[1]Li Zichuang,Dong Guotao,Yao Nan.Analysis of Spatiotemporal Variations and Driving Forces of NDVI in the Middle Reaches of Yellow River During 1982—2015[J].Research of Soil and Water Conservation,2024,31(02):202-210.
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Analysis of Spatiotemporal Variations and Driving Forces of NDVI in the Middle Reaches of Yellow River During 1982—2015
Research of Soil and Water Conservation[ISSN 1005-3409/CN 61-1272/P] Volume:
31
Number of periods:
2024 02
Page number:
202-210
Column:
Public date:
2024-03-20
- Title:
- Analysis of Spatiotemporal Variations and Driving Forces of NDVI in the Middle Reaches of Yellow River During 1982—2015
- CLC:
- Q948.1
- DOI:
- -
- Abstract:
- [Objective] The aims of this study are to explore the spatiotemporal changes of NDVI in the middle reaches of the Yellow River, to clarify the impact and driving forces of natural and human factors on NDVI changes, and to provide scientific basis for ecological protection and development. [Methods] Based on the AVHRR GIMMS NDVI dataset,linear regression analysis,Mann-Kendall test and Geodetector-mode were used to analyze the spatiotemporal evolution characteristics of vegetation NDVI in the middle reaches of Yellow River from 1982 to 2015. The driving forces of natural and human factors affecting vegetation NDVI were also analyzed. [Results] From 1982 to 2015,the NDVI of the middle reaches of Yellow River showed upward trend,with spatial distribution of high level in the southeast and low level in the northwest. The improved vegetation coverage area reached to 70.79%,with a significant improvement area of 49.2%. Annual precipitation was the dominant factor affecting NDVI changes in the middle reaches of Yellow River,and factors such as vegetation type,geomorphic type,land use type and soil type could also explain the vegetation cover status in the middle reaches of Yellow River. The impact of natural factors on vegetation change was much higher than that of human factors,and the result of factor interaction was a dual factor enhancement or non-linear enhancement. [Conclusion] The NDVI of the vegetation in the middle reaches of the Yellow River is mainly affected by annual precipitation, and the vegetation had improved significantly during the 34-year period under the interaction of natural and human factors, and more attention should be paid to the influence of human activities on the vegetation cover in the future.
- References:
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[1] Gong Z N, Zhao S Y, Gu J Z. Correlation analysis between vegetation coverage and climate drought conditions in North China during 2001—2013[J]. Journal of Geographical Sciences, 2017,27(2):143-160.
[2] 赵杰,杜自强,武志涛,等.中国温带昼夜增温的季节性变化及其对植被动态的影响[J].地理学报,2018,73(3):395-404.
Zhao J, Du Z Q, Wu Z T, et al. Seasonal variations of day and nighttime warming and their effects on vegetation dynamics in China's temperate zone[J]. Acta Geographica Sinica, 2018,73(3):395-404.
[3] Parmesan C, Yohe G. A globally coherent fingerprint of climate change impacts across natural systems[J]. Nature, 2003,421(6918):37-42.
[4] Pettorelli N, Vik J O, Mysterud A, et al. Using the satellite-derived NDVI to assess ecological responses to environmental change[J]. Trends in Ecology & Evolution, 2005,20(9):503-510.
[5] Zhao L, Dai A G, Dong B. Changes in global vegetation activity and its driving factors during 1982—2013[J]. Agricultural and Forest Meteorology, 2018,249:198-209.
[6] 苗正红,刘志明,王宗明,等.基于MODIS NDVI的吉林省植被覆盖度动态遥感监测[J].遥感技术与应用,2010,25(3):387-393.
Miao Z H, Liu Z M, Wang Z M, et al. Dynamic monitoring of vegetation fraction change in Jilin Province based on MODIS NDVI[J]. Remote Sensing Technology and Application, 2010,25(3):387-393.
[7] Camacho-De Coca F, García-Haro F J, Gilabert M A, et al. Vegetation cover seasonal changes assessment from TM imagery in a semi-arid landscape[J]. International Journal of Remote Sensing, 2004,25(17):3451-3476.
[8] 高思琦,董国涛,蒋晓辉,等.黄河源植被覆盖度变化及空间分布自然驱动力分析[J].生态环境学报,2022,31(3):429-439.
Gao S Q, Dong G T, Jiang X H, et al. Analysis of vegetation coverage changes and natural driving forces of spatial distribution in the source region of the Yellow River[J]. Ecology and Environmental Sciences, 2022,31(3):429-439.
[9] 聂桐,董国涛,蒋晓辉,等.榆林地区植被时空分异特征及其影响因素研究[J].生态环境学报,2022,31(1):26-36.
