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1.
Recent advances in remote sensing technology and methods have resulted in the development of an evapotranspiration(ET) product from the Moderate Resolution Imaging Spectrometer(MOD16). The accuracy of this product however has not been tested for coastal wetland ecosystems. The objective of this study therefore is to validate the MOD16 ET product using data from one eddy covariance flux tower situated in the Panjin coastal wetland ecosystem within the Liaohe River Delta, Northeast China. Cumulative ET data over an eight-day period in 2005 from the flux tower was calculated to coincide with the MOD16 products across the same period. Results showed that data from the flux tower were inconsistent with that gained form the MOD16 ET. In general, results from Panjin showed that there was an underestimation of MOD16 ET in the spring and fall, with Biases of -2.27 and -3.53 mm/8 d, respectively(–40.58% and -49.13% of the observed mean). Results for Bias during the summer had a range of 1.77 mm/8 d(7.82% of the observed mean), indicating an overestimation of MOD16 ET. According to the RMSE, summer(6.14 mm/8 d) achieved the lowest value, indicating low accuracy of the MOD16 ET product. However, RMSE(2.09 mm/8 d) in spring was the same as that in the fall. Relationship between ET and its relevant meteorological parameters were analyzed. Results indicated a very good relationship between surface air temperature and ET. Meanwhile a significant relationship between wind speed and ET also existed. The inconsistent comparison of MOD16 and flux tower-based ET are mainly attributed to the parameterization of the Penman-Monteith model, flux tower measurement errors, and flux tower footprint vs. MODIS pixels.  相似文献   

2.
Multi-temporal series of satellite SPOT-VEGETATION normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) data from 1998 to 2007 were used for analyzing vegetation change of the ecotone in the west of the Northeast China Plain. The yearly and monthly maximal values,anomalies and change rates of NDVI and NDWI were calculated to reveal the interannual and seasonal changes in vegetation cover and vegetation water content. Linear regression method was adopted to characterize the trends in vegetation change. The yearly maximal NDVI decreased from 0.41 in 1998 to 0.37 in 2007,implying the decreasing trend of vegetation activity. There was a significant decrease of maximal NDVI in spring and summer over the study period,while an increase trend was observed in autumn. The vegetation-improved regions and vegetation-degraded regions occupied 17.03% and 20.30% of the study area,respectively. The maximal NDWI over growing season dropped by 0.027 in 1998–2007,and about 15.15% of the study area showed a decreasing trend of water content. Vegetation water stress in autumn was better than that in spring. Vegetation cover and water content variations were sensitive to annual precipitation,autumn precipitation and summer temperature. The vegetation degradation trend in this ecotone might be induced by the warm-drying climate especially continuous spring and summer drought in the recent ten years.  相似文献   

3.
The sub-pixel impervious surface percentage(SPIS) is the fraction of impervious surface area in one pixel,and it is an important indicator of urbanization.Using remote sensing data,the spatial distribution of SPIS values over large areas can be extracted,and these data are significant for studies of urban climate,environment and hydrology.To develop a stabilized,multi-temporal SPIS estimation method suitable for typical temperate semi-arid climate zones with distinct seasons,an optimal model for estimating SPIS values within Beijing Municipality was built that is based on the classification and regression tree(CART) algorithm.First,models with different input variables for SPIS estimation were built by integrating multi-source remote sensing data with other auxiliary data.The optimal model was selected through the analysis and comparison of the assessed accuracy of these models.Subsequently,multi-temporal SPIS mapping was carried out based on the optimal model.The results are as follows:1) multi-seasonal images and nighttime light(NTL) data are the optimal input variables for SPIS estimation within Beijing Municipality,where the intra-annual variability in vegetation is distinct.The different spectral characteristics in the cultivated land caused by the different farming characteristics and vegetation phenology can be detected by the multi-seasonal images effectively.NLT data can effectively reduce the misestimation caused by the spectral similarity between bare land and impervious surfaces.After testing,the SPIS modeling correlation coefficient(r) is approximately 0.86,the average error(AE) is approximately 12.8%,and the relative error(RE) is approximately 0.39.2) The SPIS results have been divided into areas with high-density impervious cover(70%–100%),medium-density impervious cover(40%–70%),low-density impervious cover(10%–40%) and natural cover(0%–10%).The SPIS model performed better in estimating values for high-density urban areas than other categories.3) Multi-temporal SPIS mapping(1991–2016) was conducted based on the optimized SPIS results for 2005.After testing,AE ranges from 12.7% to 15.2%,RE ranges from 0.39 to 0.46,and r ranges from 0.81 to 0.86.It is demonstrated that the proposed approach for estimating sub-pixel level impervious surface by integrating the CART algorithm and multi-source remote sensing data is feasible and suitable for multi-temporal SPIS mapping of areas with distinct intra-annual variability in vegetation.  相似文献   

