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作 者:曹永强[1] 周姝含 杨雪婷 CAO Yongqiang;ZHOU Shuhan;YANG Xueting(School of Geographical Sciences,Liaoning Normal University,Dalian116029,China)
出 处:《生态学报》2022年第14期5966-5979,共14页Acta Ecologica Sinica
基 金:国家自然科学基金项目(52079060);辽宁省重点研发计划项目(2020JH2/10200043);“辽宁省兴辽英才项目”。
摘 要:区域归一化植被指数(NDVI)变化特征对环境容量和生态发展方向有重要指示作用。基于SPOT/VEGETATION NDVI数据和ESA CCI-LC植被分类数据,利用Theil-Sen+Mann-Kendall、变异系数、Hurst指数和相关性分析方法,对辽宁省2000—2019年不同植被类型归一化植被指数时空变化特征和气候因子之间的响应关系进行分析。结果表明:(1)NDVI均值呈现从乔木到草原逐渐降低的趋势,不同植被类型在生长季具有不同的生长习性;(2)各植被类型都呈增加趋势,结合Hurst指数和Sen趋势,辽宁省36.26%的植被将趋于改善,约有61.51%的植被将趋于退化;(3)变异系数结果表明:所有植被类型中以乔木植被最为稳定,草原型植被最不稳定。(4)辽宁省各植被类型NDVI与降水显著正相关,与气温相关性相对较低。结果可为辽宁省生态评价和碳循环研究提供植被覆盖动态参考。The change characteristics of regional Normalized Difference Vegetation Index(NDVI) are important indicators of environmental capacity and ecological development. Based on SPOT/VEGETATION NDVI data and ESA CCI-LC Vegetation classification data, using Theil-Sen+ Mann-Kendall, coefficient of variation, Hurst index and correlation analysis method, the spatio-temporal variation characteristics of normalized indices of different vegetation types and the response relationship between climate factors were analyzed in Liaoning Province from 2000 to 2019. The results showed that:(1) the mean value of NDVI decreased gradually from arbor vegetation to steppe vegetation, and different vegetation types had different growth habits in the growing season.(2) All vegetation types showed an increasing trend. Combined with Hurst index and Sen trend, 36.26% of the vegetation in Liaoning Province would be improved, while 61.51% of the vegetation would be degraded.(3) The results of variation coefficient showed that among all vegetation types, arbor vegetation was the most stable, while steppe vegetation was the most unstable.(4) NDVI of all vegetation types in Liaoning Province was significantly positively correlated with precipitation, but relatively low correlated with air temperature. The results can provide a reference for the ecological evaluation and carbon cycle study of Liaoning Province.
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