Modelling surface energy fluxes over maize using a two-source patch model and radiometric soil and canopy temperature observations

Models estimating surface energy fluxes over partial canopy cover with thermal remote sensing must account for significant differences between the radiometric temperatures and turbulent exchange rates associated with the soil and canopy components of the thermal pixel scene. Recent progress in separating soil and canopy temperatures from dual angle composite radiometric temperature measurements has encouraged the development of two-source (soil and canopy) approaches to estimating surface energy fluxes given observations of component soil and canopy temperatures. A Simplified Two-Source Energy Balance (STSEB) model has been developed using a “patch” treatment of the surface flux sources, which does not allow interaction between the soil and vegetation canopy components. A simple algorithm to predict the net radiation partitioning between the soil and vegetation is introduced as part of the STSEB patch modelling scheme. The feasibility of the STSEB approach under a full range in fractional vegetation cover conditions is explored using data collected over a maize (corn) crop in Beltsville Maryland, USA during the 2004 summer growing season. Measurements of soil and canopy component temperatures as well as the effective composite temperature were collected over the course of the growing season from crop emergence to cob development. Comparison with tower flux measurements yielded root-mean-square-difference values between 15 and 50 W m^− 2 for the retrieval of the net radiation, soil, sensible and latent heat fluxes. A detailed sensitivity analysis of the STSEB approach to typical uncertainties in the required inputs was also conducted indicating greatest model sensitivity to soil and canopy temperature uncertainties with relative errors reaching ∼ 30% in latent heat flux estimates. With algorithms proposed to infer component temperatures from bi-angular satellite observations, the STSEB model has the capability of being applied operationally.     

基于TSEB平行模型的黄土丘陵沟壑区蒸散发遥感估算

复杂地形条件下和干旱半干旱植被稀疏条件下的蒸散发遥感估算一直是蒸散发区域遥感估算的难点、热点问题。针对黄土丘陵沟壑区地表起伏、覆被不均一、植被稀疏的特征,选择陕甘交界区为研究区,利用Landsat TM资料求取地表特征参数和地表能量平衡各参量,采用TSEB平行模型反演出该区域的瞬时土壤蒸发、植被蒸腾和土壤-植被总蒸散发量,经过尺度转换,得到日蒸散量;并利用附加阻抗法和FAO Penman-Monteith公式计算实际蒸散发,对TSEB平行模型法遥感估算结果进行了间接精度评价,比较验证结果表明TSEB平行模型法估算的蒸散发结果合理,精高较高。     

A thermal-based remote sensing technique for routine mapping of land-surface carbon,water and energy fluxes from field to regional scales

Robust yet simple remote sensing methodologies for mapping instantaneous land-surface fluxes of water, energy and CO₂ exchange within a coupled framework add significant value to large-scale monitoring networks like FLUXNET, facilitating upscaling of tower flux observations to address questions of regional carbon cycling and water availability. This study investigates the implementation of an analytical, light-use efficiency (LUE) based model of canopy resistance within a Two-Source Energy Balance (TSEB) scheme driven primarily by thermal remote sensing inputs. The LUE model computes coupled canopy-scale carbon assimilation and transpiration fluxes, and replaces a Priestley–Taylor (PT) based transpiration estimate used in the original form of the TSEB model. In turn, the thermal remote sensing data provide valuable diagnostic information about the sub-surface moisture status, obviating the need for precipitation input data and prognostic modeling of the soil water balance. Both the LUE and PT forms of the model are compared with eddy covariance tower measurements acquired in rangeland near El Reno, OK. The LUE method resulted in improved partitioning of the surface energy budget, capturing effects of midday stomatal closure in response to increased vapor pressure deficit and reducing errors in half-hourly flux predictions from 16 to 12%. The spatial distribution of CO₂ flux was mapped over the El Reno study area using data from an airborne thermal imaging system and compared to fluxes measured by an aircraft flying a transect over rangeland, riparian areas, and harvested winter wheat. Soil respiration contributions to the net carbon flux were modeled spatially using remotely sensed estimates of soil surface temperature, soil moisture, and leaf area index. Modeled carbon and water fluxes from this heterogeneous landscape compared well in magnitude and spatial pattern to the aircraft fluxes. The thermal inputs proved to be valuable in modifying the effective LUE from a nominal species-dependent value. The model associates cooler canopy temperatures with enhanced transpiration, indicating higher canopy conductance and carbon assimilation rates. The surface energy balance constraint in this modeling approach provides a useful and physically intuitive mechanism for incorporating subtle signatures of soil moisture deficiencies and reduced stomatal aperture, manifest in the thermal band signal, into the coupled carbon and water flux estimates.     

