Assessment of vegetation dynamics and their response to variations in precipitation and temperature in the Tibetan Plateau

The Tibetan Plateau is a region sensitive to climate change, due to its high altitude and large terrain. This sensitivity can be measured through the response of vegetation patterns to climate variability in this region. Time series analysis of Normalized Difference Vegetation Index (NDVI) imagery and correlation analyses are effective tools to study land cover changes and their response to climatic variations. This is especially important for regions like the Tibetan Plateau, which has a complex ecosystem but lacks a lot of detailed in-situ observation data due to its remoteness, vastness and the severity of its climatic conditions. In this research a time series of 315 SPOT VEGETATION scenes, covering the period between 1998 and 2006, has been processed with the Harmonic ANalysis of Time Series (HANTS) algorithm in order to reveal the governing spatiotemporal pattern of variability. Results show that the spatial distribution of NDVI values is in agreement with the general climate pattern in the Tibetan Plateau. The seasonal variation is greatly influenced by the Asian monsoon. Interannual analysis shows that vegetation density (recorded here by the NDVI values) in the entire Tibetan Plateau has generally increased. Using a 1 km resolution land cover map from GLC2000, seven meteorological stations, presenting monthly data on near surface air temperature and precipitation, were selected for correlation analysis between NDVI and climate conditions in this research. A time lag response has also been found between NDVI and climate variables. Except in desert grassland (Shiquanhe station), the NDVI of all selected sites showed strong correlation with air temperature and precipitation, with variations in correlation according to the different land cover types at different locations. The strongest relationship was found in alpine and subalpine plain grass, the weakest in desert grassland.     

Links between observed micro-meteorological variability and land-use patterns in the highveld priority area of South Africa

Links between spatial and temporal variability of Planetary Boundary Layer meteorological quantities and existing land-use patterns are still poorly understood due to the non-linearity of air–land interaction processes. This study describes the results of a statistical analysis of meteorological observations collected by a network of ten Automatic Weather Stations. The stations were in operation in the highveld priority area of the Republic of South Africa during 2008–2010. The analysis revealed localization, enhancement and homogenization in the inter-station variability of observed meteorological quantities (temperature, relative humidity and wind speed) over diurnal and seasonal cycles. Enhancement of the meteorological spatial variability was found on a broad range of scales from 20 to 50?km during morning hours and in the dry winter season. These spatial scales are comparable to scales of observed land-use heterogeneity, which suggests links between atmospheric variability and land-use patterns through excitation of horizontal meso-scale circulations. Convective motions homogenized and synchronized meteorological variability during afternoon hours in the winter seasons, and during large parts of the day during the moist summer season. The analysis also revealed that turbulent convection overwhelms horizontal meso-scale circulations in the study area during extensive parts of the annual cycle.     

Can a 25-year trend in Soudano-Sahelian vegetation dynamics be interpreted in terms of land use change? A remote sensing approach

This study is based on the premise that, in the Sahel/Sudanian belt of Africa, the main determinants of interannual variation in vegetation dynamics are rainfall and land cover type. We analyzed the spatio-temporal sensitivity of the NOAA-AVHRR 8 km-resolution vegetation index (NDVI) to (i) annual rainfall variability (0.5° × 0.5° resolution) acquired over a 25-year period (1982-2006); and (ii) land use changes in the different eco-climatic regions of the Bani catchment in Mali (130 000 km²). During the period 1982-2006, there was no clear trend in rainfall over the catchment, whereas there was a strong positive trend in the NDVI, both when the NDVI values were corrected using annual rainfall variability and when they were not. We divided the catchment into three eco-climatic regions based on the relationship between the annual NDVI and rainfall. In each region, we analyzed the observed greening in relation to changes in land use after correcting for the effect of annual rainfall on the NDVI. Results show that there is a mixed level of agreement between the land cover changes at the grid cell scale and the spatial pattern of the NDVI trend. Increased cropping does not explain the increase in the annual NDVI, except in the Sahelian part of the catchment. We hypothesize that the natural vegetation dynamics related to the non-linear rainfall patterns during the 25-year study period were responsible for these results.     

