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1.
Using the Moderate Resolution Imaging Spectroradiometer-normalized difference vegetation index(NDVI) dataset,we investigated the patterns of spatiotemporal variation in vegetation coverage and its associated driving forces in the Qinling-Daba(Qinba) Mountains in 2000–2014.The Sen and Mann–Kendall models and partial correlation analysis were used to analyze the data,followed by calculation of the Hurst index to analyze future trends in vegetation coverage.The results of the study showed that(1) NDVI of the study area exhibited a significant increase in 2000–2014(linear tendency,2.8%/10a).During this period,a stable increase was detected before 2010(linear tendency,4.32%/10a),followed by a sharp decline after 2010(linear tendency,–6.59%/10a).(2) Spatially,vegetation cover showed a "high in the middle and a low in the surroundings" pattern.High values of vegetation coverage were mainly found in the Qinba Mountains of Shaanxi Province.(3) The area with improved vegetation coverage was larger than the degraded area,being 81.32% and 18.68%,respectively,during the study period.Piecewise analysis revealed that 71.61% of the total study area showed a decreasing trend in vegetation coverage in 2010–2014.(4) Reverse characteristics of vegetation coverage change were stronger than the same characteristics on the Qinba Mountains.About 46.89% of the entire study area is predicted to decrease in the future,while 34.44% of the total area will follow a continuously increasing trend.(5) The change of vegetation coverage was mainly attributed to the deficit in precipitation.Moreover,vegetation coverage during La Nina years was higher than that during El Nino years.(6) Human activities can induce ambiguous effects on vegetation coverage: both positive effects(through implementation of ecological restoration projects) and negative effects(through urbanization) were observed.  相似文献   

2.
The Three-River Headwaters Region(TRHR), which is the source area of the Yangtze River, Yellow River, and Lancang River, is of key importance to the ecological security of China. Because of climate changes and human activities, ecological degradation occurred in this region. Therefore, "The nature reserve of Three-River Source Regions" was established, and "The project of ecological protection and construction for the Three-River Headwaters Nature Reserve" was implemented by the Chinese government. This study, based on MODIS-NDVI and climate data, aims to analyze the spatiotemporal changes in vegetation coverage and its driving factors in the TRHR between 2000 and 2011, from three dimensions. Linear regression, Hurst index analysis, and partial correlation analysis were employed. The results showed the following:(1) In the past 12 years(2000–2011), the NDVI of the study area increased, with a linear tendency being 1.2%/10a, of which the Yangtze and Yellow River source regions presented an increasing trend, while the Lancang River source region showed a decreasing trend.(2) Vegetation coverage presented an obvious spatial difference in the TRHR, and the NDVI frequency was featured by a bimodal structure.(3) The area with improved vegetation coverage was larger than the degraded area, being 64.06% and 35.94%, respectively during the study period, and presented an increasing trend in the north and a decreasing trend in the south.(4) The reverse characteristics of vegetation coverage change are significant. In the future, degradation trends will be mainly found in the Yangtze River Basin and to the north of the Yellow River, while areas with improving trends are mainly distributed in the Lancang River Basin.(5) The response of vegetation coverage to precipitation and potential evapotranspiration has a time lag, while there is no such lag in the case of temperature.(6) The increased vegetation coverage is mainly attributed to the warm-wet climate change and the implementation of the ecological protection project.  相似文献   

3.
Different government departments and researchers have paid considerable attention at various levels to improving the eco-environment in ecologically fragile areas. Over the past decade, large numbers of people have emigrated from rural areas as a result of the rapid urbanization in Chinese society. The question then remains: to what extent does this migration affect the regional vegetation greenness in the areas that people have moved from Based on normalized difference vegetation index(NDVI) data with a resolution of 1 km, as well as meteorological data and socio-economic data from 2000 to 2010 in Inner Mongolia, the spatio-temporal variation of vegetation greenness in the study area was analyzed via trend analysis and significance test methods. The contributions of human activities and natural factors to the variation of vegetation conditions during this period were also quantitatively tested and verified, using a multi-regression analysis method. We found that:(1) the vegetation greenness of the study area increased by 10.1% during 2000–2010. More than 28% of the vegetation greenness increased significantly, and only about 2% decreased evidently during the study period.(2) The area with significant degradation showed a banded distribution at the northern edge of the agro-pastoral ecotone in central Inner Mongolia. This indicates that the eco-environment is still fragile in this area, which should be paid close attention. The area where vegetation greenness significantly improved showed a concentrated distribution in the southeast and west of Inner Mongolia.(3) The effect of agricultural labor on vegetation greenness exceeded those due to natural factors(i.e. precipitation and temperature). The emigration of agricultural labor improved the regional vegetation greenness significantly.  相似文献   

