Estimation of absorbed PAR across Scandinavia from satellite measurements: Part I: Incident PAR

The primary productivity of a plant community can be modeled as the product of the amount of photosynthetically active radiation (PAR) absorbed by the canopy and a light use efficiency factor, where the amount of absorbed PAR (APAR) is the product of the fractional absorption and the amount of incident PAR. By implementing a method, PARcalc, using atmospheric data from the Moderate Resolution Imaging Spectroradiometer (MODIS), incident PAR is estimated in this study. In addition, since many PAR datasets are generated by converting shortwave radiation into PAR, the ratio of PAR to shortwave radiation was also investigated. PARcalc models the photosynthetic photon flux density (PPFD) as a product of atmospheric transmittance, the cosine of the Sun zenith angle, and the solar constant. The atmospheric transmittance includes the attenuation of radiation by Rayleigh and aerosol scattering, and absorption by water and ozone. A cloud transmittance factor which is primarily a function of the cloud optical thickness is added in order to cope with cloudy conditions. The model was implemented at two sites in Sweden, Asa and Norunda, where in situ measurements of PPFD were made during the spring and summer of 2004. Modeled time-series were evaluated against the measurements, and daily sums of PPFD were calculated by fitting of a sine function in combination with linear interpolation of the instantaneous estimates from sunrise to sunset. This gave correlation coefficients at Norunda and Asa of 0.80 and 0.77, respectively, when comparing modeled and measured daily insolation. The average relative errors were 24% and 25%. Corresponding figures for five day averages were 0.91 and 0.86; and 9.3% and 11.9%. Instantaneous estimates of PPFD were modeled with correlation coefficients of 0 88-0 93 and average relative errors from 17.0%. These numbers were acquired when using measured values for determining cloudiness; the corresponding figures when the method is fully implemented using satellite data are 0.84 to 0.71 and 24.9%, respectively. The ratio of PAR to shortwave radiation was measured at Norunda 1 Jan to 31 Oct 2004 and was found to vary between 0.27 and 0.48 on a daily basis with an average of 0.43 for the whole period.     

Influence of land surface effects on MODIS aerosol retrieval using the BAER method over Korea

As satellite receiving signals are affected by complex radiative transfer processes in the atmosphere and on land surfaces, aerosol retrieval over land from space requires the ability to determine surface reflectance from the remote measurements. To use the Bremen Aerosol Retrieval (BAER) method for aerosol optical thickness (AOT) retrieval over land at a spatial scale of 1×1 km² from Moderate Resolution Imaging Spectroradiometer (MODIS) data, a linear mixing model with a vegetation index was used to calculate surface reflectances. As the vegetation index is affected by the aerosol present in the atmosphere, an empirical linear relationship between short wavelength infrared (SWIR) channel reflectance and visible reflectance was estimated to calculate a modified aerosol free vegetation index (AFRI) value. Based on a modified AFRI obtained from MODIS SWIR channel reflectance, an improved linear mixing model was applied for aerosol retrieval. A comparison of results between calculated and apparent surface reflectance was satisfactory, with a linear fit slope above 0.94, correlation coefficients above 0.84, and standard deviation below 0.008 for the study area. These results can therefore be used for improved aerosol retrieval over land by the BAER method with MODIS Level 1 data.     

中国东南地区及近海海域气溶胶反演遥感研究

大气气溶胶在很多生物地球化学循环中具有重要作用,但是由于它的来源广泛并且具有很大的时空变化性,难以在全球范围内精确、实时确定气溶胶的性质、组成及时空分布,因而对大气气溶胶的研究依赖于监测手段的发展。地基试验能获取点源的大气气溶胶光学厚度(AOD)的地面测量数据,得到的气溶胶光学厚度用于卫星数据的预处理以及气溶胶光学厚度反演的精度验证。而经过地基校验后的卫星遥感数据,可以反映大范围内实时动态的气溶胶信息。利用MODIS资料和地基探测的太阳光度计资料,对中国东南地区及近海海域的大气气溶胶光学特性进行了分析,讨论了适用于中国东南地区的大气气溶胶模型;利用连续的太阳光度计数据对MODIS资料的反演结果进行校验,结果表明：改进气溶胶模型和采用连续波段太阳光度计探测数据,可以提高MODIS AOD的校验结果。     

Mapping PAR using MODIS atmosphere products

Instantaneous PAR (Photosynthetically Active Radiation), computed from atmospheric parameters from individual images from the MODIS sensors aboard the Terra and Aqua satellite platforms, is combined to derive daily integrated PAR and mapped to a local coordinate system. Compared to field observations, the daily integrated PAR values were shown to have average errors in the order of 5-8%, with individual estimation errors as high as 21%, but monthly averages showed much better correspondence with observations yielding averaged absolute errors of around 5%. The error appears to be mostly related to uncertainties in the MODIS aerosol retrieval accuracy. This accuracy and the medium spatial resolution of the PAR map compare very favourably to other sources of PAR data and make this a useful product in the improved assessment of vegetation dynamics.     