4.
Seasonal snow is one of the most important influences on the development and distribution of permafrost and the hydrothermal regime in surface soil. Alpine meadow, which constitutes the main land type in permafrost regions of the Qinghai-Tibet Plateau, was selected to study the influence of seasonal snow on the temperature and moisture in active soil layers under different vegetation coverage. Monitoring sites for soil moisture and temperature were constructed to observe the hydrothermal processes in active soil layers under different vegetation cover with seasonal snow cover variation for three years from 2010 to 2012. Differences in soil temperature and moisture in areas of diverse vegetation coverage with varying levels of snow cover were analyzed using active soil layer water and temperature indices. The results indicated that snow cover greatly influenced the hydrothermal dynamics of the active soil layer in alpine meadows. In the snow manipulation experiment with a snow depth greater than 15 cm, the snow cover postponed both the freeze-fall and thawrise onset times of soil temperature and moisture in alpine LC （lower vegetation coverage） meadows and of soil moisture in alpine HC （higher vegetation coverage） meadows; however, the opposite response occurred for soil temperatures of alpine HC meadows,where the entire melting period was extended by advancing the thaw-rise and delaying the freeze-fall onset time of the soil temperature. Snow cover resulted in a decreased amplitude and rate of variation in soil temperature, for both alpine HC meadows and alpine LC meadows, whereas the distinct influence of snow cover on the amplitude and rate of soil moisture variation occurred at different soil layers with different vegetation coverages. Snow cover increased the soil moisture of alpine grasslands during thawing periods. The results confirmed that the annual hydrothermal dynamics of active layers in permafrost were subject to the synergistic actions of both snow cover and vegetation coverage.  相似文献   

5.
Guizhou Province is an important karst area in the world and a fragile ecological area in China. Ecological risk assessment is very necessary to be conducted in this region. This study investigates different characteristics of the spatial-temporal changes of vegetation cover in Guizhou Province of Southern China using the data set of SPOT VEGETATION(1999–2015) at spatial resolution of 1-km and temporal resolution of 10-day. The coefficient of variation, the Theil-Sen median trend analysis, and the Mann-Kendall test are used to investigate the spatial-temporal change of vegetation cover and its future trend. Results show that: 1) the spatial distribution pattern of vegetation cover in Guizhou Plateau is high in the east whereas low in the west. The average annual normalized difference vegetation index(NDVI) from west to east is higher than that from south to north. 2) Average annual NDVI improved obviously in the past 17 years. The growth rate of average annual NDVI is 0.028/10 yr, which is slower than that of vegetation in the country(0.048/10 yr) from 1998 to 2007. Average annual NDVI in karst area is lower than that in non-karst area. However, the growing rate of average annual NDVI in karst area(0.030/10 yr) is faster than that in non-karst area(0.023/10 yr), indicating that vegetation coverage increases more rapidly in karst area. 3) Vegetation coverage in the study area is stable overall, but fluctuates in the local scales. 4) Vegetation coverage presents a continuous increasing trend. The Hurst exponent of NDVI in different vegetation types has an obvious threshold in various elevations. 5) The proportion of vegetation cover with sustainable increase is higher than that of vegetation cover with sustainable decrease. The improvement in vegetation cover may expand to most parts of the study area.  相似文献   