A simple single layer model to estimate transpiration from vegetation using multi-spectral and meteorological data

A methodology is developed here to model evapotranspiration (λE_c ) from the canopy layer over large areas by combining satellite and ground measurements of biophysical and meteorological variables. The model developed here follows the energy balance approach, where λE_c is estimated as a residual when the net radiation (Rn), sensible heat flux (H) and ground flux (G) are known. Multi-spectral measurements from the NOAA Advanced Very High Resolution Radiometer (AVHRR) were used along with routine meteorological measurements made on the ground to estimate components of the energy balance. The upwelling long wave radiation, and H from the canopy layer were modelled using the canopy temperature, obtained from a linear relation between the Normalized Difference Vegetation Index (NDVI) and surface temperature. This method separates flux measurements from the canopy and bare soil without the need for a complex two layer model. From theoretical analysis of canopy reflectance, leaf area, and canopy resistance, a model is developed to scale the transpiration estimates from the full canopy to give an area averaged estimate from the mean NDVI of the study area. The model was tested using data collected from the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE), and the results show that the modelled values of total surface evapotranspiration from the soil and canopy layers vary from the ground measurements by less than 9 per cent.     

Evaluating one- and two-source energy balance models in estimating surface evapotranspiration from Landsat-derived surface temperature and field measurements

This article compares one- and two-source energy balance (OSEB and TSEB) models in the estimates of surface energy components using Landsat imagery and surface measurements acquired from an experimental field at Yucheng Station in Northern China. Compared to surface measurements, similar performance between the TSEB and OSEB models has been observed for estimated surface net radiation and soil heat flux. The root mean square difference (RMSD) is within 14–39 W m^?2 in both the TSEB and OSEB models. The residual energy (E _R) correction method yields the best agreement in comparisons of the sensible (H) and latent (LE) heat fluxes estimated using both the TSEB and OSEB models to the eddy covariance (EC) system measurements. The TSEB model is shown to greatly outperform the OSEB model in reproducing surface H and LE measurements. Cirrus clouds are likely responsible for the surface temperature retrieved from the enhanced thematic mapper plus (ETM+) sensor being lower than air temperature on days of the year (DOYs) 178 and 218 of 2009. This atmospheric stability is contrary to the unstable atmosphere that the EC measurements observe. If data on these two days are excluded and the E _R correction method is applied, when comparing the estimated H and LE to the EC measurements, RMSD is within 55 W m^?2 in the TSEB model and is larger than 97 W m^?2 in the OSEB model.     

基于TVDI的大范围干旱区土壤水分遥感反演模型研究

温度植被干旱指数TVDI(Temperature Vegetation Dryness Index)是一种基于光学与热红外遥感通道数据进行植被覆盖区域表层土壤水分反演的方法。当研究区域较大、地表覆盖格局差异显著时,利用TVDI模型来反演陆表土壤水分,精度通常较低。对Sandholt的TVDI土壤水分反演模型进行了改进:利用云掩膜校正和多天平均温度合成来减少云的影响;同时对研究区域地形起伏、覆盖类型差异的影响进行了消除;对TVDI模型干边的模拟方法进行了改进。最后,使用铝盒采样等方法利用新疆地区观测得到的地面数据来拟合改进后的模型参数,并对2009年5月和8月的土壤水分进行了反演实验。与实测数据的比较分析表明,该模型能基本满足大区域土壤水分反演的要求,改进后的模型对新疆地区的土壤水分估算精度有较显著的提高。     

