GF1-WFV与Landsat8-OLI对植被信息的提取差异研究

随着遥感技术的不断发展,中高分辨率影像逐渐在植被监测中发挥着重要的作用。为了明确高分辨率传感器在不同生态系统植被提取中的必要性,以内蒙古鄂伦春自治旗为研究对象,设置城市区域和森林区域两个应用靶区,以GF1-WFV和Landsat8-OLI两种传感器同期影像为对比数据集,探究不同分辨率下遥感植被信息提取差异。结果表明:①Landsat 8对比GF-1在城市区域和森林区域的植被指数高估、低估状态相反,城市区域GF-1的NDVI(Normalized Difference Vegetation Index,NDVI)和SAVI(Soil-Adjusted Vegetation Index,SAVI)均值比Landsat 8低5.69%和1.41%,在森林区域则高出0.77%和5.86%;②高分辨率影像避免了城市中绿化植被(GF-1植被占比71.30%和71.31%,Landsat 8为58.28%和58.30%)和森林中裸地、道路(GF-1植被占比94.97%和94.92%,Landsat 8为95.00%和94.99%)被漏提。③在分级面积上,Landsat 8相比GF-1数据在城市区域存在低覆盖度等级的6.67%和6.77%低估,在森林区域出现高覆盖度等级的12.11%和12.47%高估。研究结果反映了低绿化建成区和高密度林区更加需要使用高分影像作为植被监测工具。     

Monitoring temporal dynamics of Great Artesian Basin wetland vegetation,Australia, using MODIS NDVI

The Great Artesian Basin springs (Australia) are unique groundwater dependent wetland ecosystems of great significance, but are endangered by anthropogenic water extraction from the underlying aquifers. Relationships have been established between the wetland area associated with individual springs and their discharge, providing a potential means of monitoring groundwater flow using measurements of vegetated wetland area. Previous attempts to use this relationship to monitor GAB springs have used aerial photography or high resolution satellite images and gave sporadic temporal information. These “snapshot” studies need to be placed within a longer and more regular context to better assess changes in response to aquifer draw-downs. In this study we test the potential of 8 years of Moderate Resolution Imaging Spectroradiometer Normalised Difference Vegetation Index data as a long-term tracer of the temporal dynamics of wetland vegetation at the Dalhousie Springs Complex of the Great Artesian Basin. NDVI time series were extracted from MODIS images and phenologies of the main wetland vegetation species defined. Photosynthetic activity within wetlands could be discriminated from surrounding land responses in this medium resolution imagery. The study showed good correlation between wetland vegetated area and groundwater flow over the 2002–2010 period, but also the important influence of natural species phenologies, rainfall, and anthropogenic activity on the observed seasonal and inter-annual vegetation dynamics. Declining trends in the extent (km²) of vegetated wetland areas were observed between 2002 and 2009 followed by a return of wetland vegetation since 2010. This study underlines the need to continue long-term medium resolution satellite studies of the GAB to fully understand variability and trends in the spring-fed wetlands. The MODIS record allows a good understanding of variability within the wetlands, and gives a high temporal-frequency context for less frequent higher spatial resolution studies, therefore providing a strong baseline for assessment of future changes.     

Environmental controls of NDVI dynamics in Patagonia based on NOAA-AVHRR satellite data

Abstract. Variation in vegetation in extra-Andean Patagonia (Argentina) was analyzed using spectral data derived from AVHRR/NOAA satellite. The study of seasonal dynamics of the Normalized Difference Vegetation Index (NDVI, i.e. a combined index of the reflection in the red and infrared bands) highlighted similarities in functional aspects between regional vegetation units which are dissimilar in a geographical, physiognomical and/or floristical way, and also suggested that gross primary production is correlated with mean annual rainfall. The first axis in a Principal Component Analysis of NDVI data was correlated (r² = 0.90) with NDVI as integrated for the study period. The second axis was correlated (r² = 0.50) with the differences in NDVI during the growing season, reflecting seasonality. Mean annual rainfall accounted for 60% of integrated NDVI variability among vegetation units. Much of the residual variance (62%) was accounted for by the inverse of the distance to the Atlantic Ocean, which is interpreted as an ocean effect on vegetation functioning in the extra-Andean Patagonia.     