6.
Vegetation phenology is an indicator of vegetation response to natural environmental changes and is of great significance for the study of global climate change and its impact on terrestrial ecosystems. The normalized difference vegetation index(NDVI) and enhanced vegetation index(EVI), extracted from the Moderate Resolution Imaging Spectrometer(MODIS), are widely used to monitor phenology by calculating land surface reflectance. However, the applicability of the vegetation index based on ‘greenness' to monitor photosynthetic activity is hindered by poor observation conditions(e.g., ground shadows, snow, and clouds). Recently, satellite measurements of solar-induced chlorophyll fluorescence(SIF) from OCO-2 sensors have shown great potential for studying vegetation phenology. Here, we tested the feasibility of SIF in extracting phenological metrics in permafrost regions of the northeastern China, exploring the characteristics of SIF in the study of vegetation phenology and the differences between NDVI and EVI. The results show that NDVI has obvious SOS advance and EOS lag, and EVI is closer to SIF. The growing season length based on SIF is often the shortest, while it can represent the true phenology of vegetation because it is closely related to photosynthesis. SIF is more sensitive than the traditional remote sensing indices in monitoring seasonal changes in vegetation phenology and can compensate for the shortcomings of traditional vegetation indices. We also used the time series data of MODIS NDVI and EVI to extract phenological metrics in different permafrost regions. The results show that the length of growing season of vegetation in predominantly continuous permafrost(zone I) is longer than in permafrost with isolated taliks(zone II). Our results have certain significance for understanding the response of ecosystems in cold regions to global climate change.  相似文献   

7.
Comparison of some vegetation indices in seasonal information   总被引：1，自引：1，他引：0  
With the development of vegetation indices, the reflection capability of vegetation indices to the state of vegetation has been improved in various degrees. Especially, the vegetation index of Terra/MODIS-EVI is believed to have the highest sensitivity to the seasonality of vegetation. This study compares the reflection susceptibility of three vegetation indices （NOAA/AVHRR-NDVI, Terra/MODIS-NDVI and Terra/MODIS-EVI） to the seasonal variations of vegetation in the mid-south of Yunnan Province of China. It has been found that Terra/MODIS-EVI does best in the elimination of external disturbance. Firstly, it obviously improves the linear relationship with vegetation cover degree, especially in the high vegetation coverage area. Secondly, it avoids the emergence of vegetation index saturation. Thirdly, it reduces the environmental influence including both effects of atmosphere and soil. So it is believed that the Terra/MODIS-EVI can offer excellent tool for quantitative research of remote sensing, and has realized to be oriented by data with high quality.  相似文献   

8.
In order to investigate the transformation among the precipitation,groundwater,and surface water in the Sanjiang Plain,Northeast China,precipitation and groundwater samples which were collected at the meteorological station of the Sanjiang Mire Wetland Experimental Station,Chinese Academy of Sciences and the surface water which collected from the Wolulan River were used to identify the transformation of three types of water.The isotope composition of different kinds of water sources were analyzed via stable isotope(deuterium and oxygen-18) investigation of natural water.The results show a clear seasonal difference in the stable isotopes in precipitation.During the cold half-year,the mean stable isotope in precipitation in the Sanjiang Plain reaches its minimum with the minimum temperature.The δ18O and δD values are high in the rainy season.In the Wolulan River,the evaporation is the highest in August and September.The volume of evaporation and the replenishment to the river is mostly same.The groundwater is recharged more by the direct infiltration of precipitation than by the river flow.The results of this study indicate that the water bodies in the Sanjiang Plain have close hydrologic relationships,and that the transformation among each water system frequently occurs.  相似文献   