Using NOAA/AVHRR data to determine regional net radiation and soil heat fluxes over the heterogeneous landscape of the Tibetan Plateau

In this study, a parameterization methodology based on NOAA/AVHRR (National Oceanic and Atmospheric Administration/Advanced Very High-Resolution Radiometer) data and field observations is described and tested for deriving the regional surface reflectance, surface temperature, net radiation flux and soil heat flux over a heterogeneous landscape. As a case study, the methodology was applied to the Tibetan Plateau area. Two scenes of NOAA/AVHRR data were used in this study. The derived results were also validated using the ‘ground truth’. The results show that reasonable regional distribution of surface variables (surface reflectance and surface temperature), net radiation flux and soil heat flux over the heterogeneous landscape of the Tibetan Plateau can be obtained by using this methodology. Further improvement of the methodology was also discussed.     

An intercomparison of the Surface Energy Balance Algorithm for Land (SEBAL) and the Two-Source Energy Balance (TSEB) modeling schemes

An intercomparison of output from two models estimating spatially distributed surface energy fluxes from remotely sensed imagery is conducted. A major difference between the two models is whether the soil and vegetation components of the scene are treated separately (Two-Source Energy Balance; TSEB approach) or as a lumped composite (one-source approach; Surface Energy Balance Algorithm for Land; SEBAL) in the parameterization of radiative and turbulent exchanges with the overlying air. Comparisons are performed using data from two largescale field experiments covering sub-humid grassland (Southern Great Plains '97) and semi-arid rangeland (Monsoon '90) having very different landscape properties. In general, there was reasonable agreement between flux output from both models versus a handful of flux tower observations. However, spatial intercomparisons of model output over the full modeling domains yielded relatively large discrepancies (on the order of 100 W m^− 2) in sensible heat flux (H) that are related to land cover. In particular, bare soil and sparsely vegetated areas yielded the largest discrepancies, with TSEB fluxes being in better agreement with tower observations. Modifications to SEBAL inputs that reduced discrepancies with TSEB and observations for bare soil and shrub classes tended to increase differences for other land cover classes. In particular, improvements to SEBAL inputs of surface roughness for momentum tended to exacerbate errors with respect to observed fluxes. These results suggest that some of the simplifying assumptions in SEBAL may not be strictly applicable over the wide range in conditions present within these landscapes. An analysis of TSEB and SEBAL sensitivity to uncertainties in primary inputs indicated that errors in surface temperature or surface-air temperature differences had the greatest impact on H estimates. Inputs of secondary importance were fractional vegetation cover for TSEB, while for SEBAL, the selection of pixels representing wet and dry moisture end-member conditions significantly influenced flux predictions. The models were also run using input fields derived from both local and remote data sources, to test performance under conditions of varying ancillary data availability. In this case, both models performed similarly under both constraints.     

TSEB模型在复杂下垫面下模拟结果比较研究

地表蒸散发对干旱半干旱地区水文过程模拟以及水文平衡有重要影响,复杂地表更是对地表蒸散发模拟提出了新的挑战.利用TSEB(Two-Source Energy Balance)模型,分别以Landsat、MODIS卫星数据为驱动数据,得到黑河下游绿洲地表蒸散发时空分布格局,并利用大孔径闪烁仪和涡动相关仪的观测数据对模拟结果...     