华北平原不同生长发育期作物长势对气候因子的响应研究

利用卫星遥感归一化植被指数(NDVI)时间序列数据和站点气象数据,从农作物生长发育过程的角度,分析了1981~2008年华北平原农田在12个生长发育期(冬小麦8个、夏玉米4个)对降水和温度不同的响应特征。研究区农田植被指数对降水响应的滞后性强于对温度的滞后性,其中对降水最为敏感的是前1和前2个生长发育期,对温度最为敏感的是同期和前1个生长发育期。不同种类作物在不同时期对气候因子响应不同:冬小麦发育中后期、夏玉米发育中期,绝大多数站点植被指数与降水呈正相关;冬小麦生长发育前中期植被指数与温度呈显著甚至极显著正相关。冬小麦出苗期温度、返青期温度和返青期降水分别与不同时期植被指数显著相关,出苗期和返青期为研究区农田长势对气候因子响应的敏感期。     

MODIS卫星NDVI时间序列变化在冬小麦面积估算中的应用分析

以陕西小麦主产区关中地区为研究地点,EOS/MODIS卫星数据为主要数据源,借助冬小麦地面定位调查数据和土地覆盖类型图作为辅助信息,计算得到不同覆盖类型的植被指数时序曲线图,找出冬小麦发育期植被指数变化规律,剔除小麦生长季节的非麦区信息,用几个关键期的植被指数变化差值图设定不同阈值,利用GIS空间分析功能得到麦区分布图...     

Effective Accuracy of Satellite-Derived Hourly Irradiances

Summary  Estimates of hourly global irradiance based on geostationary satellite data with a resolution of several (2 to 10) kilometres reproduce ground-measured values with a Root Mean Square Error (RMSE) of typically 20% to 25%. The different components of this RMSE have been enumerated by several authors but, due to the lack of adequate measurements, their respective importance is not well settled. In the present study we attempt to quantify these components from a practical point of view, that is from the point of view of users having to rely on time/site specific irradiance data. We conclude that the intrinsic, or “effective” RMSE is more along the line of 12%. This effective RMSE is the measure of the methodological imprecision (satellite-to-irradiance conversion models). The remaining part of the overall RMSE is the amount by which spatially averaged satellite-derived estimates are, by their very nature, bound to differ from ground-measured local insolation. Received August 15, 1997 Revised March 4, 1998     

基于MODIS数据光谱突变法提取冬小麦种植面积研究

利用2004—2005年MODIS 16天合成的NDVI最大值植被指数数据,基于NDVI光谱突变方法对山西省运城地区冬小麦种植面积提取。冬小麦有两个生育阶段其绿度—时相曲线与其他大宗作物、植被有明显差异：一是10—11月,为冬小麦秋播至分蘖阶段;二是5—6月,为冬小麦孕穗至收获期。通过分析得出：2005年5—6月（2005161～2005129）提取的冬小麦面积与实测面积相关性最高,估测的冬小麦面积与实测面积的误差最小,准确性最高。     

内蒙古植被NDVI变化特征分析

对植被状况和植被覆盖的研究可以反映植被受环境条件影响产生的时空变化。文章根据GIMMS-NDVI数据集1982—2006年影像数据,分析内蒙古农田、森林、草原三种植被类型NDVI年内、年际的变化趋势以及植被覆盖变化特征的空间差异。各植被类型变化曲线都呈现4—7月NDVI激增,8—10月NDVI猛降,冬季农田、草原植被覆盖接近裸土的特点。农田夏季NDVI平均值的历年线性变化趋势通过显著性检验,森林夏季NDVI平均值呈现下降的趋势,草原夏季NDVI平均值呈现上升的趋势,但都不显著。     

The effect of the wintertime Arctic Oscillation on springtime vegetation over the northern high latitude region

The winter Arctic Oscillation (AO), a major source of climate variability in the Northern Hemisphere, affects winter and the subsequent spring climate over northern high latitude. Such effects are evident even in the 1st eigenmode of the normalized difference vegetation index (NDVI). The impacts of the winter AO is a dipole pattern between Eurasia and North America; positive (negative) values of the winter AO induce warmer (cooler) and high (low) vegetation activity in the following spring over Eurasia (North America). Regarding the time-lagged response of vegetation, the sea surface temperature (SST) and snow cover contribute to maintaining the large-scale circulation anomaly associated with the AO.     