4.
To understand the variations in vegetation and their correlation with climate factors in the upper catchments of the Yellow River, China, Normalized Difference Vegetation Index(NDVI) time series data from 2000 to 2010 were collected based on the MOD13Q1 product. The coefficient of variation, Theil–Sen median trend analysis and the Mann–Kendall test were combined to investigate the volatility characteristic and trend characteristic of the vegetation. Climate data sets were then used to analyze the correlation between variations in vegetation and climate change. In terms of the temporal variations, the vegetation in this study area improved slightly from 2000 to 2010, although the volatility characteristic was larger in 2000–2005 than in 2006–2010. In terms of the spatial variation, vegetation which is relatively stable and has a significantly increasing trend accounts for the largest part of the study area. Its spatial distribution is highly correlated with altitude, which ranges from about 2000 to 3000 m in this area. Highly fluctuating vegetation and vegetation which showed a significantly decreasing trend were mostly distributed around the reservoirs and in the reaches of the river with hydropower developments. Vegetation with a relatively stable and significantly decreasing trend and vegetation with a highly fluctuating and significantly increasing trend are widely dispersed. With respect to the response of vegetation to climate change, about 20–30% of the vegetation has a significant correlation with climatic factors and the correlations in most areas are positive: regions with precipitation as the key influencing factor account for more than 10% of the area; regions with temperature as the key influencing factor account for less than 10% of the area; and regions with precipitation and temperature as the key influencing factors together account for about 5% of the total area. More than 70% of the vegetation has an insignificant correlation with climatic factors.  相似文献   

5.
The Three-River Headwaters Region (TRHR), which is the source area of the Yangtze River, Yellow River, and Lancang River, is of key importance to the ecological secu- rity of China. Because of climate changes and human activities, ecological degradation oc- curred in this region. Therefore, "The nature reserve of Three-River Sou,'ce Regions" was established, and "The project of ecological protection and construction for the Three-River Headwaters Nature Reserve" was implemented by the Chinese government. This study, based on MODIS-NDVI and climate data, aims to analyze the spatiotemporal changes in vegetation coverage and its driving factors in the TRHR between 2000 and 2011, from three dimensions. Linear regression, Hurst index analysis, and partial correlation analysis were employed. The results showed the following: (1) In the past 12 years (2000-2011), the NDVI of the study area increased, with a linear tendency being 1.2%/10a, of which the Yangtze and Yellow River source regions presented an increasing trend, while the Lancang River source region showed a decreasing trend. (2) Vegetation coverage presented an obvious spatial difference in the TRHR, and the NDVI frequency was featured by a bimodal structure. (3) The area with improved vegetation coverage was larger than the degraded area, being 64.06% and 35.94%, respectively during the study period, and presented an increasing trend in the north and a decreasing trend in the south. (4) The reverse characteristics of vegetation cov- erage change are significant. In the future, degradation trends will be mainly found in the Yangtze River Basin and to the north of the Yellow River, while areas with improving trends are mainly distributed in the Lancang River Basin. (5) The response of vegetation coverage to precipitation and potential evapotranspiration has a time lag, while there is no such lag in the case of temperature. (6) The increased vegetation coverage is mainly attributed to the warm-wet climate change and the implementation of the ecological protection project.  相似文献   

