黄河流域甘肃段植被覆盖度时空变化及对气候因子的响应

陆荫; 张强; 李晓红; 杨淑霞; 杨青

doi:10.13961/j.cnki.stbctb.2020.02.034

您当前的位置：

首页 >

文章列表页 >

黄河流域甘肃段植被覆盖度时空变化及对气候因子的响应

试验研究

- 黄河流域甘肃段植被覆盖度时空变化及对气候因子的响应
- Temporal and Spatial Variation of Vegetation Coverage and Its Response to Climate Factors in Gansu Section of Yellow River Basin
- 水土保持通报 2020年40卷第2期页码：232-238
- 作者机构：
  
  甘肃省环境监测中心站,甘肃,兰州,730020
- 作者简介：
- 基金信息：
  
  甘肃省青年科技基金计划项目"基于无人机技术的甘南草地植被状况监测"（18JR3RA024）
- DOI：10.13961/j.cnki.stbctb.2020.02.034
  中图分类号： S812.1
- 纸质出版：2020
- 稿件说明：
移动端阅览
陆荫, 张强, 李晓红, 等. 黄河流域甘肃段植被覆盖度时空变化及对气候因子的响应[J]. 水土保持通报, 2020,40(2):232-238.

Lu Yin, Zhang Qiang, Li Xiaohong, et al. Temporal and Spatial Variation of Vegetation Coverage and Its Response to Climate Factors in Gansu Section of Yellow River Basin[J]. Bulletin of Soiland Water Conservation, 2020, 40(2): 232-238.
陆荫, 张强, 李晓红, 等. 黄河流域甘肃段植被覆盖度时空变化及对气候因子的响应[J]. 水土保持通报, 2020,40(2):232-238. DOI： 10.13961/j.cnki.stbctb.2020.02.034.

Lu Yin, Zhang Qiang, Li Xiaohong, et al. Temporal and Spatial Variation of Vegetation Coverage and Its Response to Climate Factors in Gansu Section of Yellow River Basin[J]. Bulletin of Soiland Water Conservation, 2020, 40(2): 232-238. DOI： 10.13961/j.cnki.stbctb.2020.02.034.

摘要

[目的] 分析黄河流域甘肃段2000-2018年植被覆盖度变化的时空演变规律，探讨该区域植被覆盖度的变化对气候的响应机制，为该区域生态环境与社会经济的协调可持续发展和进一步落实生态环境保护、建设及恢复提供科学依据。[方法] 基于2000-2018年的MODIS NDVI数据、气象数据，采用线性趋势分析和相关性分析等方法，对黄河流域甘肃段植被覆盖度的时空变化特征及与气候因子之间的关系进行分析。[结果] ①空间上，近19 a研究区植被覆盖度自西南向东北在不断降低，以甘南州的植被覆盖状况最好；植被覆盖度改善面积占36.64%，主要分布于兰州市北部、临夏州、定西市、庆阳市、平凉市大范围区域、天水市南部等，而退化面积占4.2%，主要集中于甘南州等地区。②时间上，研究区植被覆盖度以2013年为界呈现"先持续增加后波动减少"的变化趋势，但整体在不断增加；以平凉市的增加速度最快，平均每年增长0.96%。③研究区植被覆盖度对降水量变化的响应敏感，与降水量呈现显著的正相关关系。[结论] 研究区植被覆盖度空间差异明显，2000-2018年植被以改善为主，降水是影响这些区域植被改善的有利因素，降水状况的改善对研究区生态环境建设与修复至关重要。