中国东部地区冬季和夏季地面湿度空间分布特征的对比分析

利用中国东部地区315个台站1963~2012年月平均地面观测资料,揭示了东部地区冬季和夏季地面比湿(SH)和相对湿度(RH)多年平均值及其变率的空间分布特征,并分析和比较了地理因素(经度、纬度和海拔高度)对其空间分布的影响。结果表明:1)在冬季,SH(0.4~7 g kg-1)以秦岭-淮河线为界,呈现出"北低南高"的分布特征;RH(41%~82%)则呈现出"南北高、中间低"的分布特征;一般冬季地面湿度相对较低的地区其变化幅度相对较大。2)在夏季,SH(7~20 g kg-1)整体上明显大于冬季,RH(44%~89%)则与冬季差异不大,均呈现由东南部沿海向西北内陆递减的分布特征;同样夏季地面湿度较低的地区通常其变化幅度也相对较大。3)东部地区冬季地面湿度空间分布受地理因素影响,其中纬度是最主要的影响因素,经度次之,海拔高度对其整体分布影响不明显,且地理因素对冬季SH的回归效果明显好于对冬季RH的回归效果。4)东部地区夏季地面湿度空间分布受地理因素影响较冬季显著,纬度同样是影响夏季地面湿度最主要的因素,但海拔高度对夏季SH、经度对夏季RH的影响程度较冬季增大,且地理因素对夏季SH的回归效果同样好于对RH的回归效果。     

冬小麦夏玉米土壤水分预报及优化灌溉模型

利用土壤水分平衡方程，结合河南省冬小麦和夏玉米的生长规律和1994～2000年冬小麦、夏玉米田实测土壤湿度资料，建立了河南省冬小麦、夏玉米土壤水分预报及优化灌溉的计算机模型。用1998～1999年郑州市麦田实测土壤湿度资料验证该模型模拟结果，未来10、20、30天土壤湿度相对误差分别为-7．3％～7．7％、-8．3％～6．8％、-7．6％～7．7％，表明利用该模型，可以较为准确地预报未来1个月的土壤水分变化，并可根据小麦、玉米不同发育期特点，给出以最高产量和最佳经济效益为目标的灌溉建议。     

青藏高原冬、春植被归一化指数变化特征及其与高原夏季降水的联系

青藏高原气候独特,影响高原夏季降水的原因是十分复杂的和多方面的。文中利用1982—2001年的卫星遥感植被归一化指数(NDVI)资料和青藏高原55个实测台站降水资料,应用经验正交分解(EOF)、奇异值分解(SVD)等方法分析了青藏高原冬、春植被变化特征及其与高原夏季降水的联系,得到以下几点初步认识:青藏高原冬、春季植被分布基本呈现东南地区植被覆盖较好,逐渐向西北地区减少的特征。其中高原东南部地区和高原南侧边界地区NDVI值最大,而西北地区和北侧边界地区NDVI较小。EOF分析表明,20年来冬、春季高原植被的变化趋势是总体呈阶段性增加,其中尤以高原北部、西北部(昆仑山、阿尔金山和祁连山沿线)和南部的雅鲁藏布江流域植被增加明显。由SVD方法得到的高原前期NDVI与后期降水的相关性是较稳定的。青藏高原多数区域冬、春植被与夏季降水存在较好的正相关,且这种滞后相关存在明显的区域差异。高原南部和北部区域的NDVI在冬春两季都与夏季降水有明显的正相关,即冬春季植被对夏季降水的影响较显著。而冬季高原中东部玉树地区附近区域的NDVI与夏季降水也存在较明显的负相关,即冬季中东部区域的植被变化对夏季降水的影响也较显著。由此可见,高原前期NDVI的变化特征,可以作为高原降水长期预报综合考虑的一个重要参考因子。     

Spatial patterns of vegetation phenology metrics and related climatic controls of eight contrasting forest types in India – analysis from remote sensing datasets

