2001年～2010年重庆地区植被NPP时空变化特征及其与气候因子的关系

以2001年～2010年MOD17A3的年均NPP数据为基础,利用GIS技术定量分析了重庆地区植被NPP的时空变化特征及与气候因子的相关性,结果表明:2001年～2010年重庆地区植被NPP整体呈微弱上升趋势,植被覆盖略有增加,且总体分布呈现从南到北递减的趋势;重庆地区植被NPP增加幅度由南到北递减且整体变化幅度较小,仅部分区县变化幅度较大.不同的植被类型的NPP存在差异,其NPP大小顺序为:常绿阔叶林＞草地＞农田植被＞混生林＞常绿针叶林＞落叶阔叶林＞落叶针叶林＞灌丛.就气候因子与植被NPP的相关性而言,NPP与气温的相关性不明显,NPP与降水的相关显著性存在空间差异.     

基于多时相遥感数据的徐州市植被净初级生产力估算及相关性分析

以遥感数据和气象数据为主要数据源,应用改进的光能利用率模型估算徐州市2006、2008和2010年3年间6月份的植被净初级生产力(Net Primary Productivity,NPP),研究了该区域6月份NPP的时空变化及其与气象因子的相关性。结果表明：时间上,受气候和环境等因素综合变化的影响,研究区域6月份NPP呈逐年下降趋势;空间上,NPP的分布表现为在林地、草地和农田相对集中的区域偏高,且不同植被类型6月份的NPP大小关系在不同年份可能不同,其中在2006和2008年为农田>草地>林地,而2010年为农田>林地>草地。通过分析与气象因子的相关性和偏相关性,限制NPP的主要气象因子不是固定不变的,其中2006和2008年,限制NPP的主要气象因子为太阳辐射,而2010年为降雨量和温度。不同植被类型下NPP与气象因子相关性和偏相关性差异反映了不同类型植被生长对光、热、水条件要求的差异。
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中亚地区植被净初级生产力时空动态及其与气候因子关系

植被净初级生产力(Net Primary Productivity,NPP)及其对气候变化的响应是全球变化的核心研究内容之一,研究中亚地区NPP的时空格局变化对理解植被—环境的作用机理以及应对全球变化具有重要的意义。基于MOD17A3数据集、气象数据结合GIS分析方法研究中亚地区2000~2014年的植被NPP时空动态特征及其与气候因子的关系。结果表明：①中亚地区空间上NPP的变化范围在0~874 gC/m²·a之间,平均值为151.90 gC/m²·a,NPP年总量平均值为482.41TgC (1 Tg=10¹² g),NPP平均值与总量均呈现出下降趋势;②中亚地区NPP的高值区主要分布在高纬度地区和东南部高山地区,中部和南部荒漠区则为NPP的低值区;③中亚地区2000~2014年间NPP在空间上总体呈现下降趋势,达到显著下降的区域总体面积的39.89%。NPP呈下降趋势的区域主要集中在哈萨克斯坦的大部分区域,不同分区内以典型草原区最为显著;④中亚地区NPP受降水量的影响作用高于气温,荒漠草原区、典型草原区以及荒漠区主要受到降水量的控制,高山草甸区与高山林地区则受到降水和气温的共同作用。     

近10年榆林市植被净初级生产力时空分异特征

针对榆林市生态环境脆弱,植被净初级生产力分布及变化对其影响较大的问题,利用2000年、2005年和2010年的NPP数据,采用马尔科夫转移矩阵及GIS空间分析功能,揭示榆林市NPP的时空变化特征。结果表明:(1)榆林市NPP空间分布由西北向东南逐渐递增。(2)2000年~2010年NPP呈显著上升趋势:2000年~2005年NPP升高区域95.03%,增幅大于300gC/(m2·a)的占47.22%,主要分布在榆林市最北端和南部地区;2005年~2010年NPP升高区域面积93.96%,增幅大于300gC/(m2·a)的占54.10%,集中在东南大部分地区。(3)榆林市NPP增加的主要因素是1999年以来该区采取的多项植被恢复与重建工程等措施,植被覆盖度增加。     