Abstract

[Objective] The temporal and spatial evolution of vegetation coverage change from 2000 to 2018 was analyzed

and the response mechanism of vegetation coverage to climate change was clarified in Gansu section of the Yellow River basin

in order to provide scientific basis for the coordinated and sustainable development of ecological environment and social economy in this region and for the further implementation of ecological environment protection

construction and restoration.[Methods] Based on the MODIS NDVI data and meteorological data from 2000 to 2018

linear regression and correlation analysis method was used to analyze the temporal and spatial variation of vegetation coverage and its relationship with climate factors in Gansu section of the Yellow River basin.[Results] The vegetation coverage was decreasing from southwest to northeast in the past 19 years

and Gannan Prefecture had the best vegetation cover. The improved area of vegetation coverage accounted for 36.64%

which was mainly distributed in the north of Lanzhou

Linxia Prefecture

Dingxi City

Qingyang City

Pingliang City and the south of Tianshui City

while the degraded area accounted for 4.2%

which was mainly concentrated in Gannan Prefecture. The vegetation coverage in the study area showed a trend of continuous increase before 2013 and then decreased in fluctuation afterward

but it was increasing as a whole. Pingliang City was the fastest growing city

with an average annual growth rate of 0.96 per year. The vegetation coverage was sensitive to precipitation change in the study area

which showed a significant positive correlation with precipitation.[Conclusion] The spatial difference of vegetation cover in the study area was obvious. The vegetation was mainly improved from 2000 to 2018. Precipitation is a favorable factor affecting the improvement of vegetation

and the improvement of precipitation is very important for the construction and restoration of ecological environment in the study area.

关键词

Keywords

references

陈云浩,李晓兵,史培军,等.北京海淀区植被覆盖的遥感动态研究[J].植物生态学报,2001,25(5):588-593.

邹洪坤.湖北省植被覆盖度动态变化及其对气候变化的响应[D].湖北武汉:武汉大学,2018.

Wang Hongwei, Qi Yuan, Huang Chunlin, et al. Analysis of vegetation changes and dominant factors on the Qinghai-Tibet Plateau, China[J]. Sciences in Cold and Arid Regions, 2019,11(2):150-158.

Ringrose S, Matheson W, Wolski P, et al. Vegetation cover trends along the Botswana Kalahari transect[J]. Journal of Arid Environments, 2003,54(2):297-317.

邓友志.漓江流域植被覆盖度遥感估算模型及动态变化研究[D].广西桂林:桂林理工大学,2013.

郭永强,王乃江,褚晓升,等.基于Google Earth Engine分析黄土高原植被覆盖变化及原因[J].中国环境科学,2019,39(11):4804-4811.

Zhang Yahai, Ye Aizhong. Spatial and temporal variations in vegetation coverage observed using AVHRR GIMMS and Terra MODIS data in the mainland of China[J]. International Journal of Remote Sensing, 2020,41(11):4238-4268.

Liu Qun, Yang Zhaoping, Han Fang, et al. NDVI-based vegetation dynamics and their response to recent climate change:A case study in the Tianshan Mountains, China[J]. Environmental Earth Sciences, 2016,75(16):1189.

Revadekar J V, Tiwari Y K, Kumar K R. Impact of climate variability on NDVI over the Indian region during 1981-2010[J]. International Journal of Remote Sensing, 2012,33(22):7132-7150.

Xu Yufeng, Yang Jing, Chen Yaning. NDVI-based vegetation responses to climate change in an arid area of China[J]. Theoretical & Applied Climatology, 2016,126(1/2):213-222.

Park H S, Sohn B J. Recent trends in changes of vegetation over East Asia coupled with temperature and rainfall variations[J]. Journal of Geophysical Research Atmospheres, 2010,115(14):101-125.

Liu Ya, Li Yan, Li Shuangcheng, et al. Spatial and Temporal Patterns of Global NDVI Trends:Correlations with Climate and Human Factors[J]. Remote Sensing, 2015,7(10):13233-13250.

李登科,王钊.退耕还林后陕西省植被覆盖度变化及其对气候的响应[J].生态学杂志,2019,39(1):1-10.

韩飞飞,闫俊杰,郭斌.阿勒泰地区植被覆盖度及ET对气温变化的响应[J].干旱区地理,2019,42(6):1-17.