基于TSEB模型的黄河三角洲蒸散量估算

蒸散发作为湿地生态系统中地-气间水热交换的主要方式,很大程度上影响着湿地的水热平衡,合理准确地估算蒸散发量,对湿地生态系统的水分循环、能量平衡以及科学管理具有重要意义。黄河三角洲湿地作为世界上暖温带最广阔、最完整和最年轻的河口湿地生态系统,既是气候变化的敏感区,也是生态环境的脆弱区。针对其地理位置特殊、水资源供需矛盾尖锐等特点,利用SEBAL(Surface Energy Balance Algorithm for Land)和TSEB(Two-Source Energy Balance)模型,对黄河三角洲湿地蒸散发量进行估算:首先利用SEBAL模型计算地表的特征参数和各地表通量,然后利用TSEB模型分离土壤和植被,分别计算黄河三角洲湿地瞬时的土壤蒸发、植被蒸腾和土壤植被总蒸散发量,利用积分关系法进行时间尺度转换,得到日蒸散量。利用气象站实测蒸发值和FAO Penman\|Monteith公式计算的作物系数,对遥感估算结果进行直接和间接精度评价。结果表明反演的蒸散发结果合理,精高较高。分析蒸散的空间分布及不同地表类型的蒸散特性,对比分析芦苇沼泽和芦苇草甸的不同蒸散特点,结果表明基于两模型耦合的方法可用于黄河三角洲湿地蒸散量估算。     

Evapotranspiration calculated from remote multispectral and ground station meteorological data

Evapotranspiration was evaluated by combining remotely sensed reflected solar radiation and surface temperatures with ground station meteorological data (incoming solar radiation, air temperature, windspeed, and vapor pressure) to calculate net radiation and sensible heat flux. Soil heat flux was estimated as a fraction of the net radiation. Instantaneous values of ET were calculated for 18 wheat plots for 44 cloudless days over a growing season. Three of the 18 plots contained lysimeters which provided data to compare against the instantaneous values. For the remaining plots, daily ET was estimated from the instantaneous data and compared with values calculated from soil water contents measured with a neutron moisture meter. For generally clear sky conditions, the comparisons indicated that ET could be adequately evaluated using a combination of remotely sensed and ground based meteorological data. The results suggest that ET maps of relatively large areas could be made using this method with data from airborne sensors. The extent of the area covered appears to be limited by the distance that air temperature and windspeed data can be extrapolated.     

Longwave radiation flux from an urban canopy: Evaluation via measurements of directional radiometric temperature

Longwave radiation flux, an important part of the surface heat budget, is generally represented by εσT_r⁴, where ε is the surface emissivity, σ is the Stefan-Boltzmann constant, and T_r is the measured radiometric temperature. εσT_r⁴ differs from hemispheric emission because the measured radiometric temperature is anisotropic for an uneven surface. This paper analyzes the anisotropy-related error in measurements of longwave radiation flux from a building canopy. The flux difference between εσT_r⁴ and directly measured flux was up to 8% of the directly measured flux, which could be greater than the typical error in measurement of turbulent heat flux over a building canopy. The flux difference increased as the temperature variation within the urban street canyon increased, and also with increasing difference between the incident solar radiation of the building walls and street canyon floors (pavement, roads, ground surface). Theoretical calculations indicate that the flux difference is due to the structure of the building canopy and the temperature difference between the walls and canopy floors. A numerical model of a building canopy heat budget shows that the flux difference increases as the street canyon aspect ratio increases.     

基于LST-EVI特征空间的土壤水分含量反演

干旱是人类历史上的重大自然灾害之一,而土壤水分是干旱监测最重要的指标。利用遥感手段反演地表土壤水分,可以充分反映土壤水分的时空变化特征,适合进行大范围动态监测。研究基于Landsat TM数据,运用普适性单通道算法得到地表温度(LST,Land Surface Temperature),然后选用增强型植被指数(EVI,Enhanced Vegetation Index),构建了LST\|EVI特征空间,计算出温度植被干旱指数(TVDI,Temperature\|Vegetation Dryness Index)。在对实测土壤含水量数据和对应TVDI值进行回归分析的基础上,反演出2010年6月14日黄骅市自然地表20 cm深度处的体积含水量。结果表明:TVDI方法在该研究区是完全可行的,拟合精度较高;研究区自然地表土壤体积含水量分布差异明显,中等含水量地区面积最大,西南和部分北部地区含水量较低,而含水量高的区域主要分布在苇洼和沿海地区。     