基于RS和GIS的上海市植被覆盖变化特征研究

利用1997、2000和2002年的Landsat TM/ETM 遥感数据,计算了归一化差异植被指数(NDVI)并剔除植被伪变化信息,同时结合GIS空间分析功能较为详细地研究了近几年来上海城市植被覆盖的动态演变特征.结果表明:市区植被覆盖变化不大,面积总体呈现增加趋势;与市区相比,郊区的植被覆盖变化较为明显且减少面积较多;植被减少部分主要为耕地,主要对应城镇和工业用地的扩展区,增加部分主要是林地和草地;市区和浦东新区一些工矿用地和未利用地转化为草地在很大程度上增加了植被面积.     

近10年榆林市植被净初级生产力时空分异特征

针对榆林市生态环境脆弱,植被净初级生产力分布及变化对其影响较大的问题,利用2000年、2005年和2010年的NPP数据,采用马尔科夫转移矩阵及GIS空间分析功能,揭示榆林市NPP的时空变化特征。结果表明：（1）榆林市NPP空间分布由西北向东南逐渐递增。（2）2000年～2010年NPP呈显著上升趋势：2000年～2005年NPP升高区域95.03%,增幅大于300gC/（m2·a）的占47.22%,主要分布在榆林市最北端和南部地区;2005年～2010年NPP升高区域面积93.96%,增幅大于300gC/（m2·a）的占54.10%,集中在东南大部分地区。（3）榆林市NPP增加的主要因素是1999年以来该区采取的多项植被恢复与重建工程等措施,植被覆盖度增加。     

植被功能型差异对地表反照率时空分布的影响分析

地表反照率是表征地球表面捕获太阳辐射能力的特征参量,是影响气候系统的关键因素。植被通过物理(反照率)和生物过程(蒸散)影响陆地区域的能量收支过程,进而调控区域气候特征,其中陆表植被的变化及其可能的反照率影响规律受到了研究者的重视。以北京地区为例,利用MODIS地表反照率产品,结合地表覆盖类型产品中的植被功能型数据,计算并分析了2008~2013年北京地区典型植被功能型差异对地表反照率时空分布的影响。结果表明:北京地区典型植被功能型共6种,按其平均地表反照率从大到小依次为:谷物作物、城市用地、灌丛、落叶阔叶林、常绿针叶林及水体。因不同植被功能型的分布及变化对地表反照率的时空分布有直接影响,北京地区平均地表反照率总体呈东高西低、南高北低趋势,秋季最小,冬季次之,春、夏较大,且2008~2013年地表反照率呈现变化量约为-0.79×10-3/a的缓慢减小趋势。     

太湖流域植被NPP时空特征及其驱动因素研究

为了探究太湖流域植被净初级生产力(net primary productivity, NPP)2000—2019年的时空动态变化,定量识别其驱动因素并分析其影响,采用趋势分析、Hurst指数等方法研究了2000—2019年太湖流域植被NPP的时空变化特点,并结合气象、土地、人口等数据,运用相关性分析、地理探测器方法等从两方面揭示其驱动因素。结果表明：流域植被NPP多年均值呈波动上升趋势,空间上表现为西南高、中东部低的分布格局;未来流域植被NPP可能会以反持续性趋势为主,即会有所下降;气候因子与NPP的相关性不显著,土地利用变化是造成植被NPP流失的主要因素之一;单因子驱动中,土地利用变化对植被NPP的解释力最强,双因子则是以土地利用和降水因子的交互作用为主。     

