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1.
基于遥感和美国碳通量观测数据的GPP模型比较研究   总被引：1，自引：0，他引：1  
基于遥感和碳通量观测数据,本文采用VPM、EC-LUE、TG、GR、VI和MOD17六个模型估算了五种主要植被类型站点尺度的总初级生产力(GPP)。利用线性相关和定量分析方法评价并比较了上述模型在不同时间尺度上(8天、生长季和年际)的GPP模拟精度。结果表明:1)EC-LUE和VPM模型总体估算精度最高(R20.78);2)森林生态系统中,GPP估算值和实测值在季节和年累积总量上相对误差较小,而在草地和农田系统中,相对误差较大;3)GR、VI和TG模型在森林生态系统GPP估算中模拟精度较高,因其在形式上相对简单,需要的参数和输入数据相对较少,因而适用于大尺度的森林生态系统GPP估算。  相似文献   

2.
Accurate estimation of ecosystem carbon fluxes is crucial for understanding the feedbacks between the terrestrial biosphere and the atmosphere and for making climate-policy decisions. A statistical model is developed to estimate the gross primary production (GPP) of coniferous forests of northeastern USA using remotely sensed (RS) radiation (land surface temperature and near-infra red albedo) and ecosystem variables (enhanced vegetation index and global vegetation moisture index) acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. This GPP model (called R-GPP-Coni), based only on remotely sensed data, was first calibrated with GPP estimates derived from the eddy covariance flux tower of the Howland forest main tower site and then successfully transferred and validated at three other coniferous sites: the Howland forest west tower site, Duke pine forest and North Carolina loblolly pine site, which demonstrate its transferability to other coniferous ecoregions of northeastern USA. The proposed model captured the seasonal dynamics of the observed 8-day GPP successfully by explaining 84–94% of the observed variations with a root mean squared error (RMSE) ranging from 1.10 to 1.64 g C/m2/day over the 4 study sites and outperformed the primary RS-based GPP algorithm of MODIS.  相似文献   

3.
陆地总初级生产力遥感估算精度分析   总被引：1，自引：0，他引：1  
林尚荣  李静  柳钦火 《遥感学报》2018,22(2):234-252
准确估算陆地总初级生产力GPP(Gross Primary Productivity)数值对碳循环过程模拟有重要影响。本文介绍了多种基于植被指数以及基于光能利用率的遥感GPP算法,综述了不同算法在其研究区域的估算精度;并分析了MODIS/GPP以及BESS/GPP两种遥感GPP产品在不同植被类型的估算精度。通过对比全球碳通量站网络GPP数据表明,MODIS/GPP产品在全球估算结果具显著相关性(R2=0.59)及中等标准误差(RMSE=2.86 g C/m2/day),估算精度较高的植被类型有落叶阔叶林,草地等;估算精度较低类型包括常绿阔叶林,稀树草原等。本文对GPP产品中存在的不确定性进行分析,通过综述前人研究中发现的遥感估算GPP方法中存在的问题,指出可能的提高卫星遥感GPP产品估算精度的方法及发展趋势。  相似文献   

4.
黑河流域遥感物候产品验证与分析   总被引：2，自引：0，他引：2  
植被物候遥感产品对全球变化响应、农业生产管理、生态学的应用等多领域研究具有重要意义。但现有植被物候遥感产品还有较多问题,主要包括一方面使用不同参数的时间序列数据以及不同提取算法导致的产品结果差异较大,另一方面在地面验证中地面观测数据与遥感反演数据的物理含义不一致导致的验证方法的系统性误差。本文以黑河流域为研究区,对比验证基于EVI(Enhanced Vegetation Index)时间序列数据提取的MLCD(MODIS global land cover dynamics product)植被遥感物候产品和基于LAI(Leaf Area Index)时间序列数据提取的UMPM(product by universal multi-life-cycle phenology monitoring method)植被遥感物候产品的有效性及精度等。同时,通过验证分析进一步评估基于EVI和LAI时间序列提取的物候特征的差异及特点,探讨由于地面观测植被物候与遥感提取植被物候的物理意义的不一致问题导致的直接验证结果偏差。结果表明:UMPM产品有效性整体高于MLCD产品,但在以草地和灌木为主的稀疏植被区,由于LAI取值精度的原因,UMPM产品存在较多缺失数据,且时空稳定性较低;基于玉米地面观测数据表明,EVI对植被开始生长的信号比LAI更加敏感,更适合提取生长起点,但植被指数易饱和,峰值起点普遍提前,基于LAI提取的峰值起点更加合理。由于地面观测的物候期在后期更加关注果实生长,遥感观测仅关注叶片的生长,遥感定义的峰值终点和生长终点与玉米的乳熟期和成熟期差异较大。  相似文献   

