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1.
京津冀地区植被时空动态及定量归因 总被引：2，自引：0，他引：2
作为气候变化的敏感指示器,植被的物候、生长、空间分布格局等特征及其动态变化主要取决于气候环境中的水热条件,因此在气候变化背景下,气候-植被关系成为了全球变化研究的前沿和热点问题。本文综合平均温度、降水、水汽压、湿度、日照时数、SPEI等气候因子,坡度、坡向海拔等地形因子及人为活动因子,应用地理探测器方法针对2006-2015年京津冀地区不同季节NDVI、不同地貌类型区、不同植被类型区生长季NDVI的定量归因研究,揭示了过去10年间植被时空分布格局,及植被对气候、非气候因素响应的季节差异与区域差异,以期为生态工程的建设与修复提供参考意义。趋势分析表明：①2006-2015年京津冀地区NDVI呈现增加趋势,但存在显著的空间差异,如山地生长季NDVI的增长速率大于平原、台地、丘陵等地;②基于地理探测器的定量归因结果表明,降水是年尺度上NDVI空间分布的主导因子（解释力39.4%）,土地利用与降水的交互作用对NDVI的影响最为明显（q=58.2%）;③NDVI对气候因子的响应存在季节性及区域性差异,水汽压是春季NDVI空间分布的主导因子,湿度是夏、秋两季的主导因子,土地利用是冬季的主导因子;④影响因子对生长季NDVI的解释力因不同地貌类型区、不同植被类型区而差异显著。 相似文献
2.
青藏高原脆弱的高寒植被对外界干扰十分敏感,使其成为研究植被对气候变化响应的理想区域之一。青藏高原气候变化剧烈,在较短的合成时间研究气候变化对植被的影响十分必要。因此,本文利用GIMMS NDVI时间序列数据集,研究了1982-2012年青藏高原生长季月尺度植被生长的时空动态变化,探讨了其与气温、降水量和日照时数等气候因子的响应关系。结果表明：在区域尺度上,除8月外,其他各月份植被均呈增加趋势,显著增加多发生在4-7月和9月;大部分月份的NDVI增加速率随着时段的延长显著减小,表明NDVI增加趋势放缓;在像元尺度上,月NDVI显著变化的区域多呈增加趋势,但显著减少范围的扩张多快于显著增加。4月和7月植被生长主要是受气温和日照时数共同作用,6月和9月受气温的控制,而8月则主要受降水量的影响。长时间序列NDVI数据集的出现为采用嵌套时段研究植被生长变化趋势奠定了前提,而植被活动变化趋势的持续性则有助于形象表征植被活动变化过程、深入理解植被对气候变化的响应和预测植被未来生长变化趋势。由此推测,青藏高原月NDVI未来增加趋势总体上趋于缓和,但在像元尺度显著变化的区域趋于增加。 相似文献
3.
植物生长季的变化反映了全球气候变化对生态环境的影响。本研究以2000-2006年间MODIS-NDVI影像数据集,使用TIMESAT软件从归一化植被指数（NDVI）时间序列中,分别提取福建省不同森林植被的生长季开始日期（Start of Season,SOS）、生长季结束日期（End of Season,EOS）和生长季长度（Length of season,LOS）等物候参数,并与全省尺度的气温与降水量进行相关分析。结果表明：不同森林类型NDVI与当月月均气温之间具有较显著的相关性（R2为0.72-0.79,p<0.01）,同期温度变化对植被生长的影响相对于降水量更重要;而植被生长对降水量的响应存在大约2个月的时滞效应（R2为0.54-0.75,p<0.01）,说明前期的降水累积对于后续植被生长有较显著影响。福建省森林植被生长季持续时间约213~223 d,开始于每年4月初到4月中旬（第98~103 d）,结束于11月中旬前后（第316~321 d）。其中,南亚热带森林生长季长于中亚热带森林,相同气候条件下的阔叶林生长季时间略长于针叶林。另外,春季（2-4月）气温变化是导致福建省内2个气候带森林生长季开始时间、生长季结束时间及生长季长度变化的关键因素,而伴随春季温度升高,植被生长季开始时间提前（R2为0.83,p<0.01）,同时生长季长度延长（R2为0.80,p<0.01）。7 a间,生长季持续时间呈现微弱延长趋势,总体延长幅度为2.4~3.1 d。 相似文献
4.
