This study explores the spatio-temporal changes in vegetation net primary productivity (NPP) across the Beijing-Tianjin-Hebei region based on MOD17A3 data. Univariate linear regression method was employed to analyze the temporal and spatial evolution of vegetation NPP in 20 years (2000-2019). Additionally, this study analyzed the correlation between NPP and climate factors. The results show that vegetation NPP in the Beijing-Tianjin-Hebei region mainly falls within the range of 200-400 gC/(m2·a). The mean and maximum values of NPP exhibited gradual increase from 2000 to 2019, with a peak in both mean and maximum values occurring in 2016 at 385.10 gC/(m2·a) and 908.40 gC/(m2·a), respectively. The area with significantly increased NPP in the region from 2000 to 2019 was found to account for 97.12% of the study area, while the area with NPP decrease mainly occurring in areas surrounding urban centers. Furthermore, the four types of vegetation cover in the region ranking from smallest to largest in terms of NPP mean were as follows: cropland, shrub, grassland, and forest. The study also found that from 2000 to 2019, the stability of NPP in the region was characterized by high-low fluctuations, with lower fluctuations being dominant. Finally, NPP was found to be lowly correlated with the average annual temperature and highly correlated with annual precipitation. The findings can serve as reference for ecological civilization construction, ecological environmental restoration, and management and protection in Beijing-Tianjin-Hebei region.
Key words
net primary productivity (NPP) /
temporal and spatial evolution /
MOD17A3 data /
univariate linear regression /
correlation analysis /
Beijing-Tianjin-Hebei Region
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
References
[1] LIETH H, WHITTAKER R H. Primary Productivity of the Biosphere[M]. New York:Springer-Verlag, 1975.
[2] 张 莎, 袁金国, 张宇佳, 等. 河北省2001—2010年植被NPP时空变化及与气候因子相关性分析[J]. 河北大学学报(自然科学版), 2014, 34(5): 516-523.
[3] 朱利欣, 袁金国. 京津冀地区植被净初级生产力时空分布及其与地形因子的关系[J]. 科技通报, 2019, 35(6): 197-203.
[4] 李 肖, 袁金国, 孟 丹. 河北省2005—2014年植被NPP时空演变及其与气候因子的关系[J]. 水土保持研究, 2018, 25(6): 109-114, 120.
[5] 王 钊, 李登科. 2000—2015年陕西植被净初级生产力时空分布特征及其驱动因素[J]. 应用生态学报, 2018, 29(6): 1876-1884.
[6] 田智慧, 张丹丹, 赫晓慧, 等. 2000—2015年黄河流域植被净初级生产力时空变化特征及其驱动因子[J]. 水土保持研究, 2019, 26(2): 255-262.
[7] 李登科,范建忠,王 娟.基于MOD17A3的陕西省植被NPP变化特征[J].生态学杂志,2011,30(12):2776-2782.
[8] 谢 婷, 纪显德, 徐晓娜, 等. 2000—2014年张家口市植被净初级生产力的时空格局及其与气候的关系[J]. 安徽农业科学, 2019, 47(5): 68-73.
[9] 李登科, 王 钊. 基于MOD17A3的中国陆地植被NPP变化特征分析[J]. 生态环境学报, 2018, 27(3): 397-405.
[10]雷延鹏, 孙智辉, 蒋小莉, 等. 基于MOD17A3的陕北植被净初级生产力变化特征研究[J]. 安徽农业科学, 2017, 45(36): 55-57, 93.
[11]李晓玺, 袁金国, 刘夏菁, 等. 基于MODIS数据的渤海净初级生产力时空变化[J]. 生态环境学报, 2017, 26(5): 785-793.
[12]刘旻霞, 焦 骄, 潘竟虎, 等. 青海省植被净初级生产力(NPP)时空格局变化及其驱动因素[J]. 生态学报, 2020, 40(15): 5306-5317.
[13]孙庆龄, 冯险峰, 肖 潇. 武陵山区植被净第一性生产力的时空格局及其与地形因子的关系[J]. 地球信息科学学报, 2014, 16(6): 915-924.
[14]王 琳, 景元书, 李 琨. 江苏省植被NPP时空特征及气候因素的影响[J]. 生态环境学报, 2010, 19(11): 2529-2533.
[15]贺 倩, 杨雪琴, 戴晓爱. 2010—2015年三江源地区植被净初级生产力变化特征及影响因素分析[J]. raybet体育在线
院报, 2020, 37(5): 59-66.
[16]易 扬, 胡昕利, 史明昌, 等. 基于MODIS NDVI的长江中游区域植被动态及与气候因子的关系[J]. 生态学报, 2021, 41(19): 7796-7807.
PDF(34617 KB)
