黄土高原地区NDVI与气候因子空间尺度依存性及非平稳性研究

基于MODIS传感器的植被指数产品(MOD13Q1)及50年气候数据,通过地理加权回归与普通最小二乘回归模型对比,对中国黄土高原地区NDVI与气候因子间的空间尺度依存性及非平稳性进行研究,以期准确建立二者间关系.结果表明:① 研究区域内,NDVI与气候因子间存在很强的空间尺度依存关系,相同空间尺度下,年均降水较年均温对NDVI影响的波动性更大;② 与普通最小二乘回归模型相比,地理加权回归模型能够更准确地展现二者间关系;③气候因子对该地区NDVI的影响差异明显,降水存在直接正向影响,而温度的影响则较复杂;④ NDVI与气候因子间沿东北--西南的分布格局体现出区域内不同植被--气候区差异特征.二者间的异质情况还反映出除气候外,人类活动,地形等其他因素对NDVI的影响.     

Environmental zonation across the Australian arid region based on long-term vegetation dynamics

Zonation of landscapes is generally based on broad scale biophysical data, field surveys, imagery and expert knowledge. Such zonation represents a static view of the environment and does not reflect dynamics and function. Arid environments are however often highly dynamic, and spatial and temporal patterns may be expressed over long periods of time. These dynamics need to be understood for management. Our aim is to understand the dynamics and functional response of vegetation in the Australian arid zone, and use this to inform and potentially improve the currently employed stratification. Principal component analysis of 25 years of satellite imagery identified underlying factors influencing patterns of arid vegetation growth, and regions of similar long-term response. Dominant factors of variation were identified as the spatial distribution of total vegetation growth, seasonality of growth, magnitude of seasonal variability in growth, and regularity of variation in growth. Additional variation resulted from episodic vegetation growth of limited spatial extent and duration. Classes expressing these functional components were compared with the existing biogeographical regions, revealing agreement in some instances, and in other cases adding information previously not available. The study demonstrates a new approach to Australian landscape zonation that has potential for much wider application.     

北京山区植被覆盖动态变化遥感监测研究

植被覆盖变化遥感监测是区域生态监测的一个重要部分,可为区域生态建设和可持续发展提供科学依据.利用北京市1979年7月14日和2005年7月25日的Landsat MSS和TM影像,采用基于归一化植被指数(ND-VI)的像元二分模型,计算了这2个时期的植被覆盖度,并对北京山区1979-2005年间植被覆盖的变化情况进行了遥感监测和定量分析.结果表明,北京山区的植被覆盖度由1979年的70.05%下降为2005年的66.14%;植被退化的总面积为3672.90km2;植被覆盖度在80%～100%的退化面积最大,为617.45km2.     

气候变化对阿拉善荒漠植被的影响研究

利用1982—2003年NASA GIMMS归一化植被指数(NDVI)数据集和阿拉善左旗、右旗和额济纳旗气温和降水资料,对阿拉善地区NDVI变化和气候变化特征及其相互关系进行了分析。结果表明：①1982—2003年东部地区(左旗植被指数略有增加,而中部(右旗)和西部地区(额济纳旗)则呈下降趋势。季节变化东、中、西部表现不同。左旗和额济纳旗多年平均NDVI的月变化和右旗相反。②东部地区升温率最大,其次是西部和中部地区。降水表现为东部和西部地区(额济纳旗)稍有增加,而中部地区(右旗)呈缓慢减少趋势。季节变化东、中、西部表现不同。多年平均气温和降水量的月变化趋势东、中、西部一致,呈单峰型曲线。③东部地区和中部地区,降水量与植被指数存在明显的年相关、隔季和当季相关,而西部地区额济纳旗没有明显的相关性。阿拉善地区NDVI同温度的相关性不好。     

Spatial and temporal variations of vegetation in Qinghai Province based on satellite data

This paper used five years (2001-2006) time series of MODIS NDVI images with a 1-km spatial resolution to produce a land cover map of Qinghai Province in China. A classi-fication approach for different land cover types with special emphasis on vegetation, espe-cially on sparse vegetation, was developed which synthesized Decision Tree Classification, Supervised Classification and Unsupervised Classification. The spatial distribution and dy-namic change of vegetation cover in Qinghai from 2001 to 2006 were analyzed based on the land cover classification map and five grade elevation belts derived from Qinghai DEM. The result shows that vegetation cover in Qinghai in recent five years has been some improved and the area of vegetation was increased from 370,047 km2 in 2001 to 374,576 km2 in 2006. Meanwhile, vegetation cover ratio was increased by 0.63%. Vegetation cover ratio in high mountain belt is the largest (67.92%) among the five grade elevation belts in Qinghai Prov-ince. The second largest vegetation cover ratio is in middle mountain belt (61.80%). Next, in the order of the decreasing vegetation cover ratio, the remaining grades are extreme high mountain belt (38.98%), low mountain belt (25.55%) and flat region belt (15.46%). The area of middle density grassland in high mountain belt is the biggest (94,003 km2), and vegetation cover ratio of dense grassland in middle mountain belt is the highest (32.62%), and the in-creased area of dense grassland in high mountain belt is the greatest (1280 km2). In recent five years the conversion from sparse grass to middle density grass in high mountain belt has been the largest vegetation cover variation and the converted area is 15931 km2.     

