delayed trend was observed from 1999 to 2018. In a small-scale regional study, An et al [14], based on Landsat 7 ETM+ (Enhanced Thematic Mapper Plus) and Landsat 8 OLI (Operational Land Imager) data from 2013 to 2015 along a 2600 km transect in the center of the Tibetan Plateau, investigated how vegetation changes in response to differences in slope aspect and elevation.…”