Nie T, Dong G T, Jiang X H, et al. Spatio-temporal variations and influencing factors of vegetation in Yulin[J]. Ecology and Environmental Sciences, 2022,31(1):26-36.
[10] 王劲峰,徐成东.地理探测器:原理与展望[J].地理学报,2017,72(1):116-134.
Wang J F, Xu C D. Geodetector: Principle and prospective[J]. Acta Geographica Sinica, 2017,72(1):116-134.
[11] 肖建勇,王世杰,白晓永,等.喀斯特关键带植被时空变化及其驱动因素[J].生态学报,2018,38(24):8799-8812.
Xiao J Y, Wang S J, Bai X Y, et al. Determinants and spatial-temporal evolution of vegetation coverage in the Karst critical zone of South China[J]. Acta Ecologica Sinica, 2018,38(24):8799-8812.
[12] Gao S Q, Dong G T, Jiang X H, et al. Quantification of natural and anthropogenic driving forces of vegetation changes in the Three-River Headwater region during 1982—2015 based on Geographical Detector Model[J]. Remote Sensing, 2021,13(20):4175.
[13] Nie T, Dong G T, Jiang X H, et al. Spatio-temporal changes and driving forces of vegetation coverage on the Loess Plateau of Northern Shaanxi[J]. Remote Sensing, 2021,13(4):613.
[14] 王伟,阿里木·赛买提,吉力力·阿不都外力.基于地理探测器模型的中亚NDVI时空变化特征及其驱动因子分析[J].国土资源遥感,2019,31(4):32-40.
Wang Wei, Alim Samat, Jilili Abuduwaili. Geo-detector based spatio-temporal variation characteristics and driving factors analysis of NDVI in Central Asia[J]. Remote Sensing for Land & Resources, 2019.31(4):32-40.
[15] 李金珂,杨玉婷,张会茹,等.秦巴山区近15年植被NPP时空演变特征及自然与人为因子解析[J].生态学报,2019,39(22):8504-8515.
Li J K, Yang Y T, Zhang H R, et al. Spatio-temporal variations of net primary productivity and its natural and human factors analysis in Qinling-Daba Mountains in the past 15 years[J]. Acta Ecologica Sinica, 2019,39(22):8504-8515.
[16] 祝聪,彭文甫,张丽芳,等.2006—2016年岷江上游植被覆盖度时空变化及驱动力[J].生态学报,2019,39(5):1583-1594.
Zhu C, Peng W F, Zhang L F, et al. Study of temporal and spatial variation and driving force of fractional vegetation cover in upper reaches of Minjiang River from 2006 to 2016[J]. Acta Ecologica Sinica, 2019,39(5):1583-1594.
[17] 裴志林,杨勤科,王春梅,等.黄河上游植被覆盖度空间分布特征及其影响因素[J].干旱区研究,2019,36(3):546-555.
Pei Z L, Yang Q K, Wang C M, et al. Spatial distribution of vegetation coverage and its affecting factors in the upper reaches of the Yellow River[J]. Arid Zone Research, 2019,36(3):546-555.
[18] 彭文甫,张冬梅,罗艳玫,等.自然因子对四川植被NDVI变化的地理探测[J].地理学报,2019,74(9):1758-1776.
Peng W F, Zhang D M, Luo Y M, et al. Influence of natural factors on vegetation NDVI using geographical detection in Sichuan Province[J]. Acta Geographica Sinica, 2019,74(9):1758-1776.
[19] 贺振,贺俊平.基于SPOT-VGT的黄河流域植被覆盖时空演变[J].生态环境学报,2012,21(10):1655-1659.
He Z, He J P. Spatio-temporal variation of vegetation cover based on SPOT-VGT in Yellow River Basin [J]. Ecology and Environmental Sciences, 2012,21(10):1655-1659.
[20] 高海东,庞国伟,李占斌,等.黄土高原植被恢复潜力研究[J].地理学报,2017,72(5):863-874.
Gao H D, Pang G W, Li Z B, et al. Evaluating the potential of vegetation restoration in the Loess Plateau[J]. Acta Geographica Sinica, 2017,72(5):863-874.
[21] 贾培培,薛华柱,董国涛,等.黄河河潼区间NDVI变化及其对气候的响应[J].人民黄河,2019,41(4):31-36,41.
Jia P P, Xue H Z, Dong G T, et al. Variations of NDVI and its response to climate in Hekouzhen-Tongguan reach of the Yellow River[J]. Yellow River, 2019,41(4):31-36,41.