Mapping incident photosynthetically active radiation from MODIS data over China

Photosynthetically active radiation (PAR) is a key input parameter for almost all terrestrial ecosystem models, but the spatial resolution of current PAR products is too coarse to satisfy regional application requirements. In this paper, we present an operational system for PAR retrieval from MODIS data that is based on an idea proposed by [Liang, S., Zheng, T., Liu, R., Fang, H., Tsay, S. -C., & Running, S. (2006). Estimation of incident photosynthetically active radiation from Moderate Resolution Imaging Spectrometer data. Journal of Geophysical Research, 111, D15208. doi:10.1029/2005JD006730]. However, the operational system for PAR retrieval described here contains several improvements. The algorithm utilizes MODIS 1B data combining MODIS land surface products and BRDF model parameters products to directly estimate diffuse PAR, direct PAR and total PAR. Times-series data interpolation removes the noise and cloud contamination of land surface reflectance. PAR is retrieved by searching look-up tables calculated using a radiative transfer model. The system can automatically process MODIS 1B data to generate instantaneous and daily PAR. The instantaneous PAR products are compared with observational data from seven ChinaFLUX stations, and daily total PAR estimates are compared with those estimates of global radiation from 98 meteorological stations over China. The results indicate that this approach can produce reasonable PAR estimates, although this method overestimates PAR for low values of PAR.     

Effects of implementing satellite observed aerosols into a mesoscale atmosphere model

This study investigated the performance of the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU-NCAR) Mesoscale Model (MM5) in calculating the aerosol forcing on cloud cover, incoming surface solar radiation, and near-surface air temperature via the implementation of aerosol optical depth in the shortwave radiation parameterization. MM5 simulations with and without aerosol data are performed in the periods of 6–7 August 2003 and 19–21 September 2003 during which strong aerosol forcing was observed with Moderate Resolution Imaging Spectroradiometer (MODIS) data in the mid-Atlantic region. Both periods clearly showed that aerosols had a direct negative effect on surface solar radiation through aerosol scattering. For example, every 0.1 change in MODIS aerosol optical thickness (AOT) results in 44 and 59?W?m^?2 decreases in surface solar radiation for the first and second periods, respectively. A magnitude of 0.1 increment in MODIS AOT reduces air temperature 0.36 and 0.56?K for the first and second periods, respectively. Comparisons with satellite-derived surface solar radiation retrievals showed that aerosol implementation in MM5 consistently showed better incoming surface solar radiation than that of the non-aerosol case. This helps to reduce uncertainties related to the radiation–cloud–aerosol interaction in numerical weather modelling systems.     

针对MODIS 数据的地表温度非线性迭代反演方法

地表温度是气象、水文、生态等研究领域中的一个重要参数。构建了MODIS31/ 32 波段的热辐射传输方程, 讨论了方程的数值迭代解法, 提出了针对MODIS 数据地表温度的非线性迭代反演方法, 并介绍了大气透过率和地表比辐射率这两个中间参数的估计方法。误差及敏感性分析表明,提出的方法对大气透过率和地表比辐射率都不敏感, 反演精度优于传统的线性分裂窗算法。     

Landsat8卫星影像大气校正及其植被指数与SEVI性能比较

遥感影像受大气的吸收散射以及地形起伏变化的影响，使得传感器接收到的辐射信号既包含了地物的信息，同时也包含了大气以及地形的信息。为了提高地表反射率的反演精度，需要去除遥感影像中大气和地形的影响。提出了一种基于查找表的Landsat8-OLI遥感影像的大气校正方法，该方法由6S辐射传输模型生成查找表，其中输入的参数包括大气水蒸汽含量、臭氧浓度和气溶胶光学厚度等MODIS大气参数产品。利用传统方法建立的大气参数查找表通常只考虑一部分因素，这对于以MODIS产品为输入参数的大气校正是不适用的。本文建立了一个包括大部分输入参数的高维大气校正查找表，对于Landsat-8 OLI传感器具有很高的通用性，通过进行光谱分析、与USGS地表反射率产品交叉验证等方式来验证模型的精度。验证结果表明该方法能有效地反演精确可靠的地表反射率。最后，采用目视解译、统计分析将校正结果与SEVI做对比分析，比较地形影响消减的效果。结果表明该模型与SEVI在地形消减的效果上作用相当。     