Advances in satellite remote sensing of pheno-climatic features for epidemiological applications

Geographical Information Systems (GIS) and Remote Sensing (RS) technologies are being used increasingly to study the spatial and temporal patterns of diseases. They can be used to complement conventional ecological monitoring and modelling techniques, and provide a means to portray complex relationships in the ecology of diseases with strong environmental determinants. In particular, satellite technology has been extraordinarily improved during recent years, providing new parameters useful to understand the epidemiology of parasites, such as vegetation indices, land surface temperatures, soil moisture and rainfall indices. In the present review, Normalized Difference Vegetation Index (NDVI) is primarily considered, since it is the index characterizing vegetation that is most used in epidemiological studies. Multi-temporal study of RS data allows collection of bio-climatic information about risk area distribution, along with predictive studies and anticipatory models of diseases, at different geographic scales ranging from global to local. The main physical and technological basis of a mathematical model, effective at different scales, for identification of landscape pheno-climatic features is described in the current paper.     

Predicting mountain plant richness and rarity from space using satellite-derived vegetation indices

Can species richness and rarity be predicted from space? If satellite‐derived vegetation indices can provide us with accurate predictions of richness and rarity in an area, they can serve as an excellent tool in diversity and conservation research, especially in inaccessible areas. The increasing availability of high‐resolution satellite images is enabling us to study this question more carefully. We sampled plant richness and rarity in 34 quadrats (1000 m²) along an elevation gradient between 300 and 2200 m focusing on Mount Hermon as a case study. We then used 10 Landsat, Aster, and QuickBird satellite images ranging over several seasons, going up to very high resolutions, to examine the relationship between plant richness, rarity, and vegetation indices calculated from the images. We used the normalized difference vegetation index (NDVI), one of the most commonly used vegetation indexes, which is strongly correlated to primary production both globally and locally (in more seasonal and in drier and/or colder environments that have wide ranges of NDVI values). All images showed a positive significant correlation between NDVI and both plant species richness and percentage tree cover (with R² as high as 0.87 between NDVI and total plant richness and 0.89 for annual plant richness). The high resolution images enabled us to examine spatial heterogeneity in NDVI within our quadrats. Plant richness was significantly correlated with the standard deviation of NDVI values (but not with their coefficient of variation) within quadrats and between images. Contrary to richness, relative range size rarity was negatively correlated with NDVI in all images, this result being significant in most cases. Thus, given that they are validated by fieldwork, satellite‐derived indices can shed light on richness and even rarity patterns in mountains, many of which are important biodiversity centres.     

Rangeland vegetation dynamics and moisture availability in Tunisia: an investigation using satellite and meteorological data

Improved knowledge of the interactions between regional climatic patterns and vegetation dynamics are necessary for predicting the future impacts of climate change on vegetation and biogeochemical processes. This paper describes how Normalized Difference Vegetation Index (NDVI) images generated from Advanced Very High Resolution Radiometer (AVHRR) satellite data were used to investigate the dynamics of rangeland vegetation in Tunisia. The NDVI images provided information about intra- and inter-annual variations in vegetation over nine growing seasons (1983–1992). Comparison of the NDVI data with field-collected ecological parameters for nine individual field sites indicated a strong relationship between the NDVI and percentage vegetation cover. The relationship between biomass measurements and NDVI was, however, less strong. Rainfall and NDVI data for each field site were compared, and significant relationships were found between the two. These indicated that there was a delay in the vegetation response to rainfall. In addition, the NDVI data showed that the vegetation at some of the field sites remained active throughout the summer although there was no rainfall during this period. TuMERT (Tunisian Model to Estimate Rangeland Transpiration), a simple water-balance model, was developed to estimate the amount of rainfall available for use by the vegetation during transpiration. The estimates of actual transpiration derived from TuMERT were found to be more strongly correlated with the AVHRR-NDVI measurements than the rainfall data.     