赵玉.渭南市植被覆盖变化及其与气候因子的相关性[J].生态科学,2019,38(5):92-103.

张斯琦,陈辉,宋明华,等.2000-2015年柴达木盆地植被覆盖度时空变化及其与环境因子的关系[J].干旱区地理,2019,42(5):1124-1132.

陈金牛,毛学刚,侯艳军.1982-2015年山西省忻州市植被覆盖变化与气候因子的相关性分析[J].台湾农业探索,2019,3(3):28-37.

宋鹏飞,季民,刘泽群,等.山东省植被覆盖度变化与气候因子相关性分析[J].测绘科学,2020,45(3):1-8.

金凯.中国植被覆盖时空变化及其与气候和人类活动的关系[D].陕西杨凌:西北农林科技大学,2019.

杨尚武.黄河流域不同时间尺度植被覆盖变化及与气候因子的关系[D].甘肃兰州:西北师范大学,2015.

温小洁.黄河中上游植被覆盖时空演变对退耕还林(草)工程的动态响应研究[D].陕西杨凌:西北农林科技大学,2019.

陆佩毅.陇中黄土丘陵沟壑区植被恢复建设与对策探讨[J].甘肃水利水电技术,2011,47(3):62-63.

马学成.陇中黄土丘陵沟壑区县域社会生态系统恢复力时空变化及其影响因素[D].甘肃兰州:兰州大学,2019.

常继青,牛最荣.甘肃黄河流域与疏勒河流域降水径流变化特性对比分析[J].水文,2014,34(5):94-96.

姚玉璧,李耀邦,张谋草,等.陇东黄土高原气候对全球变暖的响应及其对林果的影响[J].南京林业大学学报(自然科学版),2005,29(4):73-77.

赵英时.遥感应用分析原理与方法[M].北京:科学出版社,2003.

Stow D, Daeschner S, Hope A, et al. Variability of the seasonally integrated normalized difference vegetation index across the north slope of Alaska in the 1990s[J]. International Journal of Remote Sensing, 2003,24(5):1111-1117.

穆少杰,李建龙,周伟,等.2001-2010年内蒙古植被净初级生产力的时空格局及其与气候的关系[J].生态学报,2013,33(12):3752-3764.

游浩妍,骆成凤,刘正军,等.基于MODIS植被指数估算青海湖流域植被覆盖度研究[J].遥感信息,2012,27(5):55-60.

崔丹丹,张耀南,陈广庭.2001-2010年甘肃省植被覆盖的时空变化[J].中国沙漠,2014,34(4):1161-1166.

叶培龙,刘新伟,赵文婧,等.2016年8月甘肃省持续性高温过程及其异常大气环流特征[J].高原气象,2019,38(6):1283-1292.

王伟军,赵雪雁,万文玉,等.2000-2014年甘南高原植被覆盖度变化及其对气候变化的响应[J].生态学杂志,2016,35(9):2494-2504.

王胜忠.甘南州天然草地退化及生态保护对策分析[J].农业科技与信息,2009,(03):48-49.

张晶.甘肃省甘南牧区草原法实施状况及影响[D].甘肃兰州:兰州大学,2010.

杨尚武,张勃.基于SPOT NDVI的甘肃河东植被覆盖变化及其对气候因子的响应[J].生态学杂志,2014,33(2):455-461.

胡春艳,卫伟,王晓峰,等.甘肃省植被覆盖变化及其对退耕还林工程的响应[J].生态与农村环境学报,2016,32(4):588-594.

浏览量

1257

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

基于CSLE模型的2024年福建省典型区域水土流失特征及其差异评估

黄河流域资源型城市绿色转型效率的水平测度、差异来源与时空演进

黄河流域九省区农业碳排放的驱动因素及预测

红河干热河谷不同恢复模式下植被对干旱的抵抗力

黄河流域城市土地集约利用与生态文明建设的耦合协调性