5.
The vegetation index is derived using many remote sensing sensors. Vegetation Index is extensively used and remote sensing has become the primary data source. Number of vegetation indices (VIs) have been developed during the past decades in order to assess the state of vegetation qualitatively and quantitatively. Analysis of vegetation indices has been carried out by many investigators scaling from regional level to global level using the remote sensing data of varying spatial, temporal and radiometric resolutions. There are as many as 14 VIs in use. Globally operational algorithms for generation of NDVI have utilized digital counts, at sensor radiances, ‘normalized’ reflectance (top of the atmosphere), and more recently, partially atmospheric corrected (ozone absorption and molecular scattering) reflectance. Presently NDVI and EVI are standard MODIS data products which are widely used by the scientific community for environmental studies. The OCM sensor in Oceansat 2 is designed for ocean colour studies. The OCM sensor has been used for studying ocean phytoplankton, suspended sediments and aerosol optical depth by many investigators. In addition to its capability of studying the ocean surface, OCM sensor has also the potential to study the land surface features. In a past EVI has been retrieved using OCM sensor of Oceansat 1. However, there is slight change in the band width of Oceansat 2—OCM sensor compared with OCM of Oceansat 1 sensor. In the present paper an attempt has been made to derive EVI using Oceansat 2 OCM sensor and the results have been compared with MODIS data. The enhanced vegetation index (EVI) is calculated using the reflectance values obtained after removing molecular scattering and ozone absorption component from the total radiance detected by the sensor. The band-2, Band-3, band-6 and band-8 corresponding to Blue, Red and Infrared part of the visible spectrum have been used to determine EVI. The result shows that Oceansat 2 derived EVI and MODIS derived EVI are well correlated.  相似文献   

6.
Satellite-based remote sensed phenology has been widely used to assess global climate change. However, it is constrained by uncertain linkages with photosynthesis activity. Two dynamic threshold methods were employed to retrieve spring phenology metrics from four Moderate Resolution Imaging Spectroradiometer (MODIS) products, including fraction of Absorbed Photosynthetically Active Radiation (fAPAR), Leaf Area Index (LAI), Normalized Difference Vegetation Index (NDVI), and Enhanced Vegetation Index (EVI) for three temperate deciduous broadleaf forests in North America between 2001 and 2009. These MODIS-based spring phenology metrics were subsequently linked to the photosynthetic curves (daily gross primary productivity, GPP) measured by an eddy covariance flux tower. The 20% dynamic threshold spring onset metrics from MODIS products were closer to the photosynthesis onset metrics at the date of 2% GPP increase for NDVI and fAPAR, and closer to the date of 5% and 10% increase of GPP for EVI and LAI, respectively. The 50% dynamic threshold onset metrics were closer to the photosynthesis onset metrics at the date of 10% GPP increase for NDVI, and closer to the date of 20% GPP increase for fAPAR, LAI and EVI, respectively. These results can improve our knowledge on the photosynthesis activity status of remotely sensed spring phenology metrics.  相似文献   