6.
To understand the variations in vegetation and their correlation with climate factors in the upper catchments of the Yellow River, China, Normalized Difference Vegetation Index(NDVI) time series data from 2000 to 2010 were collected based on the MOD13Q1 product. The coefficient of variation, Theil–Sen median trend analysis and the Mann–Kendall test were combined to investigate the volatility characteristic and trend characteristic of the vegetation. Climate data sets were then used to analyze the correlation between variations in vegetation and climate change. In terms of the temporal variations, the vegetation in this study area improved slightly from 2000 to 2010, although the volatility characteristic was larger in 2000–2005 than in 2006–2010. In terms of the spatial variation, vegetation which is relatively stable and has a significantly increasing trend accounts for the largest part of the study area. Its spatial distribution is highly correlated with altitude, which ranges from about 2000 to 3000 m in this area. Highly fluctuating vegetation and vegetation which showed a significantly decreasing trend were mostly distributed around the reservoirs and in the reaches of the river with hydropower developments. Vegetation with a relatively stable and significantly decreasing trend and vegetation with a highly fluctuating and significantly increasing trend are widely dispersed. With respect to the response of vegetation to climate change, about 20–30% of the vegetation has a significant correlation with climatic factors and the correlations in most areas are positive: regions with precipitation as the key influencing factor account for more than 10% of the area; regions with temperature as the key influencing factor account for less than 10% of the area; and regions with precipitation and temperature as the key influencing factors together account for about 5% of the total area. More than 70% of the vegetation has an insignificant correlation with climatic factors.  相似文献   

7.
Soil erosion is a major threat to our terrestrial ecosystems and an important global environmental problem. The Loess Plateau in China is one of the regions that suffered more severe soil erosion and undergoing climate warming and drying in the past decades. The vegetation restoration named Grain-to-Green Program has now been operating for more than 10 years. It is necessary to assess the variation of soil erosion and the response of precipita- tion and vegetation restoration to soil erosion on the Loess Plateau. In the study, the Revised Universal Soil Loss Equation (RUSLE) was applied to evaluate annual soil loss caused by water erosion. The results showed as follows. The soil erosion on the Loess Plateau between 2000 and 2010 averaged for 15.2 t hm-2 a 1 and was characterized as light for the value less than 25 t hm-2 a-1. The severe soil erosion higher than 25 t hm-2 a-~ was mainly distributed in the gully and hilly regions in the central, southwestern, and some scattered areas of earth-rocky mountainous areas on the Loess Plateau. The soil erosion on the Loess Plateau showed a deceasing trend in recent decade and reduced more at rates more than 1 t hm 2 a 1 in the areas suffering severe soil loss. Benefited from the improved vegetation cover and ecological construction, the soil erosion on the Loess Plateau was significantly declined, es- pecially in the east of Yulin, most parts of Yah'an prefectures in Shaanxi Province, and the west of Luliang and Linfen prefectures in Shanxi Province in the hilly and gully regions. The variation of vegetation cover responding to soil erosion in these areas showed the relatively higher contribution than the precipitation. However, most areas in Qingyang and Dingxi pre- fectures in Gansu Province and Guyuan in Ningxia Hui Autonomous Region were predomi- nantly related to precipitation.  相似文献   

8.
The Qinling Mountains, located at the junction of warm temperate and subtropical zones, serve as the boundary between north and south China. Exploring the sensitivity of the response of vegetation there to hydrothermal dynamics elucidates the dynamics and mechanisms of the main vegetation types in the context of changes in temperature and moisture. Importance should be attached to changes in vegetation in different climate zones. To reveal the sensitivity and areal differentiation of vegetation responses to hydrothermal dynamics, the spatio-temporal variation characteristics of the normalized vegetation index(NDVI) and the standardized precipitation evapotranspiration index(SPEI) on the northern and southern slopes of the Qinling Mountains from 2000 to 2018 are explored using the meteorological data of 32 meteorological stations and the MODIS NDVI datasets. The results show that: 1) The overall vegetation coverage of the Qinling Mountains improved significantly from 2000 to 2018. The NDVI rise rate and area ratio on the southern slope were higher than those on the northern slope, and the vegetation on the southern slope improved more than that on the northern slope. The Qinling Mountains showed an insignificant humidification trend. The humidification rate and humidification area of the northern slope were greater than those on the southern slope. 2) Vegetation on the northern slope of the Qinling Mountains was more sensitive to hydrothermal dynamics than that on the southern slope. Vegetation was most sensitive to hydrothermal dynamics from March to June on the northern slope, and from March to May(spring) on the southern slope. The vegetation on the northern and southern slopes was mainly affected by hydrothermal dynamics on a scale of 3–7 months, responding weakly to hydrothermal dynamics on a scale of 11–12 months. 3) Some 90.34% of NDVI and SPEI was positively correlated in the Qinling Mountains. Spring humidification in most parts of the study area promoted the growth of vegetation all the year round. The sensitivity of vegetation responses to hydrothermal dynamics with increasing altitude increased first and then decreased. Elevations of 800 to 1200 m were the most sensitive range for vegetation response to hydrothermal dynamics. The sensitivity of the vegetation response at elevations of 1200–3000 m decreased with increasing altitude. As regards to vegetation type, grass was most sensitive to hydrothermal dynamics on both the northern and southern slopes of the Qinling Mountains; but most other vegetation types on the northern slope were more sensitive to hydrothermal dynamics than those on the southern slope.  相似文献   