Identification of current ecosystem functional types in the Iberian Peninsula

Aim To examine the geographical patterns of the interception of photosynthetically active radiation by vegetation and to describe its spatial heterogeneity through the definition of ecosystem functional types (EFTs) based on the annual dynamics of the Normalized Difference Vegetation Index (NDVI), a spectral index related to carbon gains. Location The Iberian Peninsula. Methods EFTs were derived from three attributes of the NDVI obtained from NOAA/AVHRR sensors: the annual integral (NDVI‐I), as a surrogate of primary production, an integrative indicator of ecosystem functioning; and the intra‐annual relative range (RREL) and month of maximum NDVI (MMAX), which represent key features of seasonality. Results NDVI‐I decreased south‐eastwards. The highest values were observed in the Eurosiberian Region and in the highest Mediterranean ranges. Low values occurred in inner plains, river basins and in the southeast. The Eurosiberian Region and Mediterranean mountains presented the lowest RREL, while Eurosiberian peaks, river basins, inner‐agricultural plains, wetlands and the southeastern part of Iberia presented the highest. Eurosiberian ecosystems showed a summer maximum of NDVI, as did high mountains, wetlands and irrigated areas in the Mediterranean Region. Mediterranean mountains had autumn–early‐winter maxima, while semi‐arid zones, river basins and continental plains had spring maxima. Based on the behaviour in the functional traits, 49 EFTs were defined. Main conclusions The classification, based on only the NDVI dynamics, represents the spatial heterogeneity in ecosystem functioning by means of the interception of radiation by vegetation in the Iberian Peninsula. The patterns of the NDVI attributes may be used as a reference in evaluating the impacts of environmental changes. Iberia had a high spatial variability: except for biophysically impossible combinations (high NDVI‐I and high seasonality), almost any pattern of seasonal dynamics of radiation interception was represented in the Peninsula. The approach used to define EFTs opens the possibility of monitoring and comparing ecosystem functioning through time.     

Environmental controls of NDVI and sheep production in the Tierra del Fuego steppe of Argentina

Abstract. We analysed vegetation dynamics in Tierra del Fuego steppes using Normalized Difference Vegetation Index (NDVI) data provided by advanced very high‐resolution radiometer (AVHRR) on board the National Oceanic and Atmospheric Administration (NOAA) polar satellite. Our objective, at a regional scale, was to analyse the spatial variability of NDVI dynamics in relation to parent material and geographic location, representing the fertility and climate gradients respectively; at a local scale, it was to analyse the inter‐annual variability associated with climate and its relation with sheep production indices. The general pattern of NDVI dynamics was analysed with Principal Component Analysis. We found that the geographic location was more important than landscape type in explaining NDVI dynamics despite the fact that the variation in landscape type reflects a fertility gradient strongly associated with floristic composition and secondary productivity. Discriminant Analysis was performed to identify the variables that better distinguish geographic units. The Northern region (with the lowest precipitation and the highest temperatures) had lower NDVI values over the year. In the Central region, NDVI reached the highest value of the season, surpassing both other regions. The Southern region (the coldest and moistest) had its growth pattern displaced towards the summer. For the Central region we analysed 10 years of monthly NDVI data with PCA. We found that precipitation from August to December and winter temperature are the most important determinants of overall NDVI values. Lamb production was correlated with spring and early summer NDVI values. Sheep mortality is affected by low NDVI values in late summer and high annual amplitude. Satellite information allowed us to characterize the vegetation dynamics of three ecological areas across the Fuegian steppe.     