7.
地表生物量对农作物估产、植被长势评估具有很重要的意义。随着遥感技术的发展与应用,遥感为生物量估算提供了一种新的手段。本文以唐山市为例,利用小麦种植区的MODIS遥感影像数据和同期野外调查获得的16组32个生物量数据,对比分析了归一化植被指数(NDVI)、增强型植被指数(EVI)与小麦生物量多个回归方程的相关系数,进而建立了NDVI、EVI与小麦生物量的线性回归模型。结果显示,使用MODIS数据的植被指数能够很好地对研究区地上生物量进行估算,其中使用EVI的三次函数模型拟合精度最高,并且对每组数据进行平均处理会使模型精度进一步提高。  相似文献   

8.
Gross primary production (GPP) is a parameter of significant importance for carbon cycle and climate change research. Remote sensing combined with other climate and meteorological data offers a convenient tool for large scale GPP estimation. This paper presents a study of GPP estimation using three methods with in situ measurements of canopy reflectance, LAI, and the photosynthetically active radiation (PAR). First, because LAI is considered as an indicator of the factor of absorbed PAR (fAPAR), it provides reasonable estimates of GPP for all types of wheat with coefficient of determination R2 of 0.7353. The second method uses four kinds of vegetation indices (VIs) to estimate GPP because these indices are suggested to be reliable candidates in the estimation of light use efficiency (LUE). Good determination coefficients were acquired in estimating GPP with R2 ranging from the lowest of 0.7604 for NDVI to the highest of 0.8505 for EVI. A new method was proposed for the estimation of GPP following the Monteith logic, which considering GPP as a product of VI × VI × PAR. Results indicated that this method can provide the best estimates of GPP as determination coefficient R2 increased largely compared to the other two methods. EVI × EVI × PAR was demonstrated to be the most suitable for the estimation of GPP with the highest R2 of 0.9207, which was about 10% larger as compared to GPP estimated from the single EVI. These results will be helpful for the development of new models of GPP estimation with all remote sensing inputs.  相似文献   

9.
The present study investigates the characteristics of CO2 exchange (photosynthesis and respiration) over agricultural site dominated by wheat crop and their relationship with ecosystem parameters derived from MODIS. Eddy covariance measurement of CO2 and H2O exchanges was carried out at 10 Hz interval and fluxes of CO2 were computed at half-hourly time steps. The net ecosystem exchange (NEE) was partitioned into gross primary productivity (GPP) and ecosystem respiration (R e) by taking difference between day-time NEE and respiration. Time-series of daily reflectance and surface temperature products at varying resolution (250–1000 m) were used to derive ecosystem variables (EVI, NDVI, LST). Diurnal pattern in Net ecosystem exchange reveals negative NEE during day-time representing CO2 uptake and positive during night as release of CO2. The amplitude of the diurnal variation in NEE increased as LAI crop growth advances and reached its peak around the anthesis stage. The mid-day uptake during this stage was around 1.15 mg CO2 m−2 s−1 and night-time release was around 0.15 mg CO2 m−2 s−1. Linear and non-linear least square regression procedures were employed to develop phenomenological models and empirical fits between flux tower based GPP and NEE with satellite derived variables and environmental parameters. Enhanced vegetation index was found significantly related to both GPP and NEE. However, NDVI showed little less significant relationship with both GPP and NEE. Furthemore, temperature-greenness (TG) model combining scaled EVI and LST was parameterized to estimate daily GPP over dominantly wheat crop site. (R 2 = 0.77). Multi-variate analysis shows that inclusion of LST or air temperature with EVI marginally improves variance explained in daily NEE and GPP.  相似文献   

10.

Background

A simulation model based on remote sensing data for spatial vegetation properties has been used to estimate ecosystem carbon fluxes across Yellowstone National Park (YNP). The CASA (Carnegie Ames Stanford Approach) model was applied at a regional scale to estimate seasonal and annual carbon fluxes as net primary production (NPP) and soil respiration components. Predicted net ecosystem production (NEP) flux of CO2 is estimated from the model for carbon sinks and sources over multi-year periods that varied in climate and (wildfire) disturbance histories. Monthly Enhanced Vegetation Index (EVI) image coverages from the NASA Moderate Resolution Imaging Spectroradiometer (MODIS) instrument (from 2000 to 2006) were direct inputs to the model. New map products have been added to CASA from airborne remote sensing of coarse woody debris (CWD) in areas burned by wildfires over the past two decades.

