黄河源区植被生长季NDVI时空特征及其对气候变化的响应

利用黄河源区MODIS/NDVI数据、1∶100万植被类型图和气象资料,分析了该区不同植被类型生长季NDVI时空特征以及与气候因子的关系。结果表明,1）2000—2011年,黄河源区植被生长呈改善趋势,生长季NDVI年际变化率每10 a为＋2.75%,高寒草原、高寒草甸、高寒灌丛生长季NDVI年际变化率分别为每10 a＋2.84%、＋2.65%、＋2.77%。2）黄河源区植被改善面积占全区总面积的29.39%,主要分布在卡日曲和玛曲上游、扎曲流域、布青山南麓、扎陵湖北部和鄂陵湖周边地区。植被退化面积仅占全区总面积的0.98%,主要分布在约古宗列曲东南部山地和卡日曲北部山地。受水热条件控制,植被改善表现为：①植被改善面积南坡大于北坡;②植被改善面积随海拔升高先增加后减小;③植被改善面积随坡度增加迅速减小。3）黄河源区植被生长季NDVI与同期气温和降水分别存在显著正相关性,其中高寒草原和高寒草甸生长受降水影响更为明显,而高寒灌丛生长受气温影响更为明显。气候的暖湿化趋势可能是促使黄河源区植被生长改善的主要原因。     

中国植被生长的最适温度估算与分析

利用中国区域的GIMMS NDVI数据集和相应时期气象站点实测的温度数据集,分别在时间尺度和空间地域上对比分析植被生长过程与环境温度变化的关系,并由此提取区域植被生长关键阶段对应的温度,最后得到了中国各生态地理区植被生长的最适温度及其变化区间。结果显示:①研究首次给出了不同生态区植被生长的最适温度,其中青藏高原的参考最适温度最低,在10 ℃左右,而长江中下游和华南地区的较高,很多区域的值都超过了25 ℃,说明植被生长的最适温度具有很强的地域分异性;②根据论文结果,通过海拔高度和纬度两个地理因子,可快速拟合得到中国陆地植被生长的近似最适温度。研究结果可以为生态系统模型的参数本地化和空间化提供参考。     

东北多年冻土区植被NDVI变化及其对气候变化和土地覆被变化的响应

利用1982~2006年的NOAA AVHRR-GIMMS和MODIS 2种数据集的归一化植被指数(NDVI)数据对东北多年冻土区植被NDVI年际动态和空间差异进行分析,并结合气象数据和土地利用/覆被数据分析了植被NDVI对气候变化和土地利用/覆被变化的响应.研究表明,东北多年冻土区植被NDVI值较高,且空间差异明显;森林为该区主要植被类型,NDVI值较高,主要分布于大小兴安岭和伊春地区;草地集中分布于西南部, NDVI值相对较低.东北多年冻土区过去25a间植被生长的变化趋势为:伴随着气温的显著升高和降水量减少,植被NDVI显著下降.较气温而言,降水量是影响植被NDVI的主要因子(r = 0.77, P < 0.01).在气候变化和人类活动的双重作用下,东北多年冻土区植被NDVI在1982~2006年间表现为4个阶段:1982~1990年,植被NDVI虽有小幅波动,但整体上呈持续增加的趋势;1990~1993年,植被NDVI呈迅速下降趋势; 1993~1997年,植被NDVI呈现回升态势,表现出缓慢上升的趋势;1998~2006年,植被NDVI呈现总体下降趋势.不同植被类型表现出不同的NDVI年际变化规律,尤以草地NDVI值波动最大.植被NDVI变化空间异质性显著.气候变化和多年冻土退化影响了东北多年冻土区植被NDVI动态.年均气温升高和年降水量降低影响了植被的生长.从像元尺度来看,研究区植被NDVI与气温和降水均具有较显著的相关性.研究区土地利用/覆被变化的分析结果表明,不同的土地利用类型间的转变对植被NDVI的大小和空间分布产生了重要影响.     