基于小波分析的NDVI与环境因子空间尺度依存关系研究(英文)

本文通过多尺度分解途径分析了NDVI与环境因子如地形与气候之间的空间尺度依存关系。为了揭示两者关系的尺度效应,选取青藏高原北纬32.5度作为研究样带,应用小波变换分析了不同空间尺度下的小波一致性和相位关系。研究结果表明:在青藏高原小于80km空间尺度上,气候变量如降水和气温不是控制NDVI的主导因素;而大于这个尺度,在一些生态区可以发现NDVI和气候因子具有显著的小波一致性。作为一个分异因子,海拔高度在青藏高原东南缘的纵向岭谷区对NDVI有着显著影响。通过这一研究发现,小波变换是研究NDVI与影响因素之间多尺度关系的一个有力途径。     

The response of vegetation growth to shifts in trend of temperature in China

Though many studies have focused on the causes of shifts in trend of temperature, whether the response of vegetation growth to temperature has changed is still not very clear. In this study, we analyzed the spatial features of the trend changes of temperature during the growing season and the response of vegetation growth in China based on observed climatic data and the normalized difference vegetation index (NDVI) from 1984 to 2011. An obvious warming to cooling shift during growing season from the period 1984–1997 to the period 1998–2011 was identified in the northern and northeastern regions of China, whereas a totally converse shift was observed in the southern and western regions, suggesting large spatial heterogeneity of changes of the trend of growing season temperature throughout China. China as a whole, a significant positive relationship between vegetation growth and temperature during 1984 to 1997 has been greatly weakened during 1998–2011. This change of response of vegetation growth to temperature has also been confirmed by Granger causality test. On regional scales, obvious shifts in relationship between vegetation growth and temperature were identified in temperate desert region and rainforest region. Furthermore, by comprehensively analyzing of the relationship between NDVI and climate variables, an overall reduction of impacts of climate factors on vegetation growth was identified over China during recent years, indicating enhanced influences from human associated activities.     

额济纳荒漠绿洲植被生态需水量研究

荒漠绿洲的生态需水量主要指维持荒漠绿洲植被正常生长所需要消耗的水量.采用3S技术与野外生产力测定相结合的方法, 通过建立植被归一化指数(NDVI)、生产力、蒸腾系数之间的关系方程, 计算了额济纳荒漠绿洲的植被生态需水量.结果表明, 维持额济纳绿洲现状的需水量为1.53×10⁸ m³, 若使现有的植被恢复到目前最高生产力水平的生态需水量为3.49×10⁸ m³. 考虑到城镇居民生活用水、河道输水损失、绿洲植被耗水、绿洲内农田用水和降水补充等, 额济纳旗绿洲维持现状需要黑河下泄水量(狼心山)为1.93~2.23×10⁸ m³之间, 若使现有的植被恢复到目前最高生产力水平, 需要黑河下泄水量(狼心山)为4.28~5.17×10⁸ m³之间.     

Desertification in the Sahel: Towards better accounting for ecosystem dynamics in the interpretation of remote sensing images

To date, the interpretation of remote sensing images has not revealed wide-spread degradation of the vegetation in the Sahel. However, the interpretation of spectral information depends on a range of assumptions regarding the dynamics of the Sahelian vegetation as a function of rainfall variability and human management. Recent papers have presented diverging views on the vegetation dynamics of the Sahel and how these can be analysed with remote sensing images. We present a further analysis of the vegetation dynamics of semi-arid rangelands, in particular the Sahel, and the subsequent implications for the interpretation of remote sensing images. Specifically, the ecological processes driving the response of the Sahelian vegetation to rainfall variation are re-examined, and a regression analysis of NPP versus rainfall data is carried out. It is shown that the relation between the interannual variation in NPP and rainfall in the Sahel is non-linear and that this relation differs between sites with different average annual rainfall. It has been common practise in remote sensing studies for the Sahel to aggregate data from various Sahelian sites in order to obtain an average relation between rainfall, NPP and Rain Use Efficiency, and to assume these relations to be linear. This paper shows that this approach may lead to a bias in the interpretation of remote sensing images and that further work is required to clarify if wide-spread ecosystem degradation has occurred in the Sahel.     

腾格里沙漠南缘哈思山树轮记录的NDVI变化

利用采自腾格里沙漠南缘哈思山的油松树轮样品建立树轮宽度年表,结合GIMMS归一化植被指数（NDVI）数据资料重建了本区1804~2009年6~9月NDVI变化序列。本研究分析了NDVI序列变化特征,在此基础上,探讨了本区植被变化与沙尘暴天气及其与干旱气候的关系,结果表明：近206年来腾格里沙漠南缘NDVI虽未发现显著增加趋势,但期间经历了多次波动;植被生长较好的阶段出现在1826~1829年、1849~1852年、1885~1895年、1934~1963年和1969~1978年,植被生长较差的阶段为1815~1823年、1831~1847年、1897~1909年、1924~1932年、1988~1993年和2001~2006年。发现NDVI极低值年份与周边地区沙尘暴多发期有良好的对应关系,说明腾格里沙漠南缘NDVI变化与当地沙尘天气有一定潜在联系,但地表植被变化对沙尘暴的发生起到的作用是有限的。腾格里沙漠南缘NDVI变化与旱涝等级及PDSI有显著的相关性,指示了水分条件对本区地表植被生长有明显的制约作用。