2001-2018年西南地区NDVI变化特征及影响因素

杨艳蓉; 侯召朕; 张增信

doi:10.13961/j.cnki.stbctb.2021.02.044

您当前的位置：

首页 >

文章列表页 >

2001-2018年西南地区NDVI变化特征及影响因素

试验研究

- 2001-2018年西南地区NDVI变化特征及影响因素
- NDVI Changes and Driving Factors in Southwest China from 2001 to 2018
- 水土保持通报 2021年41卷第2期页码：337-344
- 作者机构：
  
  1. 南京林业大学生物与环境学院,江苏,南京,210037
  2. 南京林业大学南方现代林业协同创新中心,江苏,南京,210037
  3. 南京林业大学林学院,江苏,南京,210037
- 作者简介：
- 基金信息：
  
  国家自然科学基金项目“基于云地闪分析的我国西南天然林雷击火起火点范围预警研究”（31971670）
- DOI：10.13961/j.cnki.stbctb.2021.02.044
  中图分类号： X87;S157.2
- 纸质出版：2021
- 稿件说明：
移动端阅览
杨艳蓉, 侯召朕, 张增信. 2001-2018年西南地区NDVI变化特征及影响因素[J]. 水土保持通报, 2021,41(2):337-344.

Yang Yanrong, Hou Zhaozhen, Zhang Zengxin. NDVI Changes and Driving Factors in Southwest China from 2001 to 2018[J]. Bulletin of Soiland Water Conservation, 2021, 41(2): 337-344.
杨艳蓉, 侯召朕, 张增信. 2001-2018年西南地区NDVI变化特征及影响因素[J]. 水土保持通报, 2021,41(2):337-344. DOI： 10.13961/j.cnki.stbctb.2021.02.044.

Yang Yanrong, Hou Zhaozhen, Zhang Zengxin. NDVI Changes and Driving Factors in Southwest China from 2001 to 2018[J]. Bulletin of Soiland Water Conservation, 2021, 41(2): 337-344. DOI： 10.13961/j.cnki.stbctb.2021.02.044.

摘要

[目的

]

研究西南地区人为和自然因素影响下的NDVI动态特征，为该区天然林保护政策的科学实施提供依据。[方法

]

利用2001—2018年MODIS NDVI数据、土地利用数据、气候数据，结合Theil-Sen中值趋势分析、Mann-Kendall趋势检验等，探讨人为和自然因素下西南地区植被动态变化。[结果

]

①各类型植被NDVI均逐年递增，增速最快的是农用地和稀树草原。岷江—乌蒙山以东是NDVI高值区和显著改善趋势区；加上云贵高原南缘，显著改善趋势区占总面积的67.09%。②天然林保护、退耕还林/还草的林业政策促使低NDVI植被向高NDVI植被转变是西南地区NDVI增加的原因之一。其中贡献度最大的是稀树草原类型向森林类型的转化，2001—2018年转化面积达73 693 km

，净转化率逐年提高，主要分布在岷江—乌蒙山以东。③气温与不同植被NDVI的正相关性大于年降水量，在岷江—乌蒙山以东，NDVI与气象要素的正相关性都较高。在气温上升、降水量增加的条件下，41.8%的NDVI增长与气温和降水有关，二者的贡献率分别为32.35%和14.54%。[结论

]

随着20世纪末以来的天然林保护政策实施以及暖、湿化区域气候变化等人为和自然因素影响，2001—2018年西南地区NDVI持续增加，这种增加特征在岷江—乌蒙山东、西两侧表现差异，东侧森林增加面积、NDVI改善趋势普遍高于西侧。

Abstract

[Objective] The dynamic changes of NDVI under the influence of human and natural factors in Southwest China were studied in order to provide a basis for the scientific implementation of natural forest protection policies in this region.[Methods] Based on MODIS NDVI

land use data and climate data from 2001 to 2018

combined with Theil-Sen median trend analysis and Mann-Kendall trend test

the dynamic changes of vegetation under human and natural factors in the Southwest China were investigated.[Results] ① NDVI of all types of vegetation increased year by year

with the fastest growth in agricultural land and savanna. The east of Minjiang and Wumeng Mountains was the region with high NDVI value and significant improvement trend; Combined with the southern margin of the Yunnan-Guizhou Plateau