西藏当雄县高寒草地NDVI的海拔分异特征及其指示

通过提取西藏当雄县Landsat ETM影像NDVI以及DEM的海拔要素,在坡面的小尺度水平上分析了NDVI的海拔格局,并利用沿海拔梯度的草地地上生物量实测数据进行验证,进一步在全县尺度上分析了当雄NDVI >0.2 的区域内草地NDVI 的海拔分异特征.主要结果如下:①在坡面尺度上,随海拔的增加,不同计算方式的NDVI均表现为先增加后降低的单峰格局,与沿海拔梯度实测的地上生物量格局一致,NDVI最大值与围栏外生物量最大值均出现在4 950 m左右;②在全县尺度上,当雄草地NDVI随海拔的变化略为复杂:在4 300 m以上,NDVI随海拔的增加表现为先升高后降低,最高值出现在4 700 m左右;在4 300 m以下植被可能以湿地草甸为主,形成另一个NDVI高值区,但其分布面积仅为总草场面积的10%左右.上述结果表明,海拔是影响当雄县NDVI 空间分布的重要地形因子,NDVI 的海拔格局体现了较大尺度上草地植被对不同水热组合环境的适应特征,这对于在气候变化背景下实施高寒地区生态保护工程以及制定合理的草场资源配置方案具有重要指导意义.     

呼伦贝尔草原植被覆盖度估算的光谱模型

采用美国ASD公司Fieldspec3光谱仪和日本富士数码相机,于2009年7~8月在内蒙古呼伦贝尔草原区进行了植物高光谱和植被覆盖度测定,并运用回归分析方法,建立实测归一化植被指数(ASD NDVI)和植被覆盖度之间的地面光谱模型,分析MODIS/TERRA卫星的NDVI(MODIS NDVI)与ASD NDVI的关系,建立预测植被覆盖度的MODIS光谱模型,并对模型进行精度检验.结果表明所建的MODIS光谱模型是线性函数,该模型预测精度高于亚像元分解模型,标准误差为11.58%,平均预测精度达到88.75%.     

Post-fire vegetation regrowth detection in the Deiva Marina region (Liguria-Italy) using Landsat TM and ETM+ data

Obtaining quantitative information about the recovery of fire-affected ecosystems is of utmost importance from the management and decision-making point of view. Nowadays the concern about natural environment protection and recovery is much greater than in the past. However, the resources and tools available for its management are still not sufficient. Thus, attention and precision is needed when decisions must be taken. Quantitative estimates on how the vegetation is recovering after a fire can be of help for evaluating the necessity of human intervention on the fire-affected ecosystem, and their importance will grow as the problem of forest fires, climate change and desertification increases.This article performs a comparison of methods to extract quantitative estimates of vegetation cover regrowth with Landsat TM and ETM+ data in an area that burned during the summer of 1998 in the Liguria region (Italy). In order to eliminate possible sources of error, a thorough pre-processing was carried out, including a careful geometric correction (reaching RMSE lower than 0.3 pixels), a topographic correction by means of a constrained Minnaert model and a combination of absolute and relative atmospheric correction methods. Pseudo Invariant Features (PIF) were identified by implementing an automated selection method based in temporal Principal Component Analysis (PCA), which has been called multi-Temporal n-Dimensional Principal Component Analysis (mT-nD-PCA).Spectral Mixture Analysis (SMA) was compared against quantitative vegetation indices which are based on well known traditional vegetation indices like Normalized Difference Vegetation Index (NDVI) and Modified Soil Adjusted Vegetation Index (MSAVI). Accuracy assessment was performed by regressing vegetation cover results obtained with each method against field data gathered during the fieldwork campaign carried out in the study area. Results obtained showed how vegetation cover fractions extracted from the NDVI based quantitative index were the most accurate, being superior to the rest of the techniques applied, including SMA.     

