Analysis of NDVI changes and driving factors in Taihang mountain area from 2000 to 2015

doi:10.14088/j.cnki.issn0439-8114.2020.09.014

Abstract

Abstract: This research was based on MODIS NDVI data from 2000 to 2015, combined with meteorological, land use and other relevant data of the same period. According to the NDVI change data and land use type change data obtained by relevant calculations, the NDVI change data were reversely studied to find the driving factors that affect NDVI change. The results showed that, from 2000 to 2015, the overall vegetation coverage in the study area had been improved, with an average growth rate of 0.007 5/a. The driving factor for the increase of NDVI was the promotion effect of meteorological factors on vegetation growth. Human activities directly led to the increase of NDVI within the cultivated land by making the cultivated land crops grow more vigorous. Human activities played a role in promoting vegetation in natural areas far from cities, such as Taihang mountain afforestation project, farmland conversion project, rural population transfer to cities and other ecological protection measures, which had a positive impact on the change of NDVI in grassland, woodland and water area. The driving factor of NDVI reduction area was the decrease of cultivated land and grassland area around the city and the increase of urban area in Taihang mountain area. Human activities weaken the vegetation growth in the city and its surrounding areas.

Key words: NDVI, ArcGIS, vegetation coverage, climatic factors, human activities, Taihang mountain area

CLC Number:

Q948.1

LI Xin-yuan, WANG Li, JING Hai-tao, FAN Chen-yu, YU Xun. Analysis of NDVI changes and driving factors in Taihang mountain area from 2000 to 2015[J]. HUBEI AGRICULTURAL SCIENCES, 2020, 59(9): 70-76.

References

[1] 杨菊,熊康宁,肖时珍. 赤水丹霞地貌区植被覆盖度时空变化分析[J]. 人民长江,2018,49(18):38-44.
[2] 唐见,曹慧群,陈进. 生态保护工程和气候变化对长江源区植被变化的影响量化[J]. 地理学报,2019,74(1):76-86.
[3] WU D H, ZHAO X, LIANG S L, et al.Time-lag effects of global vegetation responses to climate change[J]. Global change biology,2015,21(9):3520-3531.
[4] TIETJEZ B, SCHLAEPFER D R, BRADFORD J B, et al.Climate change-induced vegetation shifts lead to more ecological droughts despite projected rainfall increases in many global temperate drylands[J]. Global change biology, 2017, 23(7):2743-2754.
[5] CHEN B X, ZHANG X Z, TAO J, et al.The impact of climate change and anthropogenic activities on alpine grassland over the Qinghai-Tibet Plateau[J]. Agricultural and forest meteorology, 2014, 189: 11-18.
[6] 孙庆龄,李宝林,李飞,等. 三江源植被净初级生产力估算研究进展[J]. 地理学报,2016,71(9):1596-1612.
[7] JIANG L L,JIAPAER G,BAO A,et al.Vegetation dynamics and responses to climate change and human activities in Central Asia[J]. Science of the total environment, 2017,599:967-980.
[8] 李薇,谈明洪. 太行山区不同坡度NDVI变化趋势差异分析[J]. 中国生态农业学报,2017,25(4):509-519.
[9] 李晓荣,高会,韩立朴,等. 太行山区植被NPP时空变化特征及其驱动力分析[J]. 中国生态农业学报,2017,25(4):498-508.
[10] 胡实,赵茹欣,贾仰文,等. 中国典型山地植被垂直地带性特征及其影响要素[J]. 自然杂志,2018,40(1):12-16.
[11] 张亮,丁明军,张华敏,等. 1982—2015年长江流域植被覆盖度时空变化分析[J]. 自然资源学报,2018,33(12):2084-2097.
[12] 薛朝浪,赵宇鸾,魏小芳,等. 基于CCA的太行山区土地利用变化驱动机制分析[J]. 贵州师范大学学报,2019,37(1):93-103.
[13] 李苗苗,吴炳方,颜长珍,等. 密云水库上游植被覆盖度的遥感估算[J]. 资源科学,2004(4):153-159.
[14] 江振蓝,荆长伟,李丹,等. 运用Mann-Kendall方法探究地表植被变化趋势及其对地形因子的响应机制——以太湖苕溪流域为例[J]. 浙江大学学报(农业与生命科学版),2011,37(6):684-692.
[15] 罗红霞,戴声佩,刘恩平,等. 2001—2014年海南岛植被覆盖时空变化特征[J]. 水土保持研究,2018,25(5):343-350.
[16] 谷金芝,宫兆宁. 2001—2015年华北平原植被覆盖度时空变化特征及影响因素分析[J]. 测绘与空间地理信息,2018,41(8):47-51.
[17] 徐建华. 现代地理学中的数学方法[M]. 北京:高等教育出版社,2002.
[18] 李双双,延军平,万佳. 近10年陕甘宁黄土高原区植被覆盖时空变化特征[J]. 地理学报,2012,67(7):960-970.
[19] 刘启兴,董国涛,景海涛,等. 2000—2016年黄河源区植被NDVI变化趋势及影响因素[J]. 水土保持研究,2019,26(3):86-92.