揭示自然的复原力:用谷歌地球引擎探索新冠肺炎时代印度贾坎德邦的植被动态

IF 3 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Climate Pub Date : 2023-09-08 DOI:10.3390/cli11090187
Tauseef Ahmad, Saurabh Kumar Gupta, S. Singh, Gowhar Meraj, Pankaj Kumar, S. Kanga
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引用次数: 0

摘要

2019年严重急性呼吸综合征冠状病毒病(新冠肺炎)大流行对全球健康和经济稳定提出了前所未有的挑战。有趣的是,必要的封锁措施虽然破坏了人类社会,但无意中导致了环境复兴,尤其是在减少空气污染和改善植被健康方面。这项研究利用谷歌地球引擎进行基于云的数据分析,调查了封锁对印度贾坎德邦植被健康的影响。使用时空NDVI分析和时间序列模型对MODIS-NDVI数据进行分析。这些分析显示,从2019年4月到2020年,最大植被绿化率显著增加了19%,随后在同年3月和5月分别增加了13%和3%。从2000年到2020年的一项长期分析显示,植被的绿色度总体上升了16.7%。虽然最大值保持相对恒定,但在旱季略有增加。陆地卫星数据Mann–Kendall趋势检验强化了这些发现,显示贾坎德邦西北地区的NDVI趋势从负(1984–2019)显著转变为正17.7%(1984–2021)。还研究了封锁前和封锁期间的降水量(使用NASA功率和Merra2数据)和NDVI相关性。6月的降雨量最大(350–400毫米),而7月的降雨量通常在300毫米左右,覆盖了贾坎德邦近85%的地区。有趣的是,2020年8月的降雨量高达550毫米,主要发生在贾坎德邦的南部地区,而2019年同月为400毫米。在此期间,NDVI值的峰值变化范围在0.6–0.76和0.76–1之间,在全州范围内观察到。尽管空气污染的减少改善了植被健康,但这些好处在封锁后开始减少。这一观察结果强调了科学家和研究人员立即关注和干预的必要性。了解封锁引发的环境变化及其对植被健康的影响,有助于制定积极的环境管理战略,为可持续和有韧性的未来铺平道路。
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Unveiling Nature’s Resilience: Exploring Vegetation Dynamics during the COVID-19 Era in Jharkhand, India, with the Google Earth Engine
The Severe Acute Respiratory Syndrome Coronavirus Disease 2019 (COVID-19) pandemic has presented unprecedented challenges to global health and economic stability. Intriguingly, the necessary lockdown measures, while disruptive to human society, inadvertently led to environmental rejuvenation, particularly noticeable in decreased air pollution and improved vegetation health. This study investigates the lockdown’s impact on vegetation health in Jharkhand, India, employing the Google Earth Engine for cloud-based data analysis. MODIS-NDVI data were analyzed using spatio-temporal NDVI analyses and time-series models. These analyses revealed a notable increase in maximum vegetation greenery of 19% from April 2019 to 2020, with subsequent increases of 13% and 3% observed in March and May of the same year, respectively. A longer-term analysis from 2000 to 2020 displayed an overall 16.7% rise in vegetation greenness. While the maximum value remained relatively constant, it demonstrated a slight increment during the dry season. The Landsat data Mann–Kendall trend test reinforced these findings, displaying a significant shift from a negative NDVI trend (1984–2019) to a positive 17.7% trend (1984–2021) in Jharkhand’s north-west region. The precipitation (using NASA power and Merra2 data) and NDVI correlation were also studied during the pre- and lockdown periods. Maximum precipitation (350–400 mm) was observed in June, while July typically experienced around 300 mm precipitation, covering nearly 85% of Jharkhand. Interestingly, August 2020 saw up to 550 mm precipitation, primarily in Jharkhand’s southern region, compared to 400 mm in the same month in 2019. Peak changes in NDVI value during this period ranged between 0.6–0.76 and 0.76–1, observed throughout the state. Although the decrease in air pollution led to improved vegetation health, these benefits began to diminish post-lockdown. This observation underscores the need for immediate attention and intervention from scientists and researchers. Understanding lockdown-induced environmental changes and their impact on vegetation health can facilitate the development of proactive environmental management strategies, paving the way towards a sustainable and resilient future.
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来源期刊
Climate
Climate Earth and Planetary Sciences-Atmospheric Science
CiteScore
5.50
自引率
5.40%
发文量
172
审稿时长
11 weeks
期刊介绍: Climate is an independent, international and multi-disciplinary open access journal focusing on climate processes of the earth, covering all scales and involving modelling and observation methods. The scope of Climate includes: Global climate Regional climate Urban climate Multiscale climate Polar climate Tropical climate Climate downscaling Climate process and sensitivity studies Climate dynamics Climate variability (Interseasonal, interannual to decadal) Feedbacks between local, regional, and global climate change Anthropogenic climate change Climate and monsoon Cloud and precipitation predictions Past, present, and projected climate change Hydroclimate.
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