Knowing fire incidence through fuel phenology: A remotely sensed approach

Fire is a basic ecological factor that contributes to determine vegetation diversity and dynamics in time and space. Fuel characteristics play an essential role in fire ignition and propagation; at the landscape scale fuel availability and flammability are closely related to the vegetation phenology that directly affects wildfire pattern in time and space. In this view, the annual normalized difference vegetation index (NDVI) profiles derived from high temporal resolution satellites, like SPOT Vegetation, represent an effective tool for monitoring the coarse-scale vegetation seasonal timing. The objective of this study thus consists in quantifying the explanatory power of multitemporal NDVI profiles on the fire regime characteristics of the potential natural vegetation (PNV) types of Sardinia (Italy) over a 5-year period (2000-2004). The results obtained show a good association between the NDVI temporal dynamics of the PNV of Sardinia and the corresponding fire regime characteristics, emphasizing the role of the bioclimatic timing of the vegetation in controlling the coarse-scale wildfire spatio-temporal distribution of Sardinia. By providing a sound phytogeographical framework for describing different wildfire regimes, PNV maps can thus be considered helpful cartographic documents for fire management strategies at the landscape scale.     

华北平原1981～2001年作物蒸散量的时空分异特征

利用土壤-植被-大气传输机理模型(VIP模型),以GIS背景数据库(土地利用图、土壤质地图和数字高程图)为支撑,在NOAA-AVHRRNDVI数据和气象信息的驱动下,连续模拟了1981～2001年华北平原冬小麦和夏玉米生育期的蒸散过程。结果表明:模拟的作物蒸散量与Lysimeter观测值和其他学者的田间试验研究结果具有较好的一致性。华北平原冬小麦多年平均蒸散量空间上呈现南高北低的趋势,其中黄河以北地区和山东半岛的蒸散量在200～400mm之间,南部地区在400～466mm之间。对玉米而言,北部的海河低地平原以及津、冀、鲁的沿海地区多年平均蒸散量变化在230～380mm,其余大部分地区蒸散量在380～470mm。除本区最南端的极少部分地区外,华北平原大部分地区冬小麦生育期内的自然降水都小于蒸散量,水分亏缺量大于200mm,而夏玉米生育期内大部分地区的降水大于蒸散量。     

Using NDVI to Assess Vegetative Land Cover Change in Central Puget Sound

We used the Normalized Difference Vegetation Index (NDVI) in the rapidly growing Puget Sound region over three 5-year time blocks between 1986–1999 at three spatial scales in 42 Watershed Administrative Units (WAUs) to assess changes in the amounts and patterns of green vegetation. On average, approximately 20% of the area in each WAU experienced significant NDVI change over each 5-year time block. Cumulative NDVI change over 15 years (summing change over each 5-year time block) was an average of approximately 60% of each WAU, but was as high as 100% in some. At the regional scale, seasonal weather patterns and green-up from logging were the primary drivers of observed increases in NDVI values. At the WAU scale, anthropogenic factors were important drivers of both positive and negative NDVI change. For example, population density was highly correlated with negative NDVI change over 15 years (r = 0.66, P < 0.01), as was road density (r = 0.71, P < 0.01). At the smallest scale (within 3 case study WAUs) land use differences such as preserving versus harvesting forest lands drove vegetation change. We conclude that large areas within most watersheds are continually and heavily impacted by the high levels of human use and development over short time periods. Our results indicate that varying patterns and processes can be detected at multiple scales using changes in NDVIa values.     

广东省NDVI时空变化特征及其对气候因子的响应

广东省植被类型丰富、气候条件复杂,开展气候因子对植被的影响研究,对于全省保护生态环境、应对气候变化具有重要意义.利用MODIS NDVI数据和地面气象观测数据,基于变化趋势分析、空间自相关分析、相关性分析等方法,研究广东省NDVI时空分布特征及其对气温、降水、日照时数等气候因子的响应.结果表明,2000—2018年广东...