9.
The normalized difference vegetation index (NDVI) is used extensively to describe vegetation cover and ecological environ- ment change. The purpose of this study was to contrast the response of different tree species growing in the same habitat to climate change and retrieve past NDVI using tree-ring width data from tree cores collected from the transitional zone of Pinus tabulaeformis and Picea crassifolia in the Luoshan Mountains in the middle arid region of Ningxia. Correlation analysis indi- cated that radial growth ofP tabulaeJbrmis is more sensitive to precipitation and temperature change than that ofP crassifolia. Natural factors such as water availability and heat at this elevation are more suited to the growth ofP crassifolia, and are more advantageous to its renewal and succession. P. crassifolia is probably the better of the two species for protecting the forest ecosystem and conserving water in the Luoshan desertification area. Ring width of P. crassifolia correlates significantly with average NDVI for April-May (r =0.641, p 〈0.01), and both of them are influenced positively by precipitation in April-May. The reconstructed NDVI for 1923-2007 shows the relatively low vegetation cover occurred in the 1920s-1930s, the 1960s-1970s, and the early 21 st century. The reconstructed NDVI better reflected the drought climate in the study area.  相似文献   

10.
青藏高原植被覆盖变化与降水关系   总被引:15,自引:6,他引:9  
The temporal and spatial changes of NDVI on the Tibetan Plateau, as well as the relationship between NDVI and precipitation, were discussed in this paper, by using 8-km resolution multi-temporal NOAA AVHRR-NDVI data from 1982 to 1999. Monthly maximum NDVI and monthly rainfall were used to analyze the seasonal changes, and annual maximum NDVI, annual effective precipitation and growing season precipitation (from April to August) were used to discuss the interannual changes. The dynamic change of NDVI and the corre- lation coefficients between NDVI and rainfall were computed for each pixel. The results are as follows: (1) The NDVI reached the peak in growing season (from July to September) on the Tibetan Plateau. In the northern and western parts of the plateau, the growing season was very short (about two or three months); but in the southern, vegetation grew almost all the year round. The correlation of monthly maximum NDVI and monthly rainfall varied in different areas. It was weak in the western, northern and southern parts, but strong in the central and eastern parts. (2) The spatial distribution of NDVI interannual dynamic change was different too. The increase areas were mainly distributed in southern Tibet montane shrub-steppe zone, western part of western Sichuan-eastern Tibet montane coniferous forest zone, western part of northern slopes of Kunlun montane desert zone and southeastern part of southern slopes of Himalaya montane evergreen broad-leaved forest zone; the decrease areas were mainly distributed in the Qaidam montane desert zone, the western and northern parts of eastern Qinghai-Qilian montane steppe zone, southern Qinghai high cold meadow steppe zone and Ngari montane desert-steppe and desert zone. The spatial distribution of correlation coeffi- cient between annual effective rainfall and annual maximum NDVI was similar to the growing season rainfall and annual maximum NDVI, and there was good relationship between NDVI and rainfall in the meadow and grassland with medium vegetation cover, and the effect of rainfall on vegetation was small in the forest and desert area.  相似文献   