9.
This paper proposes a WD-GA-LSSVM model for predicting the displacement of a deepseated landslide triggered by seasonal rainfall,in which wavelet denoising(WD)is used in displacement time series of landslide to eliminate the GPS observation noise in the original data,and genetic algorithm(GA)is applied to obtain optimal parameters of least squares support vector machines(LSSVM)model.The model is first trained and then evaluated by using data from a gentle dipping(~2°-5°)landslide triggered by seasonal rainfall in the southwest of China.Performance comparisons of WD-GA-LSSVM model with Back Propagation Neural Network(BPNN)model and LSSVM are presented,individually.The results indicate that the adoption of WD-GA-LSSVM model significantly improves the robustness and accuracy of the displacement prediction and it provides a powerful technique for predicting the displacement of a rainfall-triggered landslide.  相似文献   

10.
The Qilian Mountains(QM) possess a delicate vegetation ecosystem, amplifying the evident response of vegetation phenology to climate change. The relationship between changes in vegetation growth and climate remains complex. To this end, we used MODIS NDVI data to extract the phenological parameters of the vegetation including meadow(MDW), grassland(GSD), and alpine vegetation(ALV) in the QM from 2002 to 2021. Then, we employed path analysis to reveal the direct and indirect impacts of seasonal c...  相似文献   

11.
基于MOD16产品的我国2001-2010年蒸散发时空格局变化分析   总被引：6，自引：0，他引：6  
蒸散发的时空格局分析对理解气候变化与水资源之间的相互影响具有重要的作用。本文基于MODIS全球蒸散发产品(MOD16),分析了2001-2010年我国陆面蒸散发的时空格局变化,得出以下结论：(1)站点尺度和流域尺度的精度验证结果表明,MOD16产品对于我国森林、农田生态系统类型,以及辽河、海河、黄河和淮河流域的模拟精度较高;(2)2001-2010年,我国年均蒸散发为532±10 mm,年内蒸散值变化最大的是东北区,月均蒸散变异系数为0.87,而西北区变化幅度最小,变异系数为0.19;(3)2001-2010年,我国陆面蒸散发年际变化总的趋势不明显,占陆地面积11.2%区域的蒸散发呈显著减少趋势(p<0.05),主要分布在青藏高原中部,内蒙古中东部地区及新疆北部,只有2.3%的区域的蒸散发增加趋势显著,(p<0.05),主要分布在黄土高原地区、黄淮海平原及东北平原;(4)通过对比干旱指数变化趋势、植被指数变化趋势图可以看出,蒸散发显著减少的区域主要分布于干旱加剧的半干旱地区,而蒸散发显著增加的区域主要位于植被变好的地区。  相似文献   

12.
As a key parameter for indicating the fraction of surface-reflected solar incident radiation, land surface albedo plays an important role in the Earth's surface energy budget(SEB). Since the Sanjiang Plain has been severely affected by human activities(e.g., reclamation and shrinking of wetlands), it is important to assess the spatiotemporal variations of surface albedo in this region using a long-term remote sensing dataset. In order to investigate the surface albedo climatology, trends, and mechanisms of change, we evaluated the surface albedo variations in the Sanjiang Plain, China from 1982 to 2015 using the Global LAnd Surface Satellite(GLASS) broadband surface albedo product. The results showed that: 1) an increasing annual trend(+0.000 58/yr) of surface albedo was discovered in the Sanjiang Plain based on the GLASS albedo dataset, with a much stronger increasing trend(+0.001 26/yr) occurring during the winter. Most of the increasing trends occurred over the cultivated land, unused land, and land use conversion types located in the northeastern Sanjiang Plain. 2) The increasing trend of land surface albedo in Sanjiang Plain can be largely explained by the changes of both snow cover extent and land use. The surface albedo in winter is highly correlated with the snow cover extent in the Sanjiang Plain, and the increasing trend of surface albedo can be further enhanced by the land use changes.  相似文献   

