College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi, 830017, China.
College of Geography and Environmental Sciences, Zhejiang Normal University, Jinhua, 321004, China.
Environ Sci Pollut Res Int. 2023 Jun;30(30):75511-75531. doi: 10.1007/s11356-023-27702-x. Epub 2023 May 24.
This study aims to understand the factors and mechanisms influencing the spatio-temporal changes of fractional vegetation cover (FVC) in the northern slopes of the Tianshan Mountains. The MOD13Q1 product data between June and September (peak of plants growing) during the 2001-2020 period was incorporated into the pixel dichotomy model to calculate the vegetation cover changes. Then, the principal component analysis method was used to identify the primary driving factors affecting the change in vegetation cover from the natural, human, and economic perspectives. Finally, the partial correlation coefficients of FVC with temperature and precipitation were further calculated based on the pixel scale. The findings indicate that (1) FVC in the northern slopes of the Tianshan Mountains ranged from 0.37 to 0.47 during the 2001-2020 period, with an obvious inter-annual variation and an overall upward trend of about 0.4484/10 a. Although the vegetation cover had some changes over time, it was generally stable, and the area of strong variation only accounted for 0.58% of the total. (2) The five grades of vegetation cover were distributed spatially similarly, but the area-weighted gravity center for each vegetation class shifted significantly. The FVC under different land use/land cover types and elevations was obviously different, and as elevation increased, vegetation coverage presented a trend of a "∩"-shape change. (3) According to the results of principal component analysis, human activities, economic growth, and natural climate were the main driving factors that caused the changes in vegetation cover, and the cumulative contribution of the three reached 89.278%. In addition, when it came to climatic factors, precipitation had a greater driving force on the vegetation cover change, followed by temperature and sunshine hours. (4) Overall, precipitation and temperature were correlated positively with FVC, with the average correlation coefficient values of 0.089 and 0.135, respectively. Locally, the correlations vary greatly under different LULC and altitudes. This research can provide some scientific basis and reference for the vegetation evolution pattern and ecological civilization construction in the region.
本研究旨在了解天山北坡植被覆盖度(FVC)时空变化的影响因素和机制。利用 2001-2020 年 6-9 月(植物生长高峰期)的 MOD13Q1 产品数据,采用像元二分模型计算植被覆盖变化,运用主成分分析法从自然、人为和经济角度识别影响植被覆盖变化的主要驱动因素,进一步基于像元尺度计算 FVC 与温度和降水的偏相关系数。结果表明:(1)2001-2020 年天山北坡 FVC 范围为 0.37-0.47,年际变化明显,总体呈上升趋势,约为 0.4484/10a。植被覆盖虽然随时间有一定变化,但总体较稳定,强变化面积仅占总面积的 0.58%。(2)植被覆盖度五级等级空间分布相似,但各植被类型面积加权重心发生明显位移。不同土地利用/土地覆被类型和海拔下的 FVC 明显不同,随着海拔升高,植被覆盖度呈“∩”型变化趋势。(3)主成分分析结果表明,人为活动、经济增长和自然气候是引起植被覆盖变化的主要驱动因素,三者的累积贡献率达到 89.278%。此外,就气候因素而言,降水对植被覆盖变化的驱动力更大,其次是温度和日照时数。(4)总体而言,降水和温度与 FVC 呈正相关,平均相关系数分别为 0.089 和 0.135。局部来看,不同土地利用/土地覆被和海拔下的相关性差异较大。本研究可为该区域植被演变模式和生态文明建设提供一定的科学依据和参考。