[22] 高海东,吴曌.黄河头道拐:潼关区间植被恢复及其对水沙过程影响[J].地理学报,2021,76(5):1206-1217.
Gao H D, Wu Z. Vegetation restoration and its effect on runoff and sediment processes in the Toudaoguai-Tongguan section of the Yellow River [J]. Acta Geographica Sinica, 2021,76(5):1206-1217.
[23] 付含培,王让虎,王晓军.1999—2018年黄河流域NDVI时空变化及驱动力分析[J].水土保持研究,2022,29(2):145-153,162.
Fu H P, Wang R H, Wang X J. Analysis of spatiotemporal variations and driving forces of NDVI in the Yellow River Basin during 1999—2018[J]. Research of Soil and Water Conservation, 2022,29(2):145-153,162.
[24] 刘彦随,李进涛.中国县域农村贫困化分异机制的地理探测与优化决策[J].地理学报,2017,72(1):161-173.
Liu Y S, Li J T. Geographic detection and optimizing decision of the differentiation mechanism of rural poverty in China[J]. Acta Geographica Sinica, 2017,72(1):161-173.
[25] Liu Z Z, Wang H, Li N, et al. Spatial and temporal characteristics and driving forces of vegetation changes in the Huaihe River Basin from 2003 to 2018[J]. Sustainability, 2020,12(6):2198.
[26] Wang J F, Li X H, Christakos G, et al. Geographical detectors-based health risk assessment and its application in the neural tube defects study of the Heshun region, China[J]. International Journal of Geographical Information Science, 2010,24(1):107-127.
[27] 程昌武.黄河流域1982—2015年植被变化及其影响因素分析[D].西安:长安大学,2020.
Cheng C W. Vegetation Dynamics and Its Influential Factors in the Yellow River Basin During 1982 to 2015[D]. Xi'an: Chang'an University, 2020.
[28] 贺振,贺俊平.近32年黄河流域植被覆盖时空演化遥感监测[J].农业机械学报,2017,48(2):179-185.
He Z, He J P. Remote Sensing on spatio-temporal evolution of vegetation cover in the Yellow River Basin during 1982—2013[J].Transactions of the Chinese Society for Agricultural Machinery, 2017,48(2):179-185.
[29] 李晴晴,曹艳萍,苗书玲.黄河流域植被时空变化及其对气候要素的响应[J].生态学报,2022,42(10):4041-4054.
Li Q Q, Cao Y P, Miao S L. Spatio-temporal variation in vegetation coverage and its response to climate factors in the Yellow River Basin, China[J]. Acta Ecologica Sinica, 2022,42(10):4041-4054.
[30] He L, Guo J B, Jiang Q, et al. How did the Chinese Loess Plateau turn green from 2001 to 2020: An explanation using satellite data[J]. Catena, 2022,214:106246.
[31] 信忠保,许炯心,郑伟.气候变化和人类活动对黄土高原植被覆盖变化的影响[J].中国科学D辑:地球科学,2007,37(11):1504-1514.
Xin Z B, Xu J X, Zheng W. Impact of climate change and human activities on vegetation cover in the Loess Plateau[J]. Scientia Sinica(Terrae),2007,37(11):1504-1514.
[32] Tong S Q, Zhang J Q, Ha S, et al. Dynamics of fractional vegetation coverage and its relationship with climate and human activities in Inner Mongolia, China[J]. Remote Sensing, 2016,8(9):776.
[33] Zhu Z C, Bi J, Pan Y Z, 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.
[34] He Y H Z, Wang L, Niu Z, et al. Vegetation recovery and recent degradation in different karst landforms of southwest China over the past two decades using GEE satellite archives[J]. Ecological Informatics, 2022,68:101555.
[35] 何宏昌,马炳鑫,靖娟利,等.近20年西南喀斯特地区植被NPP时空变化及自然因素地理探测[J].水土保持研究,2022,29(3):172-178,188.
He H C, Ma B X, Jing J L, et al. Spatiotemporal changes of NPP and Natural factors in the Southwestern karst areas from 2000 to 2019[J]. Research of Soil and Water Conservation, 2022,29(3):172-178,188.
[36] Zheng K Y, Tan L S, Sun Y W, et al. Impacts of climate change and anthropogenic activities on vegetation change: Evidence from typical areas in China[J]. Ecological Indicators, 2021,126:107648.
[37] 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.
Sun G P, Liu X F, Wang X H, et al. Changes in vegetation coverage and its influencing factors across the Yellow River Basin during 2001—2020[J]. Journal of Desert Research, 2021,41(4):205-212.
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Last Update:
2024-04-20