Changes in vegetation cover and its influencing factors in the inner Mongolia reach of the yellow river basin from 2001 to 2018

归一化差异植被指数 干旱 环境科学 植被(病理学) 植树造林 自然地理学 增强植被指数 固碳 气候变化 水文学(农业) 农林复合经营 地理 生态学 植被指数 地质学 病理 岩土工程 生物 二氧化碳 医学
作者
Xiaojing Zhang,Guoqiang Wang,Baolin Xue,A Yinglan
出处
期刊:Environmental Research [Elsevier]
卷期号:215: 114253-114253 被引量:37
标识
DOI:10.1016/j.envres.2022.114253
摘要

Vegetation cover is one of the primary indicators of changes in ecosystems. China has implemented a few large-scale afforestation programs in the arid and semi-arid areas, including the Inner Mongolia Reach of the Yellow River Basin to prevent and control soil erosion. Although these programs have alleviated the environment problems in the region to a certain extent, the effects of the increasing vegetation greenness on the environments under climate change remain controversial for the argued large water consumption. In this study, the spatio-temporal characteristics of Normalized Difference Vegetation Index (NDVI) in the vegetation coverage area of the study area based on remote sensing data from 2001 to 2018. Meanwhile, using the Extreme Gradient Boosting (XGBoost) method – an excellent algorithm for ensemble learning methods – to forecast vegetation growth in the following ten years. The results indicated that, despite of the spatial heterogeneity, the vegetation NDVI exhibited a significant increase across the study area. Based on the NDVI trend, the area of improved vegetation in this region was much larger than the degraded area from 2001 to 2018, accounting for 85.9% and 8.6% of the total vegetation coverage area, respectively. However, the forecasting result by the Hurst index shows the future growth and carbon sequestration capacity in most areas showed a declining trend. Further, based on the Coupled Model Inter comparison Project - Phase 6 (CMIP6) data, the XGBoost method is used to predict the growth status and carbon sequestration capacity of vegetation in this area under different climate scenarios. The results showed that different climate scenarios had little effect on vegetation growth from 2019 to 2030. Results from this study may provide basis for the protection of ecological environment in the Inner Mongolia Reach of the Yellow River Basin.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
乔沃维奇发布了新的文献求助10
刚刚
纯情的凡双完成签到 ,获得积分10
3秒前
xixi完成签到 ,获得积分10
5秒前
瘦瘦的果汁完成签到,获得积分10
6秒前
WILD完成签到 ,获得积分10
7秒前
木卫二完成签到 ,获得积分10
8秒前
niu完成签到,获得积分10
9秒前
听音乐的可可完成签到 ,获得积分10
9秒前
wwtt完成签到 ,获得积分10
10秒前
红火完成签到 ,获得积分10
11秒前
高海龙完成签到,获得积分10
13秒前
李四发布了新的文献求助10
15秒前
16秒前
Auston_zhong应助予秋采纳,获得10
17秒前
假装学霸完成签到 ,获得积分10
17秒前
九日九日发布了新的文献求助10
17秒前
闪闪小小完成签到 ,获得积分10
19秒前
乔木自燃完成签到 ,获得积分10
19秒前
LYH完成签到,获得积分10
20秒前
jinjing完成签到,获得积分10
21秒前
白粥粥完成签到 ,获得积分10
22秒前
liujianxin发布了新的文献求助10
23秒前
大个应助科研通管家采纳,获得10
24秒前
27秒前
小米的稻田完成签到 ,获得积分10
30秒前
Lina完成签到 ,获得积分10
34秒前
早睡早起发布了新的文献求助10
34秒前
35秒前
王佳豪完成签到,获得积分10
36秒前
激动的xx完成签到 ,获得积分10
36秒前
戚时雨完成签到 ,获得积分10
39秒前
liujianxin发布了新的文献求助10
41秒前
orixero应助巫青丝采纳,获得10
41秒前
专一的元柏完成签到 ,获得积分10
45秒前
danli完成签到 ,获得积分10
45秒前
Lexi完成签到 ,获得积分10
45秒前
46秒前
roundtree完成签到 ,获得积分0
46秒前
ufofly730完成签到 ,获得积分10
52秒前
优雅的平安完成签到 ,获得积分10
52秒前
高分求助中
Modern Epidemiology, Fourth Edition 5000
Kinesiophobia : a new view of chronic pain behavior 5000
Molecular Biology of Cancer: Mechanisms, Targets, and Therapeutics 3000
Digital Twins of Advanced Materials Processing 2000
Propeller Design 2000
Weaponeering, Fourth Edition – Two Volume SET 2000
First commercial application of ELCRES™ HTV150A film in Nichicon capacitors for AC-DC inverters: SABIC at PCIM Europe 1000
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 纳米技术 化学工程 生物化学 物理 计算机科学 内科学 复合材料 催化作用 物理化学 光电子学 电极 冶金 细胞生物学 基因
热门帖子
关注 科研通微信公众号,转发送积分 6004947
求助须知:如何正确求助?哪些是违规求助? 7525244
关于积分的说明 16111927
捐赠科研通 5150344
什么是DOI,文献DOI怎么找? 2759742
邀请新用户注册赠送积分活动 1736720
关于科研通互助平台的介绍 1632078