利用影像判读与群落监测分析长白山针叶林动态

基于不同空间尺度即永久标准地的群落学调查与卫星遥感监测相结合研究了长白山亚高山针叶林的结构与动态．标准地两次调查的间隔为11年．结果表明,每10年的死亡率为7％～9％,进界比率为18％～20％．鱼鳞云杉、臭冷杉及岳桦可以在林冠下顺利完成更新,而长白落叶松为先锋种,只能在林窗或裸地更新．落叶松为云杉及冷杉提供良好的更新条件,从而在维持亚高山森林的稳定性上起着重要作用．成熟林密度(1000株·hm^-2左右)变化不大．利用美国陆地卫星TM图像分析1984～1997年植被变化表明,大规模的风倒等自然干扰很容易检测出来,从景观尺度上,利用TM图像监测植被变化非常有效．不同反射强度变化的象素数量统计结果表明,群落的进展演替与逆向演替同时存在,并处于相对平衡状态,但由于图像分辨率(30m×30m)的关系,林窗很难同噪声区分开来．长白山亚高山针叶林带因有大量的落叶松斑块而呈现出镶嵌结构,这种镶嵌结构被定义为亚高山植被的顶极状态,在小尺度上,例如面积仅为几公顷的标准地,特别是混有落叶松等先锋树种的群落,种类组成随时间而变化,但是卫星图像分析结果证明：整体上,亚高山植被处于稳定状态。     

Increasing terrestrial vegetation activity in China, 1982-1999

Variations in vegetation activity during the past 18 years in China were investigated using the normalized difference vegetation index (NDVI) derived from the 3rd generation time series dataset of NOAA-AVHRR from 1982 to 1999. In order to eliminate the effects of non-vegetation factors, we characterized areas with NDVI < 0.1 as "sparsely vegetated areas" and areas with NDVI ≥ 0.1 as "vegetated areas". The results showed that increasing NDVI trends were evident, to varying extents, in almost all regions in China in the 18 years, indicating that vegetation activity has been rising in recent years in these regions. Compared to the early 1980s, the vegetated area increased by 3.5% by the late 1990s, while the sparsely vegetated area declined by 18.1% in the same period. The national total mean annual NDVI increased by 7.4% during the study period. Extended growing seasons and increased plant growth rates accounted for the bulk of these increases, while increases in temperature and summer rainfall, and strengthening agricultural activity were also likely important factors. NDVI changes in China exhibited relatively large spatial heterogeneity; the eastern coastal regions experienced declining or indiscernibly rising trends, while agricultural regions and western China experienced marked increases. Such a pattern was due primarily to urbanization, agricultural activity, regional climate characteristics, and different vegetation responses to regional climate changes.     

Satellite-based Studies on Large-Scale Vegetation Changes in China

Remotely-sensed vegetation indices, which indicate the density and photosynthetic capacity of vegetation, have been widely used to monitor vegetation dynamics over broad areas. In this paper, we reviewed satellite-based studies on vegetation cover changes, biomass and productivity variations, phenological dynamics, desertification, and grassland degradation in China that occurred over the past 2–3 decades. Our review shows that the satellite-derived index (Normalized Difference Vegetation Index, NDVI) during growing season and the vegetation net primary productivity in major terrestrial ecosystems (for example forests, grasslands, shrubs, and croplands) have significantly increased, while the number of fresh lakes and vegetation coverage in urban regions have experienced a substantial decline. The start of the growing season continually advanced in China's temperate regions until the 1990s, with a large spatial heterogeneity. We also found that the coverage of sparsely-vegetated areas declined, and the NDVI per unit in vegetated areas increased in arid and semi-arid regions because of increased vegetation activity in grassland and oasis areas. However, these results depend strongly not only on the periods chosen for investigation, but also on factors such as data sources, changes in detection methods, and geospatial heterogeneity. Therefore, we should be cautious when applying remote sensing techniques to monitor vegetation structures, functions, and changes.     

