[1]YUE Meng,GENG Guangpo,WANG Tao,et al.Spatiotemporal Variation of Vegetation NDVI and Its Driving Factors in the Shaanxi Section of the Yellow River Basin from 2000 to 2019[J].Research of Soil and Water Conservation,2023,30(02):238-246,255.[doi:10.13869/j.cnki.rswc.2023.02.022]
Copy
Spatiotemporal Variation of Vegetation NDVI and Its Driving Factors in the Shaanxi Section of the Yellow River Basin from 2000 to 2019
Research of Soil and Water Conservation[ISSN 1005-3409/CN 61-1272/P] Volume:
30
Number of periods:
2023 02
Page number:
238-246,255
Column:
Public date:
2023-03-10
- Title:
- Spatiotemporal Variation of Vegetation NDVI and Its Driving Factors in the Shaanxi Section of the Yellow River Basin from 2000 to 2019
- Keywords:
- vegetation variations; climate change; human activities; residual analysis; Shaanxi section of the Yellow River Basin
- CLC:
- Q948
- DOI:
- 10.13869/j.cnki.rswc.2023.02.022
- Abstract:
- Vegetation is an important component of the terrestrial ecosystem, and studying the rules of vegetation change and its driving factors is helpful to strengthen the ecological protection and sustainable development of regional vegetation. Based on the SPOT NDVI and meteorological data, spatiotemporal characteristics of vegetation NDVI change and its driving factors in the Shaanxi section of the Yellow River Basin from 2000 to 2019 were analyzed by trend analysis, partial correlation analysis and residual analysis. The results are as follows.(1)from 2000 to 2019, the vegetation NDVI in the Shaanxi section of the Yellow River Basin showed the significant increase trend at a rate of 0.008 6/a; the NDVI growth rates in different regions decreased in the order: northern Shaanxi(0.010 9/a)>Guanzhong(0.005 3/a), and the NDVI growth rates in different land use types decreased in the order: grassland(0.011/a)>cropland(0.008 1/a)>forest(0.007 8/a);(2)the proportion of area with an increasing trend of vegetation NDVI accounted for 86.19%, of which the proportion of area with a significant increase was 81.90%; the proportion of area with the increased NDVI in different regions decreased in the order: northern Shaanxi(91.87%)>Guanzhong(66.91%), and the proportion of area with the increased NDVI in different land use types decreased in the order: forest(97.48%)>grassland(90.38%)>cropland(69.78%);(3)90.24% of the regional vegetation NDVI was positively correlated with annual precipitation, and 66.3% of the regional vegetation NDVI was positively correlated with the annual mean temperature;(4)the changes of vegetation NDVI in the study area were affected by climate change, human activities and their combined effects, accounting for 5.65%, 73.11% and 21.24%, respectively; among them, the proportion of human activity area decreased in the order: northern Shaanxi(79.88%)>Guanzhong(55.49%), grassland(85.2%)>cropland(73%)>forest(59.67%). Overall, the vegetation activity in the Shaanxi section of the Yellow River Basin was significantly enhanced from 2000 to 2019. Precipitation had a greater impact on vegetation than temperature in the study area. Human activity was the main driving forces for vegetation change in the study area. These conclusions can provide an important reference for ecological construction and vegetation restoration in the study area.
- References:
-
[1] 金凯,王飞,韩剑桥,等.1982—2015年中国气候变化和人类活动对植被NDVI变化的影响[J].地理学报, 2020,75(5):75-88.
[2] 陈晨,王义民,黎云云,等.黄河流域1982—2015年不同气候区植被时空变化特征及其影响因素[J].长江科学院院报,2022,39(2):56-62,81.
[3] 丁海勇,丁昕玮.基于SPOT_NDVI的甘肃省植被覆盖变化及其与气候、地形因子的关系[J].长江流域资源与环境,2020,29(12):2665-2678.
[4] 张亮,丁明军,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.
[5] 李晶,刘乾龙,刘鹏宇.1998—2018年呼伦贝尔市植被覆盖度时空变化及驱动力分析[J].生态学报,2022,42(1):220-235.
[6] 秦格霞,芦倩,孟治元,等.1982—2015年中国北方草地NDVI时空动态及其对气候变化的响应[J].水土保持研究,2021,28(1):101-108,117.
[7] 陈婷,夏军,邹磊,等.白洋淀流域NDVI时空演变及其对气候变化的响应[J].资源科学,2021,43(6):1248-1259.