11.
The “Grain for Green Project” initiated by the governments since 1999 were the dominant contributors to the vegetation restoration in the agro-pastoral transitional zone of northern China. Climate change and human activities are responsible for the improvement and degradation to a certain degree. In order to monitor the vegetation variations and clarify the causes of rehabilitation in the Shaanxi-Gansu-Ningxia Region, this paper, based on the MODIS-NDVI and climate data during the period of 2000-2009, analyzes the main characteristics, spatial-temporal distribution and reasons of vegetation restoration, using methods of linear regression, the Hurst Exponent, standard deviation and other methods. Results are shown as follows. (1) From 2000 to 2009, the NDVI of the study area was improved progressively, with a linear tendency being 0.032/10a, faster than the growth of the Three-North Shelter Forest Program (0.007/10a) from 1982 to 2006. (2) The vegetation restoration is characterized by two fast-growing periods, with an “S-shaped” increasing curve. (3) The largest proportion of the contribution to vegetation restoration was observed in the slightly improved area, followed by the moderate and the significantly improved area; the degraded area is distributed sporadically over southern part of Ningxia Hui Autonomous Region as well as eastern Dingbian of Shaanxi province, Huanxian and Zhengyuan of Gansu province. (4) Climate change and human activities are two driving forces in vegetation restoration; moreover anthropogenic factors such as “Grain for Green Project” were the main causes leading to an increasing trend of NDVI on local scale. However, its influencing mechanism remains to be further investigated. (5) The Hurst Exponent of NDVI time series shows that the vegetation restoration was sustainable. It is expected that improvement in vegetation cover will expand to the most parts of the region.  相似文献   

12.
近10 年陕甘宁黄土高原区植被覆盖时空变化特征   总被引:45,自引:4,他引:41  
李双双  延军平  万佳 《地理学报》2012,67(7):960-970
基于2000-2009 年MODIS-NDVI 植被覆盖指数, 采用线性趋势分析、Hurst 指数和偏相关系数等数理分析方法, 对陕甘宁地区“退耕还林还草”实施10a 来植被覆盖时空变化特征、影响因素及其未来变化趋势进行分析。结果表明:① 2000-2009 年陕甘宁地区植被覆盖呈现明显增加趋势0.032/10a, 远快于三北防护林工程区1982-2006 年植被覆盖平均增速0.007/10a;② 陕甘宁地区植被恢复具有阶段性, 整体呈“S”型增长, 具有两次明显的植被高恢复期;③ 陕甘宁地区植被恢复以轻微改善为主, 中度改善次之, 呈退化趋势区域比重较小(2.38%), 零星分布于宁南八县、定边东部、甘肃陇东的环县和镇原;④ 陕甘宁地区植被覆盖度逐年提高、生态环境持续改善是人类活动和气候变化共同驱动, 其中人类经济活动作用明显;⑤ 陕甘宁地区植被恢复具有一定的持续性, 未来大部分区域将持续改善, 退化区集中分布于陕北中东部、“彭阳-镇原”南部以及盐池北部。  相似文献   

13.
黄土高原植被恢复潜力研究   总被引:23,自引:1,他引:22  
黄土高原从1999年开始大规模退耕还林(草),植被覆盖发生了较大变化,对黄土高原植被恢复现状和恢复潜力进行评估具有重要意义。本文使用1999-2013年SPOT VEG NDVI数据,采用线性回归、Hurst指数分析法、统计学方法以及地理空间分析技术,对黄土高原植被恢复状况和潜力进行了探讨。结论主要为:① 1999年退耕还林(草)以来,黄土高原植被覆盖度呈显著上升趋势,黄土高原三分之二地区的植被将会持续改善;② 植被响应曲线分析表明,黄土区植被覆盖度和干旱指数呈显著的指数关系,且缓坡相关性大于陡坡。土石山区植被响应函数为线性函数,相关系数下降;③ 整个黄土高原地区平均植被恢复潜力为69.75%。植被恢复潜力值东南高而西北低,黄土高原东南地区植被恢复状况较好,其植被恢复潜力指数较小,而植被恢复潜力指数较高的地区主要为北方风沙区及西部丘陵沟壑区;④ 不同降水量条件下,植被恢复速度差别显著,其中降水量在375~575 mm之间的地区,植被恢复最快。植被恢复措施应该“因水制宜”,避免因造林带来的土壤干化加剧。研究结果以期为黄土高原生态文明建设提供科学支撑。  相似文献   