北方农牧交错区地处半湿润/半干旱生态脆弱过渡带,干旱是影响该区植被生产力的关键因素之一。探究干旱对植被总初级生产力的影响,对深刻理解气候变化下生态系统生产力变化响应特征及优化区域碳水循环具有重要意义。为了更好地了解水分限制区不同干旱特征对GPP影响,本研究以北方农牧交错区为例,基于长时间序列的标准化降水蒸散发指数(SPEI3,1900—2020年)和植被总初级生产力(GPP,1982—2018年)等数据,首先采用小波分析明确SPEI3与GPP强相关周期,在此基础上利用游程理论识别干旱特征,进而分析了北方农牧交错区干旱特征与GPP的变化趋势,最后厘定了不同干旱特征对GPP的影响。结果表明:(1) 1982—2018年北方农牧交错区SPEI3与GPP在半年周期和年周期存在显著相关关系,滞后效应随时间变化而变化;年际分析能够减弱滞后效应对SPEI3与GPP相关性的影响;(2) 1900—2020年北方农牧交错区干旱历时、干旱烈度和烈度峰值均呈现显著增加趋势,干旱烈度随着干旱历时和烈度峰值的增加而加剧,干旱特征高值区往往具有更强的增加趋势;(3) 1982—2018年北方农牧交错区GPP总体呈... 相似文献
5.
10年来锡林郭勒盟草原植被长势变化及其影响因子分析 总被引：2，自引：0，他引：2
对草原植被长势变化的监测,及其与气候因子关系的分析,对生态环境治理及保护具有重要意义。本文利用250m的MODIS-NDVI数据,构建草原植被长势指数(MGI),分析了16天间隔的植被长势变化及其与降水、气温的相关性和对降水响应的滞后性。得到锡盟3种草原类型区2001-2010年草原长势变化情况,及降水、气温在草原生长不同阶段对草原长势的影响。研究结果表明:(1)在空间上长势东部变化好于中部与西部,北部好于南部;时间上2003年长势最好、2001年长势最差。(2)锡盟内3种草原类型区MGI均与降水关系明显,与气温相关性不显著,降水对温性草原区长势变化的影响最大。(3)在草原生长的不同阶段,影响因子不同,前期与后期主要受气温影响,中期主要受降水影响,草原生长对降水存在明显的滞后,一般在32-48天,同时指出草原植被在不同时间段对降水响应的滞后时间。 相似文献
6.
基于随机森林的遥感干旱监测模型的构建 总被引：1，自引：0，他引：1
利用遥感数据进行大面积旱情监测是现有干旱监测的重要方法之一,然而传统的遥感干旱监测方法主要侧重于对土壤湿度或植被状况等单一干旱响应因子进行监测,对综合多因子的干旱监测研究较为有限。随机森林是一种机器学习方法,具有学习过程快速、运算速度快、稳定性好、预测精度高的优点,近年来被应用于生态环境等多个领域。本文利用2001-2010年4-9月的MODIS数据提取的植被状态指数（VCI）、温度状态指数（TCI）和土地覆盖类型（LC）,TRMM降水资料计算的TRMM-Z指数及SRTM-DEM、土壤有效含水量（AWC）等多个遥感及土壤资料提取的干旱因子为自变量,以气象站点的综合气象干旱指数（CI）为因变量,利用随机森林模型构建遥感干旱监测模型,并以河南省为研究区进行了评价和分析。该模型在2009-2010年的监测值和实测CI值的具有显著的相关性,并且二者干旱等级的一致率为81%。在2001-2010年4-9月间,模型监测值与气象站点的标准降水蒸散发指数（SPEI）总体干旱等级一致率为74.9%,较为一致,其中9月的模型结果与SPEI的干旱等级一致率最高,达到82.4%,空评估率和漏评估率最低;与10 cm土壤相对湿度的相关系数在0.475-0.639之间,达到极显著水平。河南省2011年4-6月干旱事件同样验证了本文构建的模型旱情监测结果,说明本模型能较好地就应用于监测区域旱情监测。 相似文献
7.