the trend area of significant improvement accounted for 67.09% of the total area. ② One of the reasons for the increase of NDVI in Southwest China was that the natural forest protection and the forestry policy of returning farmland to forest/grassland promoted the transformation of low NDVI vegetation to high NDVI vegetation. The largest contribution was the conversion of woody savanna and savanna to forests. From 2001 to 2018

the conversion area reached 73 693 km2

and the net conversion rate increased year by year

mainly distributed in the east part of the boundary of Minjiang River and Wumeng Mountain. ③ The positive correlation between temperature and NDVI was greater than that of annual precipitation. In the east of Minjiang River and Wumeng Mountains

the positive correlation between NDVI and meteorological elements was high. Under the condition of warming and getting wetter

41.8% of NDVI growth was related to temperature and precipitation

and their contribution rates were 32.35% and 14.54% respectively.[Conclusion] With the implementation of natural forest protection policy and the warming and humidifying regional climate change in the last 20 years

the NDVI in the Southwest China continued to increase from 2001 to 2018. Based on the boundary of the Minjiang River and Wumeng Mountains

such increasing characteristics showed differences in the east and west parts

and the increasing forests area and the NDVI improvement trend on the east side was generally higher than that of on the west side.

关键词

Keywords

references

张琨,吕一河,傅伯杰,等.黄土高原植被覆盖变化对生态系统服务影响及其阈值[J].地理学报,2020,75(5):949-960.

Defries R S, Townshend J R. NDVI-derived land cover classifications at a global scale[J]. International Journal of Remote Sensing, 1994,15(17):3567-3586.

Chen Chi, Park T, Wang Xuhui, et al. China and India lead in greening of the world through land-use management[J]. Nature Sustainability, 2019,2(2):122-129.

王新超.我国启动实施六大林业重点工程[J].农村实用工程技术,2001(8):33-36.

王钰,王爽宇.中国20年退耕还耕还草5亿多亩[J].中南林业科技大学学报,2019,39(220):2-6.

Du Jiaqiang, Quan Zhanjun, Fang Shifeng, et al. Spatiotemporal changes in vegetation coverage and its causes in China since the Chinese economic reform[J]. Environmental Science and Pollution Research, 2020,27(1):1144-1159.

Guo Meng, Li Jing, He Hongshi, et al. Detecting global vegetation changes using mann-kendal (MK) trend test for 1982-2015 time period[J]. Chinese Geographical Science, 2018,28(6):907-919.

Peng Shushi, Piao Shilong, Ciais Philippe, et al. Asymmetric effects of daytime and night-time warming on Northern Hemisphere vegetation[J]. Nature, 2013,501(7465):88-92.

Roerink G J, Menenti M, Soepboer W, et al. Assessment of climate impact on vegetation dynamics by using remote sensing[J]. Physics and Chemistry of the Earth, Parts A/B/C, 2003,28(1-3):103-109.

韩雅,朱文博,李双成.基于GWR模型的中国NDVI与气候因子的相关分析[J].北京大学学报(自然科学版),2016,52(6):1125-1133.

郑朝菊,曾源,赵玉金,等.20世纪90年代以来中国西南地区土地覆被变化[J].生态学报,2016,36(23).

国政,聂华,臧润国,等.西南地区天然林保护工程生态效益评价[J].内蒙古农业大学学报(自然科学版),2011,32(2):65-72.

华明.青藏高原热状况对夏季西南地区气候影响的分析及模拟[J].高原气象,2003,22(S1):152-156.

Zhou Q, Wei X, Zhou X, et al. Vegetation coverage change and its response to topography in a typical karst region:The Lianjiang River basin in Southwest China[J]. Environmental Earth Sciences, 2019,78(6):1-10.

Yue Yuemin, Wang Kailung, Zhang B, et al. Remote sensing of fractional cover of vegetation and exposed bedrock for karst rocky desertification assessment[J]. Procedia Environmental Sciences, 2012,13(1):847-853.

吕妍,张黎,闫慧敏,等.中国西南喀斯特地区植被变化时空特征及其成因[J].生态学报,2018,38(24):8774-8786.

谢慧君,张廷斌,易桂花,等.川西高原植被NDVI动态变化特征及对气候因子的响应[J].水土保持通报,2020,40(4):286-294.

李应鑫,李石华,彭双云.云南省九大高原湖泊流域NDVI时空演变及其与气候的响应关系[J].水土保持研究,2020,141(4):196-204.