Results

Model results indicated that relatively cooler and wetter summer growing seasons were the most favorable for annual plant production and net ecosystem carbon gains in representative landscapes of YNP. When summed across vegetation class areas, the predominance of evergreen forest and shrubland (sagebrush) cover was evident, with these two classes together accounting for 88% of the total annual NPP flux of 2.5 Tg C yr-1 (1 Tg = 1012 g) for the entire Yellowstone study area from 2000-2006. Most vegetation classes were estimated as net ecosystem sinks of atmospheric CO2 on annual basis, making the entire study area a moderate net sink of about +0.13 Tg C yr-1. This average sink value for forested lands nonetheless masks the contribution of areas burned during the 1988 wildfires, which were estimated as net sources of CO2 to the atmosphere, totaling to a NEP flux of -0.04 Tg C yr-1 for the entire burned area. Several areas burned in the 1988 wildfires were estimated to be among the lowest in overall yearly NPP, namely the Hellroaring Fire, Mink Fire, and Falls Fire areas.

Conclusions

Rates of recovery for burned forest areas to pre-1988 biomass levels were estimated from a unique combination of remote sensing and CASA model predictions. Ecosystem production and carbon fluxes in the Greater Yellowstone Ecosystem (GYE) result from complex interactions between climate, forest age structure, and disturbance-recovery patterns of the landscape.  相似文献   

11.
通过对比分析MODIS数据的标准归一化差分植被指数、土壤调节植被指数及增强型植被指数的特点,最终选择标准归一化差分植被指数(NDVI)对工程区进行监测。并阐述了最大合成法合成MODIS植被指数是一种行之有效的方法。  相似文献   

12.
叶绿素荧光的GOSAT卫星遥感反演   总被引：1，自引：0，他引：1  
刘新杰  刘良云 《遥感学报》2013,17(6):1518-1532
由于大气吸收和散射等大气辐射传输影响,叶绿素荧光卫星遥感反演存在很大的困难和挑战。本文利用日本温室气体观测卫星GOSAT的TANSO-FTS超光谱数据,选取770 nm附近受大气影响较弱的KI夫琅和费暗线,借助KPNO2010高分辨率太阳辐照度光谱,设计了加权最小二乘拟合的叶绿素荧光卫星反演算法,利用矩阵的谱条件数确定了算法中KI吸收线所采用的权重系数,获得了中国区域2010年1月至2011年6月的叶绿素荧光数据。并利用TANSO-CAI云标识数据剔除了受云影响的反演结果,并按照2°×2°格网逐月计算了荧光强度均值。将反演叶绿素荧光强度结果与同期MODIS的增强性植被指数EVI、光合有效辐射比例FPAR、总初级生产力GPP产品作对比分析,结果表明：荧光强度高值主要分布在中国西南、中南等植被覆盖度高、生长旺盛的地区,荧光强度季节性变化规律与EVI、FPAR、GPP等相似,但季节变化比上述各参数变化提前且更敏感,可以反映其他参数所不具备的独特信息。  相似文献   