青藏高原兹格塘错流域50年来湖泊水量对气候变化响应的模拟研究 总被引：3，自引：2，他引：1
运用数值模拟建立青藏高原兹格塘错流域土壤、植被、气候等的空间和属性数据库;接着,借助分布式流域尺度水文模型(SWAT模型),对兹格塘错1956—2006年间的流量进行模拟实验;最后,反演50年来兹格塘错流域水文过程,测试流域温度、降水和蒸发组合的敏感因子对湖泊水量变化的效应,探讨50年来湖泊水量对气候变化的响应。模拟实验的边界条件设置为自然地形、土壤、植被覆盖,其中土壤资料包括有机质含量、粒径等理化参数。模拟结果表明:兹格塘错的年平均流量为6.3m3/s,流量高峰集中在8月至10月,并且由于融雪补给的关系,3月出现另一个流量高峰;模拟结果与遥感解译所得到的结果吻合较好。敏感实验表明:兹格塘错流域内温度、降水和蒸发组合的敏感因子实验具有高原特征,即高原湖泊的水文过程和湖泊流量变化有着较为敏感的响应关系;兹格塘错流量受降水的影响最大,随着降水的增加,流量有所增加;在温度升高的情况下,流域蒸发量增加速度大,兹格塘错流量增加的效应不明显,而在冷湿模式下,流域蒸发量降低,兹格塘错流量增加显著。 相似文献
8.
为了充分了解“一带一路”国家和地区百年的干旱变化规律和趋势,探索其干湿变化情况,本文利用标准化降水蒸散指数SPEI（Standardized Precipitation Evaporation Index）1901-2013年12个月和3个月尺度的0.5°×0.5°数据,结合线性趋势、PCA主成分分析、Mann-Kenndall非参数检验和小波分析等方法研究多时间尺度下干旱趋势和周期变化特征。结果表明,研究区百年尺度内（1901-2013）干旱指数和面积呈现波动上升趋势,但干旱化进程缓慢,60%以上地区呈现缓慢变湿趋势,SPEI指数发生显著上升地区面积百分比为25.38%,发生显著下降地区面积仅占12.02%。MK检验和PCA分析均显示15°~35°N的中低纬度地区干旱化程度最为严重,主要地区为北非及阿拉伯半岛、伊朗高原,常年呈现显著干旱状态,而俄罗斯、哈萨克斯坦、印度半岛以及中国和蒙古两国干湿变化季节性特征明显。基于Morlet小波分析的周期分析显示,年际和季节SPEI指数的周期特征既具有相似性,又存在一定的差异性,尺度越小干湿变化交替越明显,尺度越大虽有全局特征但所展示的周期不能通过显著性检验,最终得到可用显著周期年际SPEI变化显著尺度为2~4 a,干旱特征在此尺度的周期中时间变化显著。 相似文献
9.
京津冀地区NDVI变化及气候因子驱动分析 总被引：3，自引：0，他引：3
植被覆盖动态监测及与气候变化的响应,是陆地生态系统研究的重要内容。本文以2001-2013年间京津冀地区MOD13A 3月合成NDVI数据,结合生长季的降水和气温资料,运用偏相关和复相关分析、趋势分析方法,研究了该区域NDVI的变化特征和空间分布,以及其区域植被覆盖变化的气候驱动力。结果表明,该区域NDVI最大值在13a间缓慢增加,植被覆盖呈现改善趋势;NDVI和生长季降雨量及平均气温的平均偏相关系数分别为0.20和-0.14,表明在年际变化水平上,京津冀地区NDVI总体与降水量呈正相关,与平均气温呈负相关,且降水对NDVI的影响大于温度对NDVI的影响。对植被覆盖驱动分区得出,降水和气温驱动型占区域面积的5.68%;单独降水驱动型和气温驱动型分别占4.51%、0.18%;区域内植被覆盖变化主要受非气候因子驱动型为主,所占比例为89.63%,表明人类活动对植被变化的影响巨大。 相似文献
10.