基于MODIS和AVHRR数据源的东北地区植被NDVI变化及其与气温和降水间的相关分析 

基于逐像元一元线性回归模型,应用MODIS NDVI数据对AVHRR-GIMMS NDVI进行时间序列拓展,拓展序列通过一致性检验,基于所建立的1982~2009年植被年最大NDVI数据集,在GIS平台上进行了植被NDVI变化和NDVI与年平均气温、年降水量之间的相关分析。研究结果表明:过去28 a间,植被年最大NDVI呈3个变化阶段:1982~1992年呈小幅上升趋势,1992~2006年呈缓慢下降趋势,2006~2009年呈缓慢回升态势。由空间变异分析得出NDVI变化相对大的区域主要分布在内蒙干旱和半干旱区。21世纪初和20世纪90年代相对于80年代NDVI值升高,3个阶段平均NDVI变化幅度为±0.3。 20世纪初,赤峰地区以及松嫩平原西部地区植被NDVI呈轻度增加的面积占全区6.45%。植被年最大NDVI与年平均气温、年降水量相关性空间差异明显。偏相关系数绝对值,气温大于降水的像元数占54%;综合分析,较降水而言,气温是东北全区植被年最大NDVI的主控影响因子。对于不同植被类型年最大NDVI,受气温影响强度由大到小依次为:森林>草地>沼泽湿地>灌丛>耕地;受降水影响按草地>耕地>灌丛>沼泽湿地>森林依次减弱。     

基于遥感和气象数据的东南亚森林动态变化分析

为进一步了解热带森林动态变化与人类活动及气候变化之间的关系,利用MODIS遥感数据和ERA-Interim再分析气象数据,通过时间序列分析和相关性分析,得到2001～2013年东南亚地区11个国家的森林净初级生产力(NPP)时空变化情况及其与植被覆盖率(VCF)、温度、降水和光合有效辐射(PAR)的相关关系。结果表明:①东南亚地区森林NPP呈现由赤道向南北两极方向增加的趋势;②研究区大部分区域NPP呈减少趋势,NPP变化较剧烈的地区变异系数一般较大,生态系统的固碳能力不稳定;③研究区整体森林覆盖率较高(60%～80%),2001～2013年间大部分区域VCF呈增加趋势,部分地区VCF与NPP的偏相关系数较相关系数高,表明NPP受人类活动影响大;④东南亚地区温度、降水和PAR都较高,热带雨林气候国家较热带季风气候国家森林NPP与气候因子具有更好的相关性,一般与温度呈负相关,与降水和PAR呈正相关。     

Effects of topography and human activity on the net primary productivity (NPP) of alpine grassland in northern Tibet from 1981 to 2004

Using the Carnegie–Ames–Stanford Approach (CASA) model on remote-sensing (RS), climatic, and other related data from 1981 to 2004, the researchers estimated the net primary productivity (NPP) of alpine grassland in northern Tibet. Geographical information system (GIS) techniques were used to analyse the spatial pattern of change in the NPP of alpine grassland and its response to the intensity of human activity. The researchers found that the mean values of NPP on flat (slope gradients <1°) and sunny slopes were relatively lower. Between 1981 and 2004, the NPP of alpine grassland in northern Tibet tended to decrease, but with relatively large annual fluctuations. In northern Tibet, the alpine grassland NPP for high-elevation regions has a greater proportion of area (over 26%) showing a decreasing trend. The change is more significant in areas where the slope is 15–30° and aspect has little influence on the extent of the change. The negative effects of local residential areas on the rate of change of alpine grassland NPP are smaller than those of roads.     

Recent climate variability and its impact on precipitation,temperature, and vegetation dynamics in the Lancang River headwater area of China