13.
Three-River Headwaters(TRH) region involved in this paper refers to the source region of the Changjiang(Yangtze) River,the Huanghe(Yellow) River and the Lancang River in China.Taking the TRH region of the Qinghai-Tibet Plateau as a case,the annual evapotranspiration(ET) model developed by Zhang et al.(2001) was applied to evaluate mean annual ET in the alpine area,and the response of annual ET to land use change was analyzed.The plant-available water coefficient(w) of Zhang’s model was revised by using vegetation-temperature condition index(VTCI) before annual ET was calculated in alpine area.The future land use scenario,an input of ET model,was spatially simulated by using the conversion of land use and its effects at small regional extent(CLUE-S) to study the response of ET to land use change.Results show that the relative errors between the simulated ET and that calculated by using water balance equation were 3.81% and the index of agreement was 0.69.This indicates that Zhang’s ET model based on revised plant-available water coefficient is a scientific and practical tool to estimate the annual ET in the alpine area.The annual ET in 2000 in the study area was 221.2 mm,11.6 mm more than that in 1980.Average annual ET decreased from southeast to northwest,but the change of annual ET between 1980 and 2000 increased from southeast to northwest.As a vast and sparsely populated area,the population in the TRH region was extremely unbalanced and land use change was concentrated in very small regions.Thus,land use change had little effect on total annual ET in the study area but a great impact on its spatial distribution,and the effect of land use change on ET decreased with increasing precipitation.ET was most sensitive to the interconversion between forest and unused land,and was least sensitive to the interconversion between cropland and low-covered grassland.  相似文献   

14.
The main objective of this research is to determine the capacity of land cover classification combining spectral and textural features of Landsat TM imagery with ancillary geographical data in wetlands of the Sanjiang Plain, Heilongjiang Province, China. Semi-variograms and Z-test value were calculated to assess the separability of grey-level co-occurrence texture measures to maximize the difference between land cover types. The degree of spatial autocorrelation showed that window sizes of 3×3 pixels and 11×11 pixels were most appropriate for Landsat TM image texture calculations. The texture analysis showed that co-occurrence entropy, dissimilarity, and variance texture measures, derived from the Landsat TM spectrum bands and vegetation indices provided the most significant statistical differentiation between land cover types. Subsequently, a Classification and Regression Tree (CART) algorithm was applied to three different combinations of predictors: 1) TM imagery alone (TM-only); 2) TM imagery plus image texture (TM+TXT model); and 3) all predictors including TM imagery, image texture and additional ancillary GIS information (TM+TXT+GIS model). Compared with traditional Maximum Likelihood Classification (MLC) supervised classification, three classification trees predictive models reduced the overall error rate significantly. Image texture measures and ancillary geographical variables depressed the speckle noise effectively and reduced classification error rate of marsh obviously. For classification trees model making use of all available predictors, omission error rate was 12.90% and commission error rate was 10.99% for marsh. The developed method is portable, relatively easy to implement and should be applicable in other settings and over larger extents.  相似文献   

15.
叶面积指数是描述土壤-植被-大气之间物质和能量交换的关键参数,获取大区域长时间序列叶面积指数有助于研究气候变化条件下植被的响应及反馈。本文利用MODIS观测和经过重新处理的地表长时间数据集（Land Long Term Data Record）LTDR AVHRR数据,生成了全球1981-2012年叶面积指数数据。算法通过建立二者之间像元级关系,利用高质量MODIS观测约束历史AVHRR数据的反演,这有助于减小2种存在显著差别传感器反演结果的不一致性,也有助于提高AVHRR反演质量。首先算法利用高质量MODIS地表反射率反演2000-2012年叶面积指数,然后利用多年每8 d的LTDR AVHRR地表反射率数据计算简单比植被指数（Simple Ratio,SR）,利用SR平均值和MODIS LAI平均值建立像元级AVHRR SR-MODIS LAI关系。在此基础上,实现1981-1999年AVHRR LAI反演,最终得到全球1981-2012年叶面积指数数据。本算法反演的AVHRR和MODIS LAI与全球植被的空间分布吻合,能表征主要生物群系类型的季节变化特征,2个数据集一致性较好,并且与NASA MODIS LAI标准产品（MOD15A2）的空间分布和季节变化曲线吻合较好。  相似文献   

