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。     

作物蒸散发模型研究中的地表温度反演

针对美国加州Merced县2002年8月9日的ETM+影像,利用单窗温度反演算法反演了遥感蒸散发模型S SEBI中的地表温度参数。选用了ETM+热红外的高增益61波段,对热红外波段反射率较低的植被覆盖研究区进行了地表温度反演,并反演地表温度所需要的几个参数：亮度温度、地表比辐射率、大气透射率。最后得出了研究区域地表温度分布结果：水体地表温度低于植被作物,建筑或道路的地表温度最高。不同地物间地温是不同的,作为蒸散发反演的重要参数,这将影响不同地物蒸散发估算。因此精确反演地表温度,将为今后蒸散发的研究打好基础。     

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SEBS模型的藏北那曲蒸散量研究

SEBS模型为研究高原非均匀地表区域蒸散量估算提供了一种新的方法,为高原气象台站稀少地区蒸散量变化研究提供一定的参考依据。应用SEBS模型,利用MODIS遥感数据反演所需的地表物理参数(如反照率、比辐射率、地表温度和植被覆盖度等),再结合气象站地面观测数据,包括温度、相对湿度、风速、气压等,对藏北那曲地表能量通量和蒸散量进行估算;最后分析了蒸散量与气象因子、NDVI之间的关系。结果表明:2010年藏北那曲蒸散量呈春夏季高,秋冬季低的变化趋势,蒸散量较大区域为研究区南部、东北部和区域内的水体;中部和西北部地区蒸散量较小。气温和地表温度对蒸散量的影响较明显,随着气温和地表温度的升高蒸散量不断增大,NDVI对蒸散量也有一定的影响。所以,SEBS模型在估算高原地区蒸散量方面具有一定的精度,可以满足区域日蒸散发估算的需要。     

基于TESEBS模型估算高原地区地表蒸散发

为检验TESEBS(Topographical Enhanced Surface Energy Balance System)模型在高原地区的适用性,利用2014年高原9个站点的实测资料对TESEBS模型进行适用性检验,鉴于模型估算的感热通量偏差较大,提出利用地表温度—植被指数(LST-NDVI)特征空间法来确定蒸散发率,并将模型估算的卫星过境时刻瞬时蒸散发与实测值进行比较。结果表明:TESEBS模型估算高原不同下垫面的蒸散发与实测值之间的偏差较大;利用LST-NDVI特征空间法确定蒸散发率能很好地改善模型对蒸散发的估算精度,相关系数从0.65提高至0.83,均方根误差从144减小至80 W·m~(-2),相对误差从67%减小至39%。特征空间法引入后,TESEBS模型估算的地表蒸散发明显小于原模型的估算结果,且模型给出的研究区地表蒸散发分布特征与植被指数NDVI的分布特征相一致。     

基于Landsat ETM+遥感数据的组分温度反演方法研究

地表温度在干旱监测和模拟地表热通量中有重要作用。在干旱半干旱地区,双源能量平衡模型(TSEB)通常用于计算地表的热通量。以黑河中游典型灌区为研究区域,选取4个时相的Landsat-7 ETM+遥感影像,通过植被指数与TSEB模型结合的方法反演土壤表面温度和植被冠层温度,并重点讨论土壤表面温度和植被冠层温度的分解算法。结果表明:土壤表面温度和植被冠层温度具有较好的时空一致性;土壤表面温度与植被冠层温度的反演精度通过地表净辐射与地表热通量得到了间接验证。地表净辐射与地表热通量的计算值与观测值相关性好,相关系数大于0.92。地表净辐射与地表热通量的线性回归分析表明拟合精度高。通过地表温度分解的方法获得的土壤表面温度和植被冠层温度,对监测典型区域的干旱和模拟地表热通量是可行的。     

区域遥感蒸散发模型方法研究

遥感技术为大面积区域陆面水分蒸散发量估算提供了一种新的手段,分析了国内外应用较好的遥感监测陆面水分蒸发的几种方法,主要包括地表热量平衡方法、互补相关陆面蒸散发、Penman-Montieth模型和区域蒸散发的气候学方法,并给出了可供参考的地面参数(地面反照率、NDVI、陆面温度等)的遥感获取方法,还阐述了各种方法的特点及彼此之间的联系。     