Increasing terrestrial vegetation activity in China, 1982—1999

Variations in vegetation activity during the past 18 years in China were investigated using the normalized difference vegetation index (NDVI) derived from the 3rd generation time series dataset of NOAA-AVHRR from 1982 to 1999. In order to eliminate the effects of non-vegetation factors, we characterized areas with NDVI < 0.1 as “sparsely vegetated areas” and areas with NDVI ≥ 0.1 as “vegetated areas”. The results showed that increasing NDVI trends were evident, to varying extents, in almost all regions in China in the 18 years, indicating that vegetation activity has been rising in recent years in these regions. Compared to the early 1980s, the vegetated area increased by 3.5% by the late 1990s, while the sparsely vegetated area declined by 18.1% in the same period. The national total mean annual NDVI increased by 7.4% during the study period. Extended growing seasons and increased plant growth rates accounted for the bulk of these increases, while increases in temperature and summer rainfall, and strengthening agricultural activity were also likely important factors. NDVI changes in China exhibited relatively large spatial heterogeneity; the eastern coastal regions experienced declining or indiscernibly rising trends, while agricultural regions and western China experienced marked increases. Such a pattern was due primarily to urbanization, agricultural activity, regional climate characteristics, and different vegetation responses to regional climate changes.     

Spectral response of the seagrass Zostera noltii with different sediment backgrounds

The efficiency of vegetation indices (VIs) to estimate the above-ground biomass of the seagrass species Zostera noltii Hornem. from remote sensing was tested experimentally on different substrata, since terrestrial vegetation studies have shown that VIs can be adversely influenced by the spectral properties of soils and background surfaces. Leaves placed on medium sand, fine sand and autoclaved fine sand were incrementally removed, and the spectral reflectance was measured in the 400–900 nm wavelength range. Several VIs were evaluated: ratios using visible and near infrared wavelengths, narrow-band indices, indices based on derivative analysis and continuum removal. Background spectral reflectance was clearly visible in the leaf reflectance spectra, showing marked brightness and spectral contrast variations for the same amount of vegetation. Paradoxically, indices used to minimize soil effects, such as the Soil-Adjusted Vegetation Index (SAVI) and the Modified second Soil-Adjusted Vegetation Index (MSAVI₂) showed a high sensitivity to background effects. Similar results were found for the widely used Normalized Difference Vegetation Index (NDVI) and for Pigment Specific Simple Ratios (PSSRs). In fact, background effects were most reduced for VIs integrating a blue band correction, namely the modified specific ratio (mSR₍₇₀₅₎), the modified Normalized Difference (mND₍₇₀₅₎), and two modified NDVIs proposed in this study. However, these indices showed a faster saturation for high seagrass biomass. The background effects were also substantially reduced using Modified Gaussian Model indices at 620 and 675 nm. The blue band corrected VIs should now be tested for air-borne or satellite remote sensing applications, but some require sensors with a hyperspectral resolution. Nevertheless, this type of index can be applied to analyse broad band multispectral satellite images with a blue band.     

陕北长城沿线风沙区植被指数变化及其与气候的关系

陕北长城沿线风沙区位于毛乌素沙漠东南部边沿,属毛乌素沙地向东南移动的最活跃地段,生态环境十分脆弱。使用1981～2003年23a长时间序列的NOAA/AHRR NDVI数据、气候资料,分析了陕北长城沿线风沙区植被覆盖的历史演变及其与气候因子的关系。结果表明:(1)陕北长城沿线风沙区植被覆盖状况23a来尽管有波动起伏,但是整体在持续转好,年平均NDVI增加了10.62%。低覆盖率植被面积在减少,高覆盖率植被面积在增加。夏季的NDVI值最高、波动起伏最大,其次是秋季;春、夏、秋三季的NDVI具有明显的上升趋势,季平均NDVI年增长率夏季最大,秋季次之;夏、秋季NDVI与年NDVI具有很高的相关性,这两个季节的植被状况基本决定了全年的植被分布状况。NDVI年变化曲线为单峰型,春季NDVI缓慢增加,秋季NDVI降低速度比较快。(2)年平均NDVI与温度的年际变化相关不明显,各季节NDVI与温度相关也不明显。近年来长城沿线风沙区的年降水量没有明显增加,而年平均NDVI线性增加趋势显著,降水量是引起NDVI年际波动的主要因子,非气候因素是年平均NDVI线性增加的主要原因。降水量与NDVI存在着明显的年相关和隔季相关。年降水量与年NDVI的相关,冬季降水量与春季NDVI的相关,春季降水量与夏季NDVI的相关,夏季降水量与秋季NDVI的相关性都非常高。(3)非气候因素中生态保护和环境建设等人为措施,如植树造林、草原围栏封育等是导致植被显著增加的重要原因。     