Landsat8卫星影像大气校正及其植被指数与SEVI性能比较

遥感影像受大气的吸收散射以及地形起伏变化的影响,使得传感器接收到的辐射信号既包含了地物的信息,同时也包含了大气以及地形的信息。为了提高地表反射率的反演精度,需要去除遥感影像中大气和地形的影响。提出了一种基于查找表的Landsat8-OLI遥感影像的大气校正方法,该方法由6S辐射传输模型生成查找表,其中输入的参数包括大气水蒸汽含量、臭氧浓度和气溶胶光学厚度等MODIS大气参数产品。利用传统方法建立的大气参数查找表通常只考虑一部分因素,这对于以MODIS产品为输入参数的大气校正是不适用的。本文建立了一个包括大部分输入参数的高维大气校正查找表,对于Landsat-8 OLI传感器具有很高的通用性,通过进行光谱分析、与USGS地表反射率产品交叉验证等方式来验证模型的精度。验证结果表明该方法能有效地反演精确可靠的地表反射率。最后,采用目视解译、统计分析将校正结果与SEVI做对比分析,比较地形影响消减的效果。结果表明该模型与SEVI在地形消减的效果上作用相当。     

Assessing the coupling between surface albedo derived from MODIS and the fraction of diffuse skylight over spatially-characterized landscapes

In this effort, the MODerate Resolution Imaging Spectroradiometer (MODIS) (Collection V005) Bidirectional Reflectance Distribution Function (BRDF)/Albedo algorithm is used to retrieve instantaneous surface albedo at a point in time and under specific atmospheric conditions. These retrievals are then used to study the role that the fraction of diffuse skylight plays under realistic scenarios of anisotropic diffuse illumination and multiple scattering between the surface and atmosphere. Simulations of the sky radiance using the MODTRAN®5.1 radiative transfer model were performed under different aerosol optical properties, illumination conditions, and surface characteristics to describe these effects on surface albedo retrievals from MODIS. This technique was examined using a validation scheme over four measurement sites with varied aerosol levels and landscapes, ranging from croplands to tundra ecosystems, and over extended time periods. Furthermore, a series of geostatistical analyses were performed to examine the types of spatial patterns observed at each measurement site. In particular, Enhanced Thematic Mapper Plus (ETM+) retrievals of surface albedo were acquired to analyze the change in variogram model parameters as a function of increased window-size. Results were then used to assess the degree to which a given point measurement is able to capture the intrinsic variability at the scale of MODIS observations. Assessments of MODIS instantaneous albedos that account for anisotropic multiple scattering, over snow-free and snow-covered lands and at all diurnal solar zenith angles, show a slight improvement over the albedo formulations that treat the downwelling diffuse radiation as isotropic. Comparisons with field measurements show biases improving by 0.004-0.013 absolute units (root-mean-squared error) or 0.1%-2.0% relative error.     

A new method for improving the retrieved aerosol fine-mode fraction from MODIS over ocean

A new method for improving the retrieved aerosol fine-mode fraction (₅₅₀) based on the current Moderate Resolution Imaging Spectroradiometer (MODIS) ocean algorithm is proposed. In the current MODIS ocean algorithm, the top of the atmosphere (TOA) apparent reflectance needs calculation from lookup tables (LUTs). The weighting parameters used in the calculation show an obvious spectral dependence, which is not taken into account in the current algorithm. The main measure taken in this study is to consider the spectral dependence of the weighting parameters. The MODIS aerosol products and the Aerosol Robotic Network (AERONET) data of Hong Kong Hok Tsui, Midway Island, Martha’s Vineyard Coastal Observatory (MVCO) and COVE, Virginia, where aerosols exhibit different loading and size distribution, are used to test the new method. The results show that the new method improves the retrieved fine-mode fraction, which is underestimated in anthropogenic-dominated aerosol conditions and overestimated in the sea salt-dominated aerosol conditions by the current algorithm. The correlation of the retrieved fine-mode fraction between the new method and AERONET is much higher (correlation coefficient, r?=?0.92) than that between the current MODIS and AERONET (r?=?0.80). The retrieved aerosol optical depth (AOD) is also improved. More AODs retrieved from the new method lie within the expected error bars.     