14.
2000—2016年黄土高原不同土地覆盖类型植被NDVI时空变化   总被引:3,自引:1,他引:3  
了解植被覆盖的时空变化对区域环境保护及生态环境建设具有重要意义。基于MOD13A1数据,辅以Sen+Mann-Kendall、变异系数、Hurst指数,通过分析2000—2016年间黄土高原NDVI年最大值(NDVIymax)和生长季均值(NDVIgsmean)时空变化特征及趋势,以了解黄土高原实施退耕还林(草)等生态工程后的植被覆盖恢复情况。结果表明:① 2000—2016年植被NDVIymax和NDVIgsmean呈现波动式增长趋势,增长率分别为0.0070/a(P<0.01)和0.0063/a(P<0.01),生态环境整体不断改善。② NDVIymax和NDVIgsmean显示黄土高原植被覆盖呈增加趋势的面积远高于呈减少趋势的面积(93.42%和96.22%、6.58%和3.78%),植被覆盖状态正在不断改善。2种数据变化趋势下,不同土地覆盖类型表现略有差异,森林极显著增加趋势面积最大(73.02%和82.60%),其次为耕地(47.87%和67.43%),再次为裸地(47.03%和61.68%)。③ NDVIgsmean的变异系数小于NDVIymax的变异系数,相对稳定区域面积比分别为63.31%与56.64%,2种数据分析下森林变异系数最小,植被稳定性最好。④ 从植被NDVI变化趋势与Hurst组合结果得出,NDVIymax未来呈现改善趋势面积占41.35%,退化趋势面积占58.65%;NDVIgsmean呈现改善趋势面积占49.19%,退化趋势面积占50.81%。2种数据下,灌木地未来发展趋势最好,森林和耕地退化趋势面积超过了50%。研究人员应持续关注退化趋势地区的植被状态。  相似文献   

15.
Using the Moderate Resolution Imaging Spectroradiometer-normalized difference vegetation index (NDVI) dataset, we investigated the patterns of spatiotemporal variation in vegetation coverage and its associated driving forces in the Qinling-Daba (Qinba) Mountains in 2000–2014. The Sen and Mann–Kendall models and partial correlation analysis were used to analyze the data, followed by calculation of the Hurst index to analyze future trends in vegetation coverage. The results of the study showed that (1) NDVI of the study area exhibited a significant increase in 2000–2014 (linear tendency, 2.8%/10a). During this period, a stable increase was detected before 2010 (linear tendency, 4.32%/10a), followed by a sharp decline after 2010 (linear tendency,–6.59%/10a). (2) Spatially, vegetation cover showed a “high in the middle and a low in the surroundings” pattern. High values of vegetation coverage were mainly found in the Qinba Mountains of Shaanxi Province. (3) The area with improved vegetation coverage was larger than the degraded area, being 81.32% and 18.68%, respectively, during the study period. Piecewise analysis revealed that 71.61% of the total study area showed a decreasing trend in vegetation coverage in 2010–2014. (4) Reverse characteristics of vegetation coverage change were stronger than the same characteristics on the Qinba Mountains. About 46.89% of the entire study area is predicted to decrease in the future, while 34.44% of the total area will follow a continuously increasing trend. (5) The change of vegetation coverage was mainly attributed to the deficit in precipitation. Moreover, vegetation coverage during La Nina years was higher than that during El Nino years. (6) Human activities can induce ambiguous effects on vegetation coverage: both positive effects (through implementation of ecological restoration projects) and negative effects (through urbanization) were observed.  相似文献   

16.
张艳芳  王姝 《干旱区地理》2017,40(1):138-146
基于2000-2014年MODIS NDVI数据及气象数据,运用累计降水利用效率变化差异(CRD,cumulative rain use efficiency differences)估算模型和基于地形要素降水量插值法,探讨2000-2014年黄土高原RUE(降水利用效率rain use efficiency)对植被变化的响应,以期为黄土高原生态可持续发展提供数据支撑。结果表明:黄土高原大部分地区植被覆盖得以改善,其面积约占总面积的81%,区域边缘植被覆盖退化严重。黄土高原降水利用效率RUE与累计NDVI的相关性总体表现为“东南呈正相关,西北为负相关”的空间格局,全区相关系数以正相关为主。黄土高原CRD与植被变化趋势的相关性显著,其中,植被退化背景下,植被退化程度越严重,RUE越低;植被恢复背景下,RUE受“退耕还林还草”作用显著,2000-2005年,RUE呈上升趋势,2007年后,随着退耕还林还草政策的工作重心转移,RUE呈波动变化。  相似文献   