生态过程模型已成为探测陆地植被对气候变化响应的重要手段之一,最适温度作为模型模拟过程中的一个重要参数,其准确性对模型模拟结果有重要影响。本研究以2001-2010年MODIS-NDVI、2001-2010年气象台站温度数据,以及2000年土地覆盖数据,结合前人研究的成果,将最适温度定义为适宜植物生长温度上下限之间所有月均温度的均值,并从植被类型角度出发,探讨不同植物生长的最适温度,以期为生态过程模型的改进提供参数优化方案。研究表明,不同植被类型植被生长的最适温度存在较大差异。常绿针叶林、常绿阔叶林、落叶针叶林、落叶阔叶林、混交林、灌丛、草地、农田和建设用地的最适温度,依次为22.4℃、23.4℃、14.1℃、19.5℃、20.7℃、22.6℃、15.4℃、24.8℃和25.6℃。 相似文献
11.
Global climate change has been found to substantially influence the phenology of rangeland, especially on the Tibetan Plateau. However, there is considerable controversy about the trends and causes of rangeland phenology owing to different phenological exploration methods and lack of ground validation. Little is known about the uncertainty in the exploration accuracy of vegetation phenology. Therefore, in this study, we selected a typical alpine rangeland near Damxung national meteorological station as a case study on central Tibetan Plateau, and identified several important sources influencing phenology to better understand their effects on phenological exploration. We found man-made land use was not easily distinguished from natural rangelands, and therefore this may confound phenological response to climate change in the rangeland. Change trends of phenology explored by four methods were similar, but ratio threshold method (RTM) was more suitable for exploring vegetation phenology in terms of the beginning of growing season (BGS) and end of growing season (EGS). However, some adjustments are needed when RTM is used in extreme drought years. MODIS NDVI/EVI dataset was most suitable for exploring vegetation phenology of BGS and EGS. The discrimination capacities of vegetation phenology declined with decreasing resolution of remote sensing images from MODIS to GIMMS AVHRR datasets. Additionally, distinct trends of phenological change rates were indicated in different terrain conditions, with advance of growing season in high altitudes but delay of season in lower altitudes. Therefore, it was necessary to eliminate interference of complex terrain and man-made land use to ensure the representativeness of natural vegetation. Moreover, selecting the appropriate method to explore rangelands and fully considering the impact of topography are important to accurately analyze the effects of climate change on vegetation phenology. 相似文献
12.
Changes in vegetation phenology are key indicators of the response of ecosystems to climate change. Therefore, knowledge of growing seasons is essential to predict ecosystem changes, especially for regions with a fragile ecosystem such as the Loess Plateau. In this study, based on the normalized difference vegetation index (NDVI) data, we estimated and analyzed the vegetation phenology in the Loess Plateau from 2000 to 2010 for the beginning, length, and end of the growing season, measuring changes in trends and their relationship to climatic factors. The results show that for 54.84% of the vegetation, the trend was an advancement of the beginning of the growing season (BGS), while for 67.64% the trend was a delay in the end of the growing season (EGS). The length of the growing season (LGS) was extended for 66.28% of the vegetation in the plateau. While the temperature is important for the vegetation to begin the growing season in this region, warmer climate may lead to drought and can become a limiting factor for vegetation growth. We found that increased precipitation benefits the advancement of the BGS in this area. Areas with a delayed EGS indicated that the appropriate temperature and rainfall in autumn or winter enhanced photosynthesis and extended the growth process. A positive correlation with precipitation was found for 76.53% of the areas with an extended LGS, indicating that precipitation is one of the key factors in changes in the vegetation phenology in this water-limited region. Precipitation plays an important role in determining the phenological activities of the vegetation in arid and semiarid areas, such as the Loess Plateau. The extended growing season will significantly influence both the vegetation productivity and the carbon fixation capacity in this region. 相似文献
13.