Estimation of absorbed PAR across Scandinavia from satellite measurements. Part II: Modeling and evaluating the fractional absorption

The aim of this study is to generate a quality-controlled sub-kilometer dataset of the fraction of absorbed photosynthetically active radiation (FAPAR) across Scandinavia from satellite. FAPAR is required for estimating the amount of PAR absorbed (APAR) by vegetation, which in turn allows for estimation of carbon uptake. In this study, FAPAR was modeled from normalized difference vegetation index (NDVI) which was obtained from the MODIS VI product (MOD13Q1) at 250 m spatial resolution. Modeled FAPAR was evaluated against in-situ measurements of fractional interception of PAR (FIPAR) and FAPAR at nine plots in six forested sites across Sweden and Denmark from 2001 to 2005. High resolution remote sensing data were used to investigate the representativeness of the measurement areas. Furthermore, FAPAR from the MODIS LAI/FPAR product at 1 km spatial resolution (MOD15A2) was investigated and compared the measured and modeled FAPAR. There was good agreement between modeled and measured FAPAR (6.9% average RMSE of the means). A linear relationship between daily values of NDVI and FAPAR was found (R² = 0.82), and it is concluded that seasonally adjusted NDVI can be used for accurate FAPAR estimations over forested areas in Scandinavia. However, it was found that the error was correlated with average FAPAR and that it is important to take the understory vegetation into account when measuring FAPAR in open canopies. The observed difference between FIPAR and FAPAR was 2.3 and 1.4 percentage units for coniferous and deciduous stands, respectively. MODIS FAPAR performed well although a few unrealistic values were present, highlighting the necessity to filter out low quality values using the quality-control datasets.     

Aerosol optical thickness determination by exploiting the synergy of TERRA and AQUA MODIS

Aerosol retrieval over land remains a difficult task because the solar light reflected by the Earth-atmospheric system mainly comes from the ground surface. The dark dense vegetation (DDV) algorithm for MODIS data has shown excellent competence at retrieving the aerosol distribution and properties. However, this algorithm is restricted to lower surface reflectance, such as water bodies and dense vegetation. In this paper, we attempt to derive aerosol optical thickness (AOT) by exploiting the synergy of TERRA and AQUA MODIS data (SYNTAM), which can be used for various ground surfaces, including for high-reflective surface. Preliminary validation results by comparing with Aerosol Robotic Network (AERONET) data show good accuracy and promising potential.     

基于MODIS数据的典型能见度条件下大气透过率计算

现有的辐射传输模型仅考虑气溶胶影响下的大气透过率，在能见度低于5km时，会给大气透过率计算带来较大的误差。本文综合考虑影响大气透过率的气溶胶和水汽因素，并利用中光谱分辨率MODIS（moderate resolution imaging spectmradiometer）数据，在特征参数的空间及时间尺度变化均比较大时，对大气透过率进行了定量反演，并进一步建立了整层大气透过率与行星反照率的关系模型，为近地层大气能见度的遥感监测提供了方法。     

Downscaling real-time vegetation dynamics by fusing multi-temporal MODIS and Landsat NDVI in topographically complex terrain

Canopy phenology is an important factor driving seasonal patterns of water and carbon exchange between land surface and atmosphere. Recent developments of real-time global satellite products (e.g., MODIS) provide the potential to assimilate dynamic canopy measurements with spatially distributed process-based ecohydrological models. However, global satellite products usually are provided with relatively coarse spatial resolutions, averaging out important spatial heterogeneity of both terrain and vegetation. Therefore, bias can result from lumped representation of ecological and hydrological processes especially in topographically complex terrain. Successful downscaling of canopy phenology to high spatial resolution would be indispensable for catchment-scale distributed ecohydrological modeling, aiming at understanding complex patterns of water, carbon and nutrient cycling in mountainous watersheds. Two downscaling approaches are developed in this study to overcome this issue by fusing multi-temporal MODIS and Landsat TM data in conjunction with topographic information to estimate high spatio-temporal resolution biophysical parameters over complex terrain. MODIS FPAR (fraction of absorbed photosynthetically active radiation) is used to provide medium spatial resolution phenology, while the variability of vegetation within a MODIS pixel is characterized by Landsat NDVI. The algorithms depend on the scale-invariant linear relationship between FPAR and NDVI, which is verified in this study. Downscaled vegetation dynamics are successfully validated both temporally and spatially with ground-based continuous FPAR and leaf area index measurements. Topographic correction during the downscaling process has a limited effect on downscaled FPAR products except for the period around the winter solstice in the study area.     