The alpine ecosystem is one of the most fragile ecosystems threatened by global climate change. The impact of climate variability on the vegetation dynamics of alpine ecosystems has become important in global change studies. In this study, spatially explicit gridded data, including the Moderate Resolution Imaging Spectroradiometer (MODIS) land-surface temperature (LST) product (MOD11A1/A2), the Tropical Rainfall Measuring Mission (TRMM) rainfall product (3B43), and MODIS net primary productivity (NPP) product (MOD17A3), together with meteorological observation data, were used to explore the spatio-temporal pattern of climate variability and its impact on vegetation dynamics from 2000 to 2012 in the Lancang River headwater area. We found that the variation patterns of LST, precipitation, and NPP in the study area showed remarkable spatial differences. From the northwest to the southeast the spatial variation of average annual LST exhibited a decreasing–increasing–decreasing–increasing pattern. At the same time, most of the study area exhibited an increasing LST during the growing season. The annual precipitation increased in the semi-arid northern part, whereas it decreased in the semi-humid southern part. The precipitation variability during the growing season has a pattern similar to the annual precipitation variability. Although the majority of the regions have seen an NPP increase from 2000 to 2012, the responses of the vegetation to the varied climate factors were spatially heterogeneous. The alpine–subalpine meadows in the high-altitude areas were more sensitive to climate variability in the growing season. It is argued that satellite remote-sensing products have great potential in investigating the impact of climate variability on vegetation dynamics at the finer scale, especially for the Lancang River headwater area with complex surface heterogeneity.     

Drought and elevation effects on MODIS vegetation indices in northern Arizona ecosystems

Northern Arizona ecosystems are particularly sensitive to plant-available moisture and have experienced a severe drought with considerable impacts on ecosystems from desert shrub and grasslands to pinyon-juniper and conifer forests. Long-term time-series from the Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) are used to monitor recent regional vegetation activity and temporal patterns across various ecosystems. Surface air temperature, solar radiation and precipitation are used to represent meteorological anomalies and to investigate associated impacts on vegetation greenness. Vegetation index anomalies in the northern Arizona ecosystem have a decreasing trend with increasing surface air temperature and decreasing precipitation. MODIS NDVI and EVI anomalies are likely sensitive to the amount of rainfall for northern Arizona ecosystem conditions, whereas inter-annual variability of surface air temperature accounts for MODIS NDVI anomaly variation. The higher elevation area shows the slow vegetation recovery through trend analysis from MODIS vegetation indices for 2000–2011 within the study domain and along elevation.     

Estimation of aboveground vegetation biomass based on Landsat-8 OLI satellite images in the Guanzhong Basin,China

This paper presents a method to estimate the aboveground biomass (AGB) through the selection of different estimation methods based on numerous vegetation types (i.e., broadleaf forest, coniferous forest, shrub and grassland) at a regional scale. The proposed method is based on three models, namely, the stepwise regression, an improved back-propagation neural network (Improved BBPNN) model based on the Gaussian error function, and the support vector machine (SVM) technique, Meanwhile, Landsat 8 Operational Land Imager (OLI)/Thermal Infrared Sensor (TIRS) image data and geo-parameters are employed to select 68 feature variables and optimize 213 data samples. Our results reveal that, the stepwise regression method provides the best AGB estimation performance for broadleaf forests and coniferous forests, while the SVM technique shows the best performance for grasslands and shrubs. Different vegetation types should be selected for additional biomass estimation models that have been proven to enhance the biomass estimation. This study on the AGB not only promotes research on the net primary productivity (NPP), but also plays a key role in global carbon cycle research.     

Assessment of forest damage caused by an ice storm using multi-temporal remote-sensing images: a case study from Guangdong Province

In early 2008, forest ecosystems in southern China suffered damage due to a severe ice storm disaster. The area and degree of forest damage caused by the ice storm was assessed using Satellite Pour l’Observation de la Terre (SPOT)-Vegetation images for Guangdong Province acquired between 1999 and 2008. By using the maximum value composition method and image thresholding techniques, the forest vegetation loss, expressed as the change in net primary productivity (NPP) and two indicators (I₁, I₂), was estimated. The damage threshold was determined by comparing the standard deviation of pixels of the undamaged areas in 2008 and other years without any disaster, which was 10%. The area of damaged forest vegetation was 47,670 km², with the northern Guangdong Province most seriously affected. The total loss of NPP for forest vegetation was 50,578,055 t (DW) year^?1, with 52 counties (43.7%) suffering forest vegetation damage. Evergreen coniferous forest was most widely affected, but evergreen broad-leaved forest was the most severely damaged vegetation type. Terrain topography influenced the damage to forest vegetation, which was found to increase with increasing elevation and slope gradient. The range and degree of damaged forest determined by remote-sensing data is consistent with the extent of the ice storm, indicating that this study provides a new approach for rapid assessment of forest disasters at a regional scale.     