Satellite sun‐induced chlorophyll fluorescence detects early response of winter wheat to heat stress in the Indian Indo‐Gangetic Plains

Extremely high temperatures represent one of the most severe abiotic stresses limiting crop productivity. However, understanding crop responses to heat stress is still limited considering the increases in both the frequency and severity of heat wave events under climate change. This limited understanding is partly due to the lack of studies or tools for the timely and accurate monitoring of crop responses to extreme heat over broad spatial scales. In this work, we use novel spaceborne data of sun‐induced chlorophyll fluorescence (SIF), which is a new proxy for photosynthetic activity, along with traditional vegetation indices (Normalized Difference Vegetation Index NDVI and Enhanced Vegetation Index EVI) to investigate the impacts of heat stress on winter wheat in northwestern India, one of the world's major wheat production areas. In 2010, an abrupt rise in temperature that began in March adversely affected the productivity of wheat and caused yield losses of 6% compared to previous year. The yield predicted by satellite observations of SIF decreased by approximately 13.9%, compared to the 1.2% and 0.4% changes in NDVI and EVI, respectively. During early stage of this heat wave event in early March 2010, the SIF observations showed a significant reduction and earlier response, while NDVI and EVI showed no changes and could not capture the heat stress until late March. The spatial patterns of SIF anomalies closely tracked the temporal evolution of the heat stress over the study area. Furthermore, our results show that SIF can provide large‐scale, physiology‐related wheat stress response as indicated by the larger reduction in fluorescence yield (SIF_yield) than fraction of photosynthetically active radiation during the grain‐filling phase, which may have eventually led to the reduction in wheat yield in 2010. This study implies that satellite observations of SIF have great potential to detect heat stress conditions in wheat in a timely manner and assess their impacts on wheat yields at large scales.     

中国东北地区主要植被类型NDVI变化与气候因子的关系

利用1982～1992年时间序列的NOAA/AVHRR8km×8km分辨率的归一化植被指数（Normalizeddifferencevegetationindex,NDVI）,将东经120°～135°、北纬40°～55°区域的土地覆盖类型分为10类。然后研究了各类型的NDVI年平均值的变化规律。结合该地区的19个气象站1982～1992年的年平均气温、年最高温度、年最低温度、年降水量和年相对湿度研究了各类型NDVI年平均值的变化与气候因子之间的关系,进一步阐明了气候因子是NDVI动态变化的主要原因。     