16.
本文以2007年和2008年MODIS每日地表温度（LST）数据及AMSR-E地表亮温（BT）数据为研究对象,结合土地覆盖类型数据,统计分析MODIS_LST与AMSR-E_BT在不同土地覆盖类型、频率和极化方式条件下的相关性。结果表明,频率在18.7、23.8和36.5 GHz的AMSR-E-BT与MODIS_LST的相关性较大,且在垂直极化通道上的相关性较在水平极化上大;不同土地覆盖类型,与MODIS_LST相关性较大所对应的AMSR-E微波通道不同。同时,考虑混合像元问题对相关性的影响,对25种不同地物类型组合下MODIS_LST与AMSR-E-BT的相关性进行统计分析,发现混合像元中地物类型越多,则二者相关性越小。最后,采用多元线性回归分析法,根据不同土地覆盖类型建立反演回归模型,对部分研究区域MODIS-LST进行反演,误差平均在±3.15 K以内,与不考虑下垫面覆盖的模型比较,反演MODIS_LST精度平均提高了1.5 K。  相似文献   

17.
黄河三角洲蒸散的遥感研究   总被引：16，自引：0，他引：16  
蒸散是水资源管理的一个重要参数。与传统的蒸散计算方法相比 ,利用遥感进行蒸散研究具有快速、准确、大区域尺度及地图可视化显示等特点。 SEBAL模型是一个应用遥感影像收集到的可见光波段、近红外和热红外波段信息对大区域范围进行蒸散计算的模型 ,它是基于地表能量平衡方程 ,通过计算地表净辐射通量 ,土壤热通量和显热通量 ,最后计算出用于蒸散的潜热通量 ,进而计算出遥感影像拍摄时的瞬时蒸散及当天的总蒸散量。本文利用 SEBAL模型采用 ETM+影像对黄河三角洲进行了遥感蒸散研究 ,并对黄河三角洲的蒸散特点进行了分析。蒸散研究对黄河三角洲水资源的合理利用有潜在的指导意义。  相似文献   

18.
土地覆被是地球科学研究中的重要参量,评价土地覆被数据的制图精度是保障数据合理使用的前提。本文提出了一种基于伪纯像元的精度评价策略（伪纯像元策略）,即当低空间分辨率栅格窗口内对应的高空间分辨率数据中优势类别（面积最大的地类）的占比高于伪纯像元纯度阈值（代表像元纯度,取值范围：35%~100%,步长为5%）时,以此栅格窗口为基准生成土地覆被类型为优势类别的伪纯像元用于精度评价。以澜沧江-湄公河（澜湄）流域为试验区,选择GlobeLand30为参考数据,并基于混淆矩阵精度评价方法对比分析了伪纯像元策略与重采样法（最近邻法和众数法）在CCI-LC（300 m）和MCD12Q1（500 m） 2套全球土地覆被数据精度评价中的差异。结果表明：① 伪纯像元策略在35%~100%纯度阈值下对CCI-LC和MCD12Q1在澜湄流域评价的精度分别为72.76%~55.26%和71.44%~45.41%,比重采样法评价的单一精度（众数法：71.21%和70.54%、最近邻法：71.48和69.87%）能更好地反映像元纯度对土地覆被数据精度的影响;② CCI-LC的总体精度高于MCD12Q1,且2套数据的精度差随纯度阈值的增大而增加,CCI-LC和MCD12Q1在35%、100%纯度阈值下的精度差分别为1.32%和9.85%;③ 2套数据中耕地、有林地、草地和水体的分类精度均相对较高,而灌木林地（精度接近0）和裸地的分类精度均较低;④ 2套数据与GlobeLand30的空间不一致区域多出现在土地覆被类型高度异质化的混合像元区域,且随纯度阈值的增大,评价样本栅格更趋均质,混合像元对评价精度的影响也会递减。伪纯像元精度评价策略适用于跨空间分辨率土地覆被数据的精度对比,为评价全球土地覆被产品在区域尺度的适用性及适用范围提供了新的检验策略。  相似文献   