13.
同化MODIS温度产品估算地表水热通量   总被引：4，自引：0，他引：4       下载免费PDF全文
徐同仁  刘绍民  秦军  梁顺林 《遥感学报》2009,13(6):999-1019
基于集合卡尔曼滤波和通用陆面模型(CLM 1.0)发展了一个地表温度的同化系统。这个系统同化了MODIS温度产品, 并将MODIS的叶面积指数引入CLM模型中, 主要用于改进地表水热通量的估算精度。将CLM输出的地表温度与MODIS地表温度建立关系, 并作为同化系统的观测算子。将MODIS地表温度与实测地表温度进行了比较, 将其均方差(Root Mean Square Error, RMSE)作为观测误差。选取3个美国通量网站点(Blackhill、Bondville、Brookings)作为实验数据, 结果表明: 同化结果中地表温度、显热通量的估算精度均有提高。其中Blackhill站的估算精度改进最大, 均方差由81.5W·m-2减小到58.4W·m-2, Bondville站均方差由47.0W·m-2减小到31.8W·m-2, Brookings站均方差由46.5W·m-2减小到45.1W·m-2。潜热通量估算精度在Bondville站均方差由88.6W·m-2减小到57.7W·m-2, Blackhill站均方差由53.4W·m-2减小到47.2W·m-2。总之, 结合陆面过程模型同化MODIS温度产品估算地表水热通量是可行的。  相似文献   

14.
High-resolution evapotranspiration (ET) maps can assist demand-based irrigation management. Development of high-resolution daily ET maps requires high-resolution land surface temperature (LST) images. Earth-observing satellite sensors such as the Landsat 5 Thematic Mapper (TM) and MODerate resolution Imaging Spectroradiometer (MODIS) provide thermal images that are coarser than simultaneously acquired visible and near-infrared images. In this study, we evaluated the TsHARP downscaling technique for its capability to downscale coarser LST images using finer resolution normalized difference vegetation index (NDVI) data. The TsHARP technique was implemented to downscale seven coarser scale (240, 360, 480, 600, 720, 840, and 960 m) synthetic images to a 120 m LST image. The TsHARP was also evaluated for downscaling a coarser 960 m LST image to 240 m to mimic MODIS datasets. Comparison between observed 120 m LST images and 120 m LST images downscaled from coarser 240, 360, 480, 600, 720, 840, and 960 m images yielded root mean square errors of 1.0, 1.3, 1.5, 1.6, 1.7, 1.8, and 1.9°C, respectively. This indicates that the TsHARP method can be used for downscaling coarser (960 m) MODIS-based LST images using finer Landsat (120 m) or MODIS (240 m)-derived NDVI images. However, the TsSHARP method should be evaluated further with real datasets before using it for an operational ET remote sensing program for irrigation scheduling purposes.  相似文献   

15.
估算森林地上生物量(AGB)对于全球实现碳中和目标至关重要。本文以美国缅因州Howland森林为研究区域,借助地面实测样地数据,对比分析协同不同数据源(高光谱和LiDAR)和机器学习算法(随机森林、支持向量机、梯度提升决策树和K最邻近回归)的研究,以改善Howland森林的生物量估计精度。结果表明,采用LiDAR和高光谱植被指数变量模型的最佳精度分别为0.874和0.868,协同高光谱和LiDAR变量并采用梯度提升决策树回归模型的精度为0.927,即多源遥感数据要优于单一数据源。高光谱和LiDAR数据的协同使用对于提高类似于Howland地区或更广泛区域的生物量估计的准确性,具有普遍的适用性与一定的应用前景。  相似文献   

16.
Southwestern China experienced a period of severe drought from September 2009 to May 2010. It led to widespread decline in the enhanced vegetation index (EVI) and gross primary productivity (GPP) in the springtime of 2010 (March to May). However, this study observed a spatial inconsistency between drought-impacted vegetation decline and the precipitation deficit. Significant aerosol loads that correspond to inconsistent areas were also observed during the drought period. After analyzing both MODIS GPP/NPP Collection 5 (C5) and the newer Collection 5.5 (C55) data, a large area observed to be experiencing GPP decline in the eastern part of the study area proved to be unreliable. Based on EVI data, after atmospherically contaminated data were screened from analysis, approximately 20% of the study area exhibited browning whereas 33% displayed no change or greening and the remaining area (approximately 47%) lacked sufficient data to document changing conditions. Correlation analysis showed that fire occurrences, aerosol optical depth, and precipitation anomalies during the two drought periods (from September to February and from March to May) all contributed to a decrease in GPP. C55 data remains vulnerable to aerosol contamination due to a much higher correlation coefficient with aerosol optical depth compared to C5 data. In the future, users of remotely sensed data should be cautious of and take into account impacts related to atmospheric contamination, even during drought periods.  相似文献   