基于Landsat-5 TM数据的河南省白沙灌区地表温度反演研究

地表温度是土壤水分和植被水分状态的指示计,在干旱遥感监测中有重要作用。应用Landsat-5 TM遥感数据和气象资料,利用归一化植被指数(NDVI)区分地表覆盖类型,采用Van de Griend的经验公式法结合典型地表赋值法计算出地表比辐射率。用单窗算法和单通道算法分别对河南省白沙灌区地表温度进行反演,结果表明:两种方法均能较好地将白沙灌区地表温度分布趋势反映出来,单窗算法的反演精度较高,绝对误差为1.1 ℃,更适宜白沙灌区的地表温度反演,进而可以提高灌区旱情遥感监测精度。     

The influence of meteorological conditions and topographic parameters on the beech forest microclimate of Simbruini Mountains,central Italy

The relation between vegetation surface temperature and remotely sensed spectral vegetation indices has been examined by a number of authors. The observed linear decrease in surface temperature with the increase in vegetation cover density has generally been explained in terms of the increase in latent heat flux associated with greater amounts of transpirationally active vegetation. However, these investigations have initially concentrated in spatially uniform crop or pasture targets on level terrain, excluding more complex forested environments with variable Sun-sensor-surface geometry. In irregular terrains, the vegetation surface temperature may be strongly influenced by topographic parameters, such as altitude and insulation angle, so that the actual forest microclimate is often difficult to evaluate. Moreover, in the thermal regime, the emission of radiative flux within the canopy element is very tightly coupled to the environment through driving mechanisms such as meteorological conditions. In fact, the allocation of absorbed solar radiation into sensible heat flux and latent heat flux is dominated by the availability of water at the Earth's surface and thus by precipitations and air temperature conditions. In this paper, which uses remotely sensed inputs of surface temperature and vegetation fractional cover, the effects of topographic parameters and vegetation cover density on surface temperature of vegetation are investigated based on Landsat 5 satellite images obtained in the daytime of two clear summer days with different antecedent meteorological conditions. For both scenes analysed, results indicate that altitude as well as the orientation of the surface relative to the Sun were the most important factors controlling surface temperatures of beech forests of Simbruini Mountains, in central Italy.     

Relation between vegetation canopy surface temperature and the Sun-surface geometry in a mountainous region of central Italy

Evapotranspiration is the dominant energy exchange process in dense vegetated environments with an adequate water supply. If water is available vegetation canopy temperatures do not respond immediately upon intercepting solar radiation because of the apportionment of absorbed solar radiation into sensible and latent heat. This lag in the thermal conditions of vegetation canopy following the incident solar flux can be even more complex after sunrise because the presence of dew on the foliage requires more available energy investment in evaporating water and less energy spent in warming the foliage. The aim of this Letter, which is based on remotely-sensed thermal data obtained from Landsat Thematic Mapper in the daytime of a clear summer day, is to investigate the relationship between canopy surface temperatures and the incident solar radiation for a forested montainous landscape of central Italy. Results show that, under the conditions of our experiment, a time lag of one hour considerably increases the linear relation between vegetation canopy temperature and local solar illumination angle.     

基于能量平衡原理的FPAR遥感反演研究

光合有效辐射吸收系数(FPAR)是描述植被结构以及冠层-大气物质与能量交换过程的基本生理变量。从能量守恒的原理出发,结合非线性混合像元模型,分析了太阳入射能量中的植被冠层反射、土壤吸收分量的光谱反演方法,建立了简化的FPAR遥感反演模型(FPEB)。分别应用2011和2013年西藏自冶区那曲实验数据\,2011年西藏自冶区当雄实验数据和2013年内蒙古自冶区海拉尔的实验数据,对建立的FPAR遥感反演模型进行了验证,并将FPEB模型反演结果与传统的植被指数统计模型反演结果进行了对比分析,结果表明:FPEB模型的FPAR反演精度优于NDVI统计模型,且与其他基于能量平衡原理提出的反演FPAR的模型相比具有输入参数少,模型简单的优势,在空间区域和时间上具有很好的普适性。     