19.
【Title】
There are knowledge gaps in our understanding of vegetation responses to multi-scale climate-related variables in tropical/subtropical mountainous islands in the Asia-Pacific region. Therefore, this study investigated inter-annual vegetation dynamics and regular/irregular climate patterns in Taiwan. We applied principal component analysis （PCA） on 11 years （2001~2011） of high-dimensional monthly photosynthetically active vegetation cover （PV） derived from the Moderate Resolution Imaging Spectroradiometer （MODIS） and investigated the relationships between spatiotemporal patterns of the eigenvectors and loadings of each component through time and multi-scale climate-related variations. Results showed that the first five components contributed to 96.4% of the total variance. The first component （PC1, explaining 94.5% of variance） loadings, as expected, were significantly correlated with the temporal dynamics of the PV （r = 0.94）, which was mainly governed by regional climate. The temporal loadings of PC2 and PC3 （0.8% and 0.6% of variance, respectively） were significantly correlated with the temporal dynamics of the PV of forests （r = 0.72） and the farmlands （r = 0.80）, respectively. The low-order components （PC4 and PC5, 0.3% and 0.2% of variance, respectively） were closely related to the occurrence of drought （r = 0.49） and to irregular ENSO associated climate anomalies （r = -0.54）, respectively. Pronounced correlations were also observed between PC5 and the Southern Oscillation Index （SOI） with one to three months of time lags （r = -0.35 ~ -0.43, respectively）, revealing biophysical memory effects on the time-series pattern of the vegetation through ENSO-related rainfall patterns. Our findings reveal that the sensitivity of the ecosystems in this tropical/subtropical mountainous island may not only be regulated by regional climate and human activities but also be susceptible to large-scale climate anomalies which are crucial and comparable to previous large scale analyses. This study demonstrates that PCA can be an effective tool for analyzing seasonal and inter-annual variability of vegetation dynamics across this tropical/subtropical mountainous islandin the Pacific Ocean, which provides an opportunity to forecast the responses and feedbacks of terrestrial environments to future climate scenarios.  相似文献   

20.
In this paper,a methodology for Leaf Area Index(LAI) estimating was proposed by assimilating remote sensed data into crop model based on temporal and spatial knowledge.Firstly,sensitive parameters of crop model were calibrated by Shuffled Complex Evolution method developed at the University of Arizona(SCE-UA) optimization method based on phenological information,which is called temporal knowledge.The calibrated crop model will be used as the forecast operator.Then,the Taylor′s mean value theorem was applied to extracting spatial information from the Moderate Resolution Imaging Spectroradiometer(MODIS) multi-scale data,which was used to calibrate the LAI inversion results by A two-layer Canopy Reflectance Model(ACRM) model.The calibrated LAI result was used as the observation operator.Finally,an Ensemble Kalman Filter(EnKF) was used to assimilate MODIS data into crop model.The results showed that the method could significantly improve the estimation accuracy of LAI and the simulated curves of LAI more conform to the crop growth situation closely comparing with MODIS LAI products.The root mean square error(RMSE) of LAI calculated by assimilation is 0.9185 which is reduced by 58.7% compared with that by simulation(0.3795),and before and after assimilation the mean error is reduced by 92.6% which is from 0.3563 to 0.0265.All these experiments indicated that the methodology proposed in this paper is reasonable and accurate for estimating crop LAI.  相似文献   

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