17.
基于MOD13Q1数据的宁夏生长季植被动态监测   总被引:1,自引:0,他引:1  
宁夏自2000年后实施退耕还林以来,局部地区的生态环境得到明显改善,为探求近15来年宁夏地区植被的动态变化及其影响因子,本文以MOD13Q1为数据源,结合DEM数据、土地利用分类图,采用Sen+Mann-Kendall非参数检验方法和Hurst模型,分析了宁夏不同行政区、不同海拔、不同坡度、不同坡向及不同植被类型生长季NDVI的空间变化特征及未来变化趋势;并利用重心迁移模型和转移矩阵分析宁夏2000-2014年间植被覆盖的时空演变特征。结果表明:①从空间分布看,宁夏南部六盘山、北部贺兰山及引黄灌溉区植被长势较好,中部干旱地区植被长势较差;且植被NDVI与海拔高程和坡度呈显著正相关。②从植被覆盖的转移矩阵看,较高植被覆盖的面积占比从2000年的17.29%增长到2014年的31.55%,主要是由较低植被覆盖转化而来的。③从重心迁移方向看,中度植被覆盖和较高植被覆盖的重心迁移最为明显,分别向东北方向偏移了129.49 km和向东南方向偏移了89.49 km。④从变化趋势看,生长季植被NDVI整体呈上升趋势,明显改善的面积占总面积的59.63%,轻微改善区域占31.72%;林地和水田显著改善的面积分别占总面积的71.50%和70.80%;显著改善的面积比例随海拔高程和坡度的增加均先增加后减少,且南部各行政区植被改善的面积均高于北部。⑤从可持续性看,植被恢复的持续性较强,89.24%的植被NDVI呈现持续改善的趋势;南部地区的持续改善的面积大于北部地区。  相似文献   

18.
刘宇  傅伯杰 《干旱区地理》2013,36(6):1097-1102
基于16 d合成MODIS NDVI数据提取的时间序列植被覆盖度数据,采用一元线性回归趋势分析,对黄土高原2000-2008年植被覆盖度的时空变化及其地形分异、土地利用/覆被变化的影响进行了定量分析。结果表明:(1)研究时段黄土高原植被覆盖度整体呈快速上升趋势,局部下降;(2)黄土高原植被覆盖度变化存在明显的地形分异,陡坡等植被恢复、重建和保育的主要区域植被覆盖度增速显著;(3)土地利用/覆被变化对植被覆盖度的增加影响突出,土地利用/覆被类型变更区植被覆盖度增速显著高于未变化区域,退耕还林还草区增速尤其突出;(4)土地利用/覆被类型未变化区域植被覆盖度总体上也呈增加趋势,但因植被覆盖度水平相对较高,增速明显低于土地利用/覆被类型变化区。上述结果表明,黄土高原植被保育、植被恢复和重建在植被覆盖度提升方面取得了明显成效。  相似文献   

19.
2000-2011 年三江源区植被覆盖时空变化特征   总被引:18,自引:0,他引:18  
基于MODIS-NDVI 数据,辅以线性趋势分析、Hurst 指数及偏相关系数等方法,本文从三个尺度分析了近12 年三江源区植被覆盖时空变化特征、未来趋势及其驱动因素。结果表明:(1) 近12 年三江源区植被覆盖呈现增加趋势,增速为1.2%/10a,其中长江源区、黄河源区植被均呈增加趋势,而澜沧江源区植被呈下降趋势。(2) 三江源区植被覆盖具有显著的区域差异,且NDVI频度呈现“双峰”结构。(3) 近12 年三江源区植被覆盖呈增加趋势和减少趋势的面积分别占64.06%和35.94%,且表现为源区北部增加、南部减少的空间格局。(4) 三江源区植被变化的反向特征显著,植被变化由改善趋势转为退化趋势的区域主要分布在长江源区和黄河源区的北部,而由退化趋势转为改善趋势的区域主要分布在澜沧江源区。(5) 三江源区植被对降水和潜在蒸散的响应存在时滞现象,而对气温的响应不存在时滞现象。(6) 三江源区植被覆盖的增加主要归因于气候暖湿化以及生态保护工程的实施。  相似文献   

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