Assessment of MODIS sun-sensor geometry variations effect on observed NDVI using MSG SEVIRI geostationary data

The quality of Earth observation (EO) based vegetation monitoring has improved during recent years, which can be attributed to the enhanced sensor design of new satellites such as MODIS (Moderate Resolution Imaging Spectroradiometer) on Terra and Aqua. It is however expected that sun-sensor geometry variations will have a more visible impact on the Normalized Difference Vegetation Index (NDVI) from MODIS compared to earlier data sources, since noise related to atmosphere and sensor calibration is substantially reduced in the MODIS data stream. For this reason, the effect of varying MODIS viewing geometry on red, near-infrared (NIR) and NDVI needs to be quantified. Data from the geostationary MSG (Meteosat Second Generation) SEVIRI (Spinning Enhanced Visible and Infrared Imager) sensor is well suited for this purpose due to the fixed position of the sensor, the spectral resolution, including a red and NIR band, and the high temporal resolution (15 min) of data, enabling MSG data to be used as a reference for estimating MODIS surface reflectance and NDVI variations caused by varying sun-sensor geometry. The study was performed on data covering West Africa for periods of lowest possible cloud cover for three consecutive years (2004–2006). An analysis covering the entire range of NDVI revealed day-to-day variations in observed MODIS NDVI of 50–60% for medium dense vegetation (NDVI ≈ 0.5) caused by variations in MODIS view zenith angles (VZAs) between nadir and the high forward-scatter view direction. Statistical analysis on red, NIR and NDVI from MODIS and MSG SEVIRI for three transects (characterized by different vegetation densities) showed that both MODIS red and NIR reflectances are highly dependant on MODIS VZA and relative azimuth angle (RAA), due to the anisotropic behaviour of red and NIR reflectances. The anisotropic reflectance in the red and NIR band was to some degree minimized by the ratioing properties of NDVI. The minimization by the NDVI normalization is very dependent on the vegetation density however, since the degree of anisotropy in red and NIR reflectances depends on the amount of vegetation present. MODIS VZA and RAA effects on NDVI were highest for medium dense vegetation (NDVI ≈ 0.5–0.6). The VZA and RAA effects were less for sparsely vegetated areas (NDVI ≈ 0.3–0.35) and the smallest effect on NDVI was found for dense vegetation (NDVI ≈ 0.7). These results have implications for the end users' interpretation of NDVI, and challenge the expediency of the MODIS NDVI compositing technique, which should be refined to distinguish between forward- and backward-scatter viewing direction by taking RAA into account.     

Monitoring intense dust storms over the Indian region using satellite data – a case study

Dust storms are normally considered to be natural hazards. During such events, dust aerosol is loaded into the atmosphere, directly reducing visibility and effectively reflecting solar radiation back to space. In the present study, an intense dust storm was monitored during the first week of June 2010 using Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua data over the Indian region. A dust cloud was detected using a combination of MODIS reflective and emissive channels and moving trace/spread monitored by its multi-temporal data. The MODIS Terra-derived aerosol optical depth at 550 nm (AOD₅₅₀) and the aerosol index (AI) obtained from the Ozone Monitoring Instrument (OMI) were used in conjunction with National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis wind fields for the monitoring of dust clouds. The study reveals that the movement of a high concentration of dust clouds coincided with the NCEP/NCAR reanalysis meridional and zonal wind fields (>8 m s^?1) at pressure levels of 700 hPa. The Cloud–Aerosol Lidar Pathfinder Satellite Observations (CALIPSOs) that derive vertical feature mask images also suggested that the vertical extent of the dust aerosol layer was at a height of about 6 km over northern India on 2 June 2010. The roles of long-range transport of dust over the entire Gangetic plane are analysed using back trajectories from the National Oceanic and Atmospheric Administration (NOAA) Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model. Back trajectory analysis suggests that dust clouds moving over long distances entered from the western side of India on 1 June 2010.     