Summary Leaf phenology describes the seasonal cycle of leaf functioning and is essential for understanding the interactions between the biosphere, the climate and the atmosphere. In this study, we characterized the spatial patterns in phenological variations in eight contrasting forest types in an Indian region using coarse resolution NOAA AVHRR satellite data. The onset, offset and growing season length for different forest types has been estimated using normalized difference vegetation index (NDVI). Further, the relationship between NDVI and climatic parameters has been assessed to determine which climatic variable (temperature or precipitation) best explain variation in NDVI. In addition, we also assessed how quickly and over what time periods does NDVI respond to different precipitation events. Our results suggested strong spatial variability in NDVI metrics for different forest types. Among the eight forest types, tropical dry deciduous forests showed lowest values for summed NDVI (SNDVI), averaged NDVI (ANDVI) and integrated NDVI (I-NDVI), while the tropical wet evergreen forests of Arunachal Pradesh had highest values. Within the different evergreen forest types, SNDVI, ANDVI and INDVI were highest for tropical wet evergreen forests, followed by tropical evergreen forests, tropical semi-evergreen forests and were least for tropical dry evergreen forests. Differences in the amplitude of NDVI were quite distinct for evergreen forests compared to deciduous ones and mixed deciduous forests. Although, all the evergreen forests studied had a similar growing season length of 270 days, the onset and offset dates were quite different. Response of vegetative greenness to climatic variability appeared to vary with vegetation characteristics and forest types. Linear correlations between mean monthly NDVI and temperature were found to yield negative relationships in contrast to precipitation, which showed a significant positive response to vegetation greenness. The correlations improved much for different forest types when the log of cumulative rainfall was correlated against mean monthly NDVI. Of the eight forest types, the NDVI for six forest types was positively correlated with the logarithm of cumulative rainfall that was summed for 3–4 months. Overall, this study identifies precipitation as a major control for vegetation greenness in tropical forests, more so than temperature.     

黑河实验区地表植被指数的区域分布及季节变化

利用具有较高空间分辨率的Ｌａｎｄｓａｔ ＴＭ卫星资料估算了黑河实验区夏季和近冬季地表标准化差值植被指数ＮＤＶＩ,分析了ＮＤＶＩ的区域分布特征和季节变化。结果表明,由于该实验区下垫面的复杂性,ＮＤＶＩ表现出明显的空间和季节变化,ＮＤＶＩ的图像能够很好地反映出地表植被的分布状况。     

Interannual variability and correlation of vegetation cover and precipitation in Eastern China

Based on the SPOT/VEGETATION Normalized Difference Vegetation Index (NDVI) data and daily precipitation data of 357 meteorological stations, the spatial and temporal variability of vegetation cover, measured by NDVI, and precipitation as well as their relationships are investigated in Eastern China, which is portioned into three subregions (regions I, II, and III), for the period 1998–2010. The results show that high NDVI values appear mainly in Northeastern China and in August while high precipitation (PRETOT) occurs in Southeastern China and in July (June for Southern China). Extreme precipitation days (RD95p) and amount (EPRETOT) coincide well with PRETOT. Extreme precipitation intensity (RINTEN) has a similar spatial variability to PRETOT but with a smaller seasonal variation than PRETOT. Growing season NDVI is positively correlated with PRETOT in 11.7 % of the study area (mostly in arid to subhumid regions of Northern China), where precipitation is a limiting factor for vegetation growth. In contrast, a negative correlation between growing season NDVI and PRETOT is found in 4.8 % of the study area, mostly in areas around the Yangtze River and deep Northeastern China. No significant correlations between these two variables are found for the other regions because vegetation response to precipitation is affected by other factors such as temperature, radiation, and human disturbance. On a monthly scale, there is a positive correlation between NDVI and PRETOT in May (for region II) and September (all subregions except region I). NDVI variations lag 1 month behind PRETOT in June (for region I) and October. Correlations between NDVI and RD95p, EPRETOT are similar to that with PRETOT, but the relationships between NDVI and RINTEN are relatively weaker than with PRETOT. This study provides the technical basis for agriculture development and ecological construction in Eastern China.     

The Effect of Spatial Scale of Climatic Change Scenarios on Simulated Maize, Winter Wheat, and Rice Production in the Southeastern United States

We use the CERES family of crop models to assess the effect of different spatial scales of climate change scenarios on the simulated yield changes of maize (Zea mays L.), winter wheat (Triticum aestivum L.),and rice (Oryza sativa L.) in the Southeastern United States. The climate change scenarios were produced with the control and doubled CO₂ runs of a high resolution regional climate model anda coarse resolution general circulation model, which provided the initial and lateral boundary conditions for the regional model. Three different cases were considered for each scenario: climate change alone, climate change plus elevated CO₂, and the latter with adaptations. On the state level,for most cases, significant differences in the climate changed yields for corn were found, the coarse scale scenario usually producing larger modeled yield decreases or smaller increases. For wheat, however, which suffered large decreases in yields for all cases, very little contrast in yield based on scale of scenario was found. Scenario scale resulted in significantly different rice yields, but mainly because of low variability in yields. For maize the primary climate variable that explained the contrast in the yields calculated from the two scenarios is the precipitation during grain fill leading to different water stress levels. Temperature during vernalization explains some contrasts in winter wheat yields. With adaptation, the contrasts in the yields of all crops produced by the scenarios were reduced but not entirely removed. Our results indicate that spatial resolution of climate change scenarios can be an important uncertainty in climate change impact assessments, depending on the crop and management conditions.     