刘晔,李鹏,许玥,等.中国西南干旱河谷植物群落的数量分类和排序分析[J].生物多样性,2016,24(4):378-388.

Friedl M A, McIver D K, Hodges J C F, et al. Global land cover mapping from MODIS:Algorithms and early results[J]. Remote sensing of Environment, 2002,83(1/2):287-302.

李金洁,王爱慧.基于西南地区台站降雨资料空间插值方法的比较[J].气候与环境研究,2019,24(1):52-62.

Yang Yunjie, Wang Shijie, Bai Xiaoyong, et al. Factors affecting long-term trends in global NDVI[J]. Forests, 2019,10(5):372-389.

范松克,郝成元.2001-2016年河南省NDVI时空变化特征分析[J].江苏农业学报,2019,35(4):860-867.

王计平,郭仲军,程复,等.北疆生态功能区降水气温时空变化及其与NDVI相关性分析[J].林业资源管理,2017,2(1):110-1171.

许翔驰.中国植被时空变化特征[J].哈尔滨师范大学自然科学学报,2019,35(2):100-104.

宋乃平,杜灵通,王磊.盐池县2000-2012年植被变化及其驱动力[J].生态学报,2015,35(22):7377-7386.

张勃,王东,王桂钢,等.西南地区近14年植被覆盖变化及其与气候因子的关系[J].长江流域资源与环境,2015,24(6):956-964.

冯国艳,马明国,时伟宇.2001-2016年西南喀斯特地区植被动态变化分析[J].广东农业科学,2018,44(12):94-102.

华维,范广洲,李洪权,等.西南地区近21年来NDVI变化特征分析[J].成都信息工程学院学報,2008,23(1):91-97.

尹文有.全球变暖背景下西南地区气候变化特征分析[D].甘肃兰州:兰州大学,2010.

Zhao Anzhou, Zhang Anbing, Lu Chunyan, et al. Spatiotemporal variation of vegetation coverage before and after implementation of Grain for Green Program in Loess Plateau, China[J]. Ecological Engineering, 2017,104:13-22.

芦鑫,殷淑燕.毛乌素沙地周边地区相对湿度与NDVI变化研究[J].西北大学学报(自然科学版),2018,48(234):133-142.

宋富强,康慕谊,杨朋,等.陕北地区GIMMS, SPOT-VGT和MODIS归一化植被指数的差异分析[J].北京林业大学学报,2010,32(4):72-80.

朱艺旋,张扬建,俎佳星,等.基于MODIS NDVI, SPOT NDVI数据的GIMMS NDVI性能评价[J].应用生态学报,2019,30(2):536-544.

庞静.基于地理探测器模型的自然和人为因素对植被变化的影响[D].江西太原:山西大学,2016.

王静,刘天军.基于RUE的植被覆盖动态演变特征及归因分析:以宝鸡地区为例[J].生态环境学报,2020,29(6):1078-1089.

贾京伟,牛健植,蔺星娜,等.洋河流域NDVI时空变化及驱动力分析[J].北京林业大学学报,2019,41(2):106-115.

黑哲,王飞,韩剑桥,等.退耕还林(草)以来陕北白于山区植被覆盖与土壤侵蚀强度变化[J].水土保持研究,2020,27(141):43-50.

宋乃平,杜灵通,王磊.盐池县2000-2012年植被变化及其驱动力[J].生态学报,2015,35(22):7377-7386.

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.

张思源,聂莹,张海燕,等.基于地理探测器的内蒙古植被NDVI时空变化与驱动力分析[J].草地学报,2020,28(5):1460-1472.

陶帅,邝婷婷,彭文甫,等.2000-2015年长江上游NDVI时空变化及驱动力分析:以宜宾市为例[J].生态学报,2020,40(14):1-15.

Wang Jing, Feng Liang, Palmer Paul, et al. Large Chinese land carbon sink estimated from atmospheric carbon dioxide data[J]. Nature, 2020,586(7831):720-723.

浏览量

1055

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

中尺度流域NDVI尺度转换研究

青海省都兰县NDVI变化及影响因子研究

宁夏回族自治区NDVI的时空变化特征研究

近10a黄土高原地区NDVI变化及其对水热因子响应分析

高寒矿区排土场边坡植被恢复年限对产流产沙的影响