Modeling gross primary production of temperate deciduous broadleaf forest using satellite images and climate data

Net ecosystem exchange (NEE) of CO₂ between the atmosphere and forest ecosystems is determined by gross primary production (GPP) of vegetation and ecosystem respiration. CO₂ flux measurements at individual CO₂ eddy flux sites provide valuable information on the seasonal dynamics of GPP. In this paper, we developed and validated the satellite-based Vegetation Photosynthesis Model (VPM), using site-specific CO₂ flux and climate data from a temperate deciduous broadleaf forest at Harvard Forest, Massachusetts, USA. The VPM model is built upon the conceptual partitioning of photosynthetically active vegetation and non-photosynthetic vegetation (NPV) within the leaf and canopy. It estimates GPP, using satellite-derived Enhanced Vegetation Index (EVI), Land Surface Water Index (LSWI), air temperature and photosynthetically active radiation (PAR). Multi-year (1998-2001) data analyses have shown that EVI had a stronger linear relationship with GPP than did the Normalized Difference Vegetation Index (NDVI). Two simulations of the VPM model were conducted, using vegetation indices from the VEGETATION (VGT) sensor onboard the SPOT-4 satellite and the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard the Terra satellite. The predicted GPP values agreed reasonably well with observed GPP of the deciduous broadleaf forest at Harvard Forest, Massachusetts. This study highlighted the biophysical performance of improved vegetation indices in relation to GPP and demonstrated the potential of the VPM model for scaling-up of GPP of deciduous broadleaf forests.     

Exploring the potential of MODIS EVI for modeling gross primary production across African ecosystems

One of the most frequently applied methods for integrating controls on primary production through satellite data is the light use efficiency (LUE) approach, which links vegetation gross or net primary productivity (GPP or NPP) to remotely sensed estimates of absorbed photosynthetically active radiation (APAR). Eddy covariance towers provide continuous measurements of carbon flux, presenting an opportunity for evaluation of satellite estimates of GPP. Here we investigate relationships between eddy covariance estimated GPP, environmental variables derived from flux towers, Moderate Resolution Imaging Spectroradiometer (MODIS) enhanced vegetation index (EVI) and GPP across African savanna ecosystems. MODIS GPP was found to underestimate GPP at the majority of sites, particularly at sites in the Sahel. EVI was found to correlate well with estimated GPP on a site-by-site basis. Combining EVI with tower-measured PAR and evaporative fraction (EF, a measure of water sufficiency) improved the direct relationship between GPP and EVI at the majority of the sites. The slope of this relationship was strongly related to site peak leaf area index (LAI). These results are promising for the extension of GPP through the use of remote sensing data to a regional or even continental scale.     

Characterization of seasonal variation of forest canopy in a temperate deciduous broadleaf forest, using daily MODIS data

In this paper, we present an improved procedure for collecting no or little atmosphere- and snow-contaminated observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. The resultant time series of daily MODIS data of a temperate deciduous broadleaf forest (the Bartlett Experimental Forest) in 2004 show strong seasonal dynamics of surface reflectance of green, near infrared and shortwave infrared bands, and clearly delineate leaf phenology and length of plant growing season. We also estimate the fractions of photosynthetically active radiation (PAR) absorbed by vegetation canopy (FAPAR_canopy), leaf (FAPAR_leaf), and chlorophyll (FAPAR_chl), respectively, using a coupled leaf-canopy radiative transfer model (PROSAIL-2) and daily MODIS data. The Markov Chain Monte Carlo (MCMC) method (the Metropolis algorithm) is used for model inversion, which provides probability distributions of the retrieved variables. A two-step procedure is used to estimate the fractions of absorbed PAR: (1) to retrieve biophysical and biochemical variables from MODIS images using the PROSAIL-2 model; and (2) to calculate the fractions with the estimated model variables from the first step. Inversion and forward simulations of the PROSAIL-2 model are carried out for the temperate deciduous broadleaf forest during day of year (DOY) 184 to 201 in 2005. The reproduced reflectance values from the PROSAIL-2 model agree well with the observed MODIS reflectance for the five spectral bands (green, red, NIR₁, NIR₂, and SWIR₁). The estimated leaf area index, leaf dry matter, leaf chlorophyll content and FAPAR_canopy values are close to field measurements at the site. The results also showed significant differences between FAPAR_canopy and FAPAR_chl at the site. Our results show that MODIS imagery provides important information on biophysical and biochemical variables at both leaf and canopy levels.