Northern hemisphere photosynthetic trends 1982–99

We examined trends in the averaged May–September AVHRR normalized difference vegetation index (NDVI) from 1982 to 1999 for the northern hemisphere. NDVI is closely related to the amount of absorbed photosynthetically active radiation; hence, trends in NDVI reflect trends in photosynthetic activity of land‐surface vegetation. Linear and nonlinear trend analysis techniques were applied to four differently processed and corrected Advanced Very High Resolution Radiometer (AVHRR) NDVI data sets. The results were compared in order to evaluate the effects of trends in NDVI unrelated to vegetation activity. We consistently found significant positive trends in averaged NDVI for latitude bands above 35°N in all but one data set; this one data set lacked corrections for sensor drift and instrument calibration. An impressive improvement in data quality was achieved by applying calibration and corrections for atmospheric effects. Conservative estimates of the trends over the 1982–99 period range from 0.0015 to 0.0045 NDVI units year^?1 for global latitude bands from 35 to 75°N, with trends generally higher in the 1990s than in the 1980s; trends in NDVI were larger than trends explained by artefacts. In the 1980s, North American and Eurasian trends were roughly comparable, whereas in the 1990s the North American trends were generally higher. A pixel‐level analysis shows the trends to be widespread, with large areas of Canada, Europe and northern Asia experiencing significant positive increases across all vegetated landcovers.     

Increasing terrestrial vegetation activity in China, 1982–1999

Variations in vegetation activity during the past 18 years in China were investigated using the normalized difference vegetation index (NDVI) derived from the 3rd generation time series dataset of NOAA-AVHRR from 1982 to 1999. In order to eliminate the effects of non-vegetation factors, we characterized areas with NDVI < 0.1 as “sparsely vegetated areas” and areas with NDVI ≥0.1 as “vegetated areas”. The results showed that increasing NDVI trends were evident, to varying extents, in almost all regions in China in the 18 years, indicating that vegetation activity has been rising in recent years in these regions. Compared to the early 1980s, the vegetated area increased by 3.5% by the late 1990s, while the sparsely vegetated area declined by 18.1% in the same period. The national total mean annual NDVI increased by 7.4% during the study period. Extended growing seasons and increased plant growth rates accounted for the bulk of these increases, while increases in temperature and summer rainfall, and strengthening agricultural activity were also likely important factors. NDVI changes in China exhibited relatively large spatial heterogeneity; the eastern coastal regions experienced declining or indiscernibly rising trends, while agricultural regions and western China experienced marked increases. Such a pattern was due primarily to urbanization, agricultural activity, regional climate characteristics, and different vegetation responses to regional climate changes.     

黄土高原地区提取植被信息方法的研究

研究评价了适于黄土高原地区植被信息提取的最佳植被指数和方法。该地区分布有落叶阔叶林、草原和荒漠,植被类型丰富多样。然而土壤背景对植被信息提取有较大影响。经对比分析,修正后的土壤调节植被指数（ＭＳＡＶＩ）, 不仅能增强植被信号,并能大大减小土壤背景的影响,同时又能宏观地反映该地区植被类型的分布状况。它是黄土高原地区目前提取植被信息较好的植被指数。标准化差值植被指数（ＮＤＶＩ）、土壤调节植被指数（ＳＡＶＩ）和垂直植被指数（ＰＶＩ）分别适用于高密度、中等密度和稀少植被地区植被信息的提取和监测。各种植被指数多时象累加产生的图像能较好地提取植被信息     

Modeling gross primary productivity of alpine meadow in the northern Tibet Plateau by using MODIS images and climate data

The Vegetation Photosynthesis Model (VPM) was used to simulate the gross primary productivities (GPP) of the alpine meadow ecosystem in the northern Tibet Plateau at three different spatial resolutions of 0.5 km, 1.5 km and 2.5 km, respectively. The linear relationships between enhanced vegetation indices (EVI) and GPP, with higher correlative coefficients, were better than those between normalized difference vegetation indices (NDVI) and GPP at the three resolutions. VPM could well simulate the seasonal changes and inter-annual variations of GPP, with similar trends at the three resolutions. There were significant differences (P < 0.0001) among the three modeled GPP with the three resolutions. Therefore, the modeled GPP at high resolution could not be directly extrapolated to low resolution, and vice versa. The contribution levels of different model parameters, including photosynthetically active radiation (PAR), air temperature (Ta), NDVI, EVI and land surface water indices (LSWI), to modeled GPP could vary with spatial resolution based on multiple stepwise linear regression analysis. This indicated that it was important to choose parameters properly and consider their effects on modeled GPP.