基于多源信息融合的土壤含水量估算

遥感信息在大面积土壤水分监测中具有不可替代的优势。通过对试验区域的气象数据、土壤类型数据、土壤和水体的光谱特征曲线、多时相遥感影像数据等进行预处理,提取图像信息和属性数据,并对土地利用类型和植被覆盖度进行划分。基于土壤的光谱响应机制建立像元反射光谱信息分解模型,以此计算出该区域土壤容积含水率。结果表明该方法对于低植被区的监测精度较高(理论精度89.78%),可作为土壤水分监测预警的依据。     

The estimation of the surface moisture of a vegetated soil using aerial infrared photography

The bidirectional reflectance of near infrared wavelengths of electromagnetic radiation from a vegetation canopy is primarily determined by the relative area and reflectance of the canopy and canopy dependent components: leaves, non-green vegetation, soil and shadow. It has been shown that when the percentage cover of leaves and non-green vegetation are both known and constant and the effect of shadow is minimal, then the near infrared bidirectional reflectance from the-canopy is negatively related to surface soil moisture.

This study was based on the above observation to estimate surface soil moisture of a vegetated soil from remotely sensed measurements of near infrared bidirectional reflectance.

The near infrared bidirectional reflectance, surface soil moisture and vegetation cover were measured at 10 heathland sites on 18 dates. The surface soil moisture was significantly related (at better than the 1 per cent level) to the Y axis intercept, when near infrared bidirectional reflectance (Y) was regressed against the percentage cover of green vegetation (X). This relationship between soil moisture and canopy reflectance was then used to enable the surface soil moisture of vegetated heathland soil to be estimated by means of five flights of black and white infrared aerial photography. It proved possible to estimate the surface soil moisture of the vegetated soil with an accuracy of ±18·4 percent at the 95 percent confidence limits. Possible improvements to the technique are discussed.     

Using leaf chlorophyll to parameterize light-use-efficiency within a thermal-based carbon, water and energy exchange model

Chlorophylls absorb photosynthetically active radiation and thus function as vital pigments for photosynthesis, which makes leaf chlorophyll content (C_ab) useful for monitoring vegetation productivity and an important indicator of the overall plant physiological condition. This study investigates the utility of integrating remotely sensed estimates of C_ab into a thermal-based Two-Source Energy Balance (TSEB) model that estimates land-surface CO₂ and energy fluxes using an analytical, light-use-efficiency (LUE) approach to estimating bulk canopy resistance. The LUE model component computes canopy-scale carbon assimilation and transpiration fluxes, internally estimating fluctuations in effective LUE from a nominal (species-dependent) value (LUE_n) in response to short-term variations in environmental conditions. LUE_n, however, may vary on a daily timescale, responding to changes in plant phenology, physiological condition and nutrient status. Therefore, remote sensing methodologies for improving daily estimates of LUE_n have been investigated. Day-to-day variations in LUE_n were assessed for a heterogeneous corn crop field in Maryland, U.S.A. through model optimization with eddy covariance CO₂ flux tower observations. The optimized daily LUE_n values were then compared to gridded estimates of C_ab over the tower flux footprint, retrieved from a canopy reflectance model driven by green, red and near-infrared imagery acquired with an aircraft imaging system. The tower-calibrated LUE_n data were generally well correlated with airborne retrievals of C_ab, and hourly water, energy and carbon flux estimation accuracies from TSEB were significantly improved when using C_ab for delineating spatio-temporal variations in LUE_n. The study highlights the potential synergy between thermal infrared and shortwave reflective wavebands in producing valuable remote sensing data for estimating carbon, water and heat fluxes within a two-source energy balance framework.