我国夏季降水与青藏高原春季NDVI的关系

利用1982年1月-2001年12月NDVI资料、台站降水资料和NCEP/NCAR再分析资料, 通过相关分析和合成分析方法, 初步分析了我国夏季降水与青藏高原春季植被的关系及可能机理。结果发现:青藏高原春季NDVI与我国夏季降水相关系数从南到北呈西北-东南向“ + - +”带状分布。合成分析也表明:青藏高原春季NDVI大、小值年降水年内分布也存在明显差异。降水的上述差异, 可能是由于青藏高原春季NDVI变化导致热源效应改变, 引起大气环流变化造成的。对环流分析也发现:大气环流的变化特征与降水变化表现出很好的一致性。     

Air Temperature Estimation with MODIS Data over the Northern Tibetan Plateau

Time series of MODIS land surface temperature(T_s) and normalized difference vegetation index(NDVI) products,combined with digital elevation model(DEM) and meteorological data from 2001 to 2012,were used to map the spatial distribution of monthly mean air temperature over the Northern Tibetan Plateau(NTP). A time series analysis and a regression analysis of monthly mean land surface temperature(T_s) and air temperature(T_a) were conducted using ordinary linear regression(OLR) and geographical weighted regression(GWR). The analyses showed that GWR,which considers MODIS T_s,NDVI and elevation as independent variables,yielded much better results [R_(Adj)~2 0.79; root-mean-square error(RMSE) =0.51℃–1.12℃] associated with estimating T_a compared to those from OLR(R_(Adj)~2= 0.40-0.78; RMSE = 1.60℃–4.38℃).In addition,some characteristics of the spatial distribution of monthly T_a and the difference between the surface and air temperature(T_d) are as follows. According to the analysis of the 0℃ and 10℃ isothermals,T_a values over the NTP at elevations of 4000–5000 m were greater than 10℃ in the summer(from May to October),and T_a values at an elevation of3200 m dropped below 0℃ in the winter(from November to April). T_a exhibited an increasing trend from northwest to southeast. Except in the southeastern area of the NTP,T d values in other areas were all larger than 0℃ in the winter.     

那曲地区植被NDVI时空变化及成因分析

利用GIS和遥感技术方法分析了2000—2014年那曲地区植被归一化指数(NDVI)的时空分布特征和变化趋势,探讨了NDVI与几种气象因子的关系。结果表明:空间上,研究区植被NDVI在空间上呈自西向东、自南向北逐步增大,高海拔地区小于低海拔地区的分布特点;时间上,近15a的NDVI总体上呈不显著性下降趋势,NDVI变化可以分为3个阶段,分别为2000—2005年较好,2006—2008年略差,2009—2014年好转。植被面积变化趋势表现为西北部植被处于稳定状态的面积居多,变化较明显的区域集中在中部和东南部地区的人口密集区,改善和退化区域呈现交错出现的特点。那曲地区植被变化的主要影响因素为降水量和热量因素引起的,人类活动在较短时间尺度上对植被也有较大影响。     

Variability of African farming systems from phenological analysis of NDVI time series

Food security exists when people have access to sufficient, safe and nutritious food at all times to meet their dietary needs. The natural resource base is one of the many factors affecting food security. Its variability and decline creates problems for local food production. In this study we characterize for sub-Saharan Africa vegetation phenology and assess variability and trends of phenological indicators based on NDVI time series from 1982 to 2006. We focus on cumulated NDVI over the season (cumNDVI) which is a proxy for net primary productivity. Results are aggregated at the level of major farming systems, while determining also spatial variability within farming systems. High temporal variability of cumNDVI occurs in semiarid and subhumid regions. The results show a large area of positive cumNDVI trends between Senegal and South Sudan. These correspond to positive CRU rainfall trends found and relate to recovery after the 1980??s droughts. We find significant negative cumNDVI trends near the south-coast of West Africa (Guinea coast) and in Tanzania. For each farming system, causes of change and variability are discussed based on available literature (Appendix A). Although food security comprises more than the local natural resource base, our results can perform an input for food security analysis by identifying zones of high variability or downward trends. Farming systems are found to be a useful level of analysis. Diversity and trends found within farming system boundaries underline that farming systems are dynamic.