[8] Lamchin M, Wang S W, Lim C H, et al. Understanding global spatio-temporal trends and the relationship between vegetation greenness and climate factors by land cover during 1982—2014[J]. Global Ecology and Conservation, 2020,24:e01299.
[9] Yao N, Li Y, Lei T, et al. Drought evolution, severity and trends in mainland China over 1961—2013[J]. Science of the Total Environment, 2018,616:73-89.
[10] Zhao A, Zhang A, Liu J, et al. Assessing the effects of drought and ‘Grain for Green' Program on vegetation dynamics in China's Loess Plateau from 2000 to 2014[J]. Catena, 2019,175:446-455.
[11] 彭苏萍,毕银丽.黄河流域煤矿区生态环境修复关键技术与战略思考[J].煤炭学报,2020,45(4):1211-1221.
[12] 刘海,刘凤,郑粮.气候变化及人类活动对黄河流域植被覆盖变化的影响[J].水土保持学报,2021,35(4):143-151.
[13] 张静,杜加强,盛芝露,等.1982—2015年黄河流域植被NDVI时空变化及影响因素分析[J].生态环境学报,2021,30(5):929-937.
[14] 孙高鹏,刘宪锋,王小红,等.2001—2020年黄河流域植被覆盖变化及其影响因素[J].中国沙漠,2021,41(4):205-212.
[15] 张君,延军平.1982—2013年陕西不同植被类型NDVI变化特征分析[J].干旱区资源与环境,2017,31(4):86-92.
[16] 郑勇,杨武年,刘冲,等.川西高原近20 a植被覆盖变化遥感动态监测及驱动力分析[J].遥感技术与应用,2020,35(6):1447-1456.
[17] 卫宇婷.山西省1986—2015年植被覆盖变化分析及其对气候因子的响应[D].太原:山西农业大学,2018.
[18] Wang G, Wang P, Wang T Y, et al. Contrasting changes in vegetation growth due to different climate forcings over the last three decades in the selenga-baikal basin[J]. Remote Sensing, 2019, 11(4): 426.
[19] 田智慧,任祖光,魏海涛.2000—2020年黄河流域植被时空演化驱动机制[J].环境科学,2022,43(2):743-751.
[20] Jiang L, Bao A, Guo H, 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.
[21] 杨钰杰,白晓永,谭秋,等.1982—2015年“一带一路”地区NDVI时空演变规律及其影响因素[J].山地学报,2020,38(2):252-264.
[22] 鲁亚楠,姚顺波,邓元杰,等.陕北地区土地利用及景观格局变化对生态服务价值的影响:基于退耕还林(草)背景[J].中国农业资源与区划,2019,40(11):180-192.
[23] 何云玲,余岚,屈新星,等.云南喀斯特关键带植被时空变化特征及气候与人为影响因子解析[J].长江流域资源与环境,2021,30(2):439-447.
[24] 董镱,尹冬勤,李渊,等.黄土高原植被的时空变化及其驱动力分析研究[J].中国农业大学学报,2020,25(8):120-131.
[25] 殷崎栋,柳彩霞,田野.基于MODIS NDVI数据的陕西省植被绿度时空变化及人类活动影响[J].生态学报,2021,41(4):1571-1582.
[26] Zhu Z, Bi J, Pan Y, et al. Global data sets of vegetation leaf area index(LAI)3g and fraction of photosynthetically active radiation(FPAR)3g derived from global inventory modeling and mapping studies(GIMMS)normalized difference vegetation index(NDVI3g)for the period 1981 to 2011[J]. Remote Sensing, 2013,5(2):927-948.
[27] Zhao A Z, Zhang A B, Liu X F, et al. Spatiotemporal changes of normalized difference vegetation index(NDVI)and response to climate extremes and ecological restoration in the Loess Plateau, China[J]. Theoretical and Applied Climatology,2018,132:555-567.
[28] Geng G, Yang R, Liu L. Downscaled solar-induced chlorophyll fluorescence has great potential for monitoring the response of vegetation to drought in the Yellow River Basin, China: Insights from an extreme event[J]. Ecological Indicators, 2022,138:108801.
[29] Piao S, Yin G, Tan J, et al. Detection and attribution of vegetation greening trend in China over the last 30 years[J]. Global Change Biology, 2015,21(4):1601-1609.
[30] 杨睿,耿广坡,周洪奎,等.基于SPEI_PM指数的渭河流域气象干旱时空演变特征[J].中国农业气象,2021,42(11):962-974.
- Similar References:
Memo
-
Last Update:
2023-03-10