17.
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18.
A new approach to estimate soil moisture (SM) based on evaporative fraction (EF) retrieved from optical/thermal infrared MODIS data is presented for Canadian Prairies in parts of Saskatchewan and Alberta. An EF model using the remotely sensed land surface temperature (Ts)/vegetation index concept was modified by incorporating North American Regional Reanalysis (NAAR) Ta data and used for SM estimation. Two different combinations of temperature and vegetation fraction using the difference between Ts from MODIS Aqua and Terra images and Ta from NARR data (Ts−Ta Aqua-day and Ts−Ta Terra-day, respectively) were proposed and the results were compared with those obtained from a previously improved model (ΔTs Aqua-DayNight) as a reference. For the estimation of SM from EF, two empirical models were tested and discussed to find the most appropriate model for converting MODIS-derived EF data to SM values. Estimated SM values were then correlated with in situ SM measurements and their relationships were statistically analyzed. Results indicated statistically significant correlations between SM estimated from all three EF estimation approaches and field measured SM values (R2 = 0.42–0.77, p values < 0.04) exhibiting the possibility to estimate SM from remotely sensed EF models. The proposed Ts−Ta MODIS Aqua-day and Terra-day approaches resulted in better estimations of SM (on average higher R2 values and similar RMSEs) as compared with the ΔTs reference approach indicating that the concept of incorporating NARR Ta data into Ts/Vegetation index model improved soil moisture estimation accuracy based on evaporative fraction. The accuracies of the predictions were found to be considerably better for intermediate SM values (from 12 to 22 vol/vol%) with square errors averaging below 11 (vol/vol%)2. This indicates that the model needs further improvements to account for extreme soil moisture conditions. The findings of this research can be potentially used to downscale SM estimations obtained from passive microwave remote sensing techniques.  相似文献   

19.
Wetlands are one of the most important sources of atmospheric methane (CH4) contributing about 22% to the global methane budget. But to improve estimates of CH4 emission at regional and global scales there is a need to observe the sources such as wetlands frequently and develop process-based models. In this regard, wetland inventory using satellite remote sensing data has conventionally been carried out by analysis of optical data. Due to thermal inertia differences emittive thermal channels data has shown promise to provide highly critical information about wetlands such as water spread, aquatic vegetation and mud flats etc. Thermal channels data of MODIS (Moderate Resolution Imaging Spectroradiometer) sensor with a spatial resolution of 1km and swath of 2330 km is emerging as the key source of remote sensing data for global/ regional wetland estimation and assessment of green house gas emission. In the present study MODIS thermal channels (31 and 32) and optical channels (1,2, and 3) data have been used for evaluating methane emission from wetlands in Gujarat. An empirical model based on temperature and productivity has been used to investigate the response of methane emission from different sources. Model has the potential to estimate country level methane emission based on satellite remote sensing in conjunction with collateral data/information. In this study. MODIS data of two dates pertaining to Gujarat have been analyzed and results compared with respect to methane emission.  相似文献   

20.
针对遥感影像在南方丘陵地区典型植被丰度信息提取中存在的大量混合像元问题，为进一步提高线性解混精度，通过计算像元EVI值，构建了Landsat 8时间序列影像南方典型植被（端元）和混合像元的EVI时间序列曲线，分析了不同生育期内各种地物类型的植被指数变化曲线，发现不同地物在植被指数时间序列中具有各自独立的波动规律。选取多个端元及其EVI时间序列曲线，利用光谱匹配方法对匹配EVI时间序列曲线和多个端元进行了匹配，达到利用不同端元组合进行光谱解混的目的。试验结果表明，与传统方法相比，阔叶林解混精度有明显提高，针叶林解混精度也有所提高。该研究成果可以为南方丘陵地区植被环境的研究提供有力支撑。  相似文献   

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