An understanding 0f variati0ns in vegetati0n c0ver in resp0nse t0 climate change is critical f0r predicting and managing future terrestrial ec0system dynamics. Because scientists anticipate that m0untain ec0systems will be m0re sensitive t0 future climate change c0mpared t0 0thers, 0ur 0bjectives were t0 investigate the impacts 0f climate change 0n variati0n in vegetati0n c0ver in the Qilian M0untains （QLM）, China, between 2000 and 2011. T0 acc0mplish this, we used linear regressi0n techniques 0n 250-m MODIS N0rmalized Difference Vegetati0n Index （NDVI） datasets and mete0r0l0gical rec0rds t0 determine spati0temp0ral variability in vegetati0n c0ver and climatic fact0rs （i.e. temperature and precipitati0n）. Our results sh0wed that temperatures and precipitati0n have increased in this regi0n during 0ur study peri0d. In additi0n, we f0und that gr0wing seas0n mean NDVI was mainly distributed in the vertical z0ne fr0m 2,700 m t0 3,600 m in elevati0n. In the study regi0n, we 0bserved significant p0sitive and negative trends in vegetati0n c0ver in 26.71% and 2.27% 0f the vegetated areas. C0rrelati0n analyses indicated that rising precipitati0n fr0m May t0 August was resp0nsible f0r increased vegetati0n c0ver in areas with p0sitive trends in gr0wing seas0n mean NDVI. H0wever, there was n0 similar significant c0rrelati0n between gr0wing seas0n mean NDVI and precipitati0n in regi0ns where vegetati0n c0ver declined thr0ugh0ut 0ur study peri0d. Using spatial statistics, we f0und that veeetati0n c0ver freauentlvdeclined in areas within the 2,500-3,100 m vertical z0ne, where it has steep sl0pe, and is 0n the sunny side 0f m0untains. Here, the p0sitive influences 0f increasing precipitati0n c0uld n0t 0ffset the drier c0nditi0ns that 0ccurred thr0ugh warming trends. In c0ntrast, in higher elevati0n z0nes （3,900-4,500 m） 0n the shaded side 0f the m0untains, rising temperatures and increasing precipitati0n impr0ved c0nditi0ns f0r vegetati0n gr0wth. Increased precipitati0n als0 facilitated vegetati0n gr0wth in areas experiencing warming trends at l0wer elevati0ns （2,000-2,400 m） and 0n l0wer sl0pes where water was m0re easily c0nserved. We suggest that spatial differences in variati0n in vegetati0n as the result 0f climate change depend 0n l0cal m0isture and thermal c0nditi0ns, which are mainly c0ntr0lled by t0p0graphy （e.g. elevati0n, aspect, and sl0pe）, and 0ther fact0rs, such as l0cal hydr0l0gy. 相似文献
14.
《中国地理科学(英文版)》2019,(3)
The accurate assessment of forest damage is important basis for the forest post-disaster recovery process and ecosystem management. This study evaluates the spatial distribution of damaged forest and its damaged severity caused by ice-snow disaster that occurred in southern China during January 10 to February 2 in 2008. The moderate-resolution imaging spectroradiometer(MODIS)13 Q1 products are used, which include two vegetation indices data of NDVI(Normalized Difference Vegetation Index) and EVI(Enhanced Vegetation Index). Furtherly, after Quality Screening(QS) and Savizky-Golay(S-G) filtering of MODIS 13 Q1 data, four evaluation indices are obtained, which are NDVI with QS(QSNDVI), EVI with QS(QSEVI), NDVI with S-G filtering(SGNDVI) and EVI with S-G filtering(SGEVI). The study provides a new way of firstly determining the threshold for each image pixel for damaged forest evaluation, by computing the pre-disaster reference value and change threshold with vegetation index from remote sensing data. Results show obvious improvement with the new way for forest damage evaluation, evaluation result of forest damage is much close to the field survey data with standard error of only 0.95 and 1/3 less than the result that evaluated from other threshold method. Comparatively, the QSNDVI shows better performance than other three indices on evaluating forest damages. The evaluated result with QSNDVI shows that the severe, moderate, mild damaged rates of Southern China forests are 47.33%, 34.15%, 18.52%, respectively. By analyzing the influence of topographic and meteorological factors on forest-vegetation damage, we found that the precipitation on freezing days has greater impact on forest-vegetation damage, which is regarded as the most important factor. This study could be a scientific and reliable reference for evaluating the forest damages from ice-snow frozen disasters. 相似文献
15.