植被净初级生产力的遥感模型在武汉地区的应用

卫星遥感成为观测和估算地面植被净初级生产力的一种极其有利的工具,其原因不仅仅在于它将人们从繁重的地面实验中解放出来,同时也因为它能够实现对大范围区域的植被净初级生产力进行实时监测。为了更加充分有效地利用卫星数据获取植被信息,我们在模式分解方法的基础上,建立了一种新的植被指数(VIPD)。根据地面实验建立的相应光合成曲线估算模型,估算武汉地区地域性植被净初级生产力（NPP）,研究该地区植被生长年间变化状况。并通过和不同方法估算结果及地面调查结果进行比较,检验模型对该地区的适用情况,为该地区植被NPP长期监测研究提供可靠依据。     

Annual changes in MODIS vegetation indices of Swedish coniferous forests in relation to snow dynamics and tree phenology

Remote sensing provides spatially and temporally continuous measures of forest reflectance, and vegetation indices calculated from satellite data can be useful for monitoring climate change impacts on forest tree phenology. Monitoring of evergreen coniferous forest is more difficult than monitoring of deciduous forest, as the new buds only account for a small proportion of the green biomass, and the shoot elongation process is relatively slow. In this study, we have analyzed data from 186 coniferous monitoring sites in Sweden covering boreal, southern-boreal, and boreo-nemoral conditions. Our objective was to examine the possibility to track seasonal changes in coniferous forests by time-series of MODIS eight-day vegetation indices, testing the coherence between satellite monitored vegetation indices (VI) and temperature dependent phenology. The relationships between two vegetation indices (NDVI and WDRVI) and four phenological indicators (length of snow season, modeled onset of vegetation period, tree cold hardiness level and timing of budburst) were analyzed.The annual curves produced by two curve fitting methods for smoothening of seasonal changes in NDVI and WDRVI were to a large extent characterized by the occurrence of snow, producing stable seasonal oscillations in the northern part and irregular curves with less pronounced annual amplitude in the southern part of the country. Measures based on threshold values of the VI-curves, commonly used for determining the timing of different phenological phases, were not applicable for Swedish coniferous forests. Evergreen vegetation does not have a sharp increase in greenness during spring, and the melting of snow can influence the vegetation indices at the timing of budburst in boreal forests. However, the interannual variation in VI-values for specific eight-day periods was correlated with the phenological indicators. This relation can be used for satellite monitoring of potential climate change impacts on northern coniferous spring phenology.     

缅甸土地覆被遥感制图和空间格局分析

在“一带一路”倡议框架下,中缅经济走廊逐步从概念转入实质规划建设阶段,了解和掌握缅甸土地覆被的空间格局和分布特征对于合理开发利用资源、制定务实的经济廊道建设规划具有重要的战略意义。利用Landsat-8 OLI遥感影像数据,基于多分类器集成的面向对象迭代分类方法（OIC-MCE）,生产了缅甸2015年30 m分辨率土地覆被产品（MyanmarLC-2015）。采用Google Earth高分辨率影像获取验证样本用于产品精度验证,验证结果表明：MyanmarLC-2015产品的总体分类精度为89.05%,Kappa系数为0.87,各类别的用户精度和制图精度均超过72%,能够准确地反映缅甸土地覆被类型的空间格局。根据产品统计,林地是缅甸面积最大的土地覆被类型,占国土面积56.15%,以常绿阔叶林为主,占林地面积83.57%。耕地面积次之,占国土面积27.01%。地形因子对缅甸土地覆被类型空间分布格局有显著的影响,随着海拔升高,呈现出按如下顺序的垂直地带性特征：森林湿地、水田、旱地、落叶灌木林、落叶阔叶林、常绿灌木林、常绿阔叶林、常绿针叶林。从植被生产力的角度来看,缅甸东部、东北部和东南部植...