Examining the direct and indirect effects of climatic factors on vegetation growth is critical to understand the complex linkage between climate change and vegetation dynamics. Based on the Moderate Resolution Imaging Spectroradiometer(MODIS) Normalized Difference Vegetation Index(NDVI) data and meteorological data(temperature and precipitation) from 2001 to 2012, the trend of vegetation dynamics were examined in the Ziya-Daqing basins, China. The path analysis was used to obtain the information on the relationships among climatic factors and their effects on vegetation growth. It was found that the trends of growing season NDVI were insignificant in most plain dry land, while the upward trends were significant in forest, grass and dry land in Taihang Mountains. According to the path analysis, in 23% of the basins the inter-annual NDVI variation was dominated by the direct effect of precipitation, in 5% by the direct effects of precipitation and temperature, and in less than 1% by the direct effect of temperature or indirect effects of these two climatic factors. It indicated that precipitation significantly affected the vegetation growth in the whole basins, and this effect was not regulated by temperature. Precipitation increase(especially in July, August and September) was favorable to greenness enhancement. Summer temperature rising showed negative effect on plant productivity enhancement, but temperature rise in April was beneficial for the vegetation growth. When April temperature increases by 1℃, the onset date of greenness for natural vegetation will be 2 days in advance. There was a lag-time effect of precipitation or temperature on monthly NDVI for all land use types except grass. 相似文献
16.
基于2000-2013年三江源MODIS NDVI数据,本文系统地分析了三江源植被生长季累计NDVI的时空变化特征,并结合三江源生态保护与建设工程实施的相关统计数据,探讨了人类活动对三江源植被变化的影响,最后通过气候因子与生长季累计NDVI的相关性分析,揭示了影响三江源不同地区植被变化的主要气候限制因素。结果表明,2000-2013年三江源植被NDVI整体上呈增加趋势,NDVI明显增加的区域面积比例达17.84%,主要分布于研究区的西部和北部;明显减少的区域仅占0.78%,多零星分布于研究区中部;NDVI变化稳定或没有显著变化趋势的区域面积比例为59.64%,主要位于研究区东部和南部。三江源生态保护与建设工程的实施虽然促进了植被恢复,但对区域植被整体变化的影响有限,研究时段内区域植被整体好转主要受气候因素控制。西部长江源区的植被生长主要受气温影响,东北部黄河源区主要受降水制约,南部澜沧江源区降水和气温的限制性均不明显。 相似文献
17.
新疆NDVI时空特征及气候变化影响研究 总被引：1，自引：0，他引：1
基于新疆50个气象测站2003-2010年逐日降水、气温资料,结合逐月归一化植被覆盖影像资料,利用趋势分析、R/S分析、模糊C均值聚类、图像处理等方法,系统分析了全疆NDVI时空变化特征及其可持续性,并探究NDVI与气候因子（气温、降水）之间的相关性。研究表明：植被覆盖及气象因子年际间差异不大,呈现出整体稳定的态势,但年内变化明显。北疆/天山北坡水热条件优良、植被长势最好,且植被长势对气候因子的滞后效应并不明显且滞后时间短。天山南坡/天山东段次之,而南疆植被覆盖程度最差,南疆/天山南坡植被长势对气候因子（降水、气温）存在明显的滞后效应,植被生长受气温、降水限制性更大,且气温作为主要因子,对天山南坡植被生长的限制作用表现得更为突出。总体上,新疆植被覆盖呈持续性变化,现有植被覆盖情况基本保持不变,但呈退化趋势的面积大于得到改善的面积,在一定程度上与人类活动有很大关系,探查植被长势的变化趋势并及时做出相应调整,不仅能为新疆地区的植被保护以及植被恢复工作提供一定的科学依据,更能够为合理有效地安排农作物生产提供重要的理论指导。 相似文献