主被动遥感数据协同估算干旱区草原植被生物量

结合主动微波遥感和被动光学遥感反映地表植被的各自优势,发展了一种主被动遥感协同估算干旱区草原植被生物量的模型。该模型将植被覆盖度作为水云模型的附加参数,将总体散射分为植被覆盖区散射和裸土区散射两部分,将水云模型应用到了植被覆盖稀疏区域。利用改进的水云模型和双极化ASAR数据,通过建立方程组估算植被生物量。将该方法用于乌图美仁草原植被生物量的估算,验证了该方法的有效性。结果表明:该主被动遥感协同估算模型能够成功地估算干旱区草原植被生物量,并且取得了较好的估算精度(R2=0.8562,RMSE=0.1813kg/m2)。最后,分析了该方法估算植被生物量的误差来源。     

地表蒸散发遥感产品比较与分析

蒸散发遥感估算与其他定量遥感反演参数相比存在算法复杂,环节多,输入参数多,不确定性来源多等不利因素,因而造成蒸散发遥感产品成熟度较低,产品较少,不能满足高时空分辨率、高精度、实时获取等应用需求的问题。从蒸散发遥感产品角度出发,选择目前国内外较为常用和知名的蒸散发遥感产品,系统分析了各产品的实际蒸散发估算模型方法、阻抗的参数化方案、地表可用能量的估算方法、时间尺度扩展方法,以及计算流程和输入数据等,重点比较各产品在模型算法和计算流程上的不同设计思路和处理方法,以便更加深入地理解地表蒸散遥感估算的复杂性和不确定性,对未来研发出精度更高,普适性更广的蒸散发遥感产品提供重要的参考和基础框架。最后对这些产品的验证和应用情况进行了分析对比,总结了目前蒸散发遥感产品在产品生产、验证等方面存在的问题,探讨了未来蒸散发遥感产品的发展趋势。     

基于遥感的地表蒸散发研究进展

地表蒸散发是整个生物圈、大气圈和水圈中水分循环和能量传输的重要控制因素。遥感技术的应用使得区域尺度的蒸散发估算成为可能,并在过去的几十年中快速发展。研究对遥感蒸散发估算进行了总结与归纳,在此基础上展望了今后的发展方向,明确指出了遥感蒸散发未来研究的突破点及发展方向。提出未来应加强蒸散发尺度效应、夜间蒸散发、不同蒸散发产品的统一真实性检验、国产卫星数据的使用、更高时空分辨率产品的研发以及机器学习在遥感蒸散发产品中的应用。     

A TSAR model for daily evapotranspiration at broad spatial scales: A case study in Northern China

It is technically difficult to estimate the evapotranspiration over a large area due to variation of the effect of canopy microclimate on vegetation and soil processes. In this study, an approach is developed to model daily evapotranspiration from the canopy layer and soil surface of large areas by combining remotely sensed data and ground-based meteorological variables. Combined with vegetation fraction data, a two-layer soil-vegetation atmosphere resistance (TSAR) model for the estimation of regional daily evapotranspiration is derived. A case study in Northern China shows that this model requires less ground information and is much simpler computationally than previous methods, while maintaining reasonably accurate results. The variation and characteristics of evapotranspiration over Northern China are also discussed.     

Retrieval of Component Temperatures based on Landsat-7 ETM+ Remote Sensing Data

Land surface temperature plays an important role in drought monitoring and Simulation of surface heat flux.In arid and semi\|arid regions,the Two\|Source Energy Balance model (TSEB) is commonly used to calculate the heat flux of the earth’s surface.Taking the typical irrigated area of the middle reaches of Heihe as the research area,the four Landsat\|7 ETM+ remote sensing images are selected.The soil surface temperature and canopy temperature were retrieved by combining vegetation index with TSEB model.The decomposition algorithm of soil surface temperature and vegetation canopy temperature is mainly discussed.The results showed that soil surface temperature and vegetation canopy temperature had good temporal and spatial consistency.The inversion accuracy of soil surface temperature and vegetation canopy temperature is indirectly verified by surface net radiation and surface heat flux.The calculated values of surface net radiation and surface heat flux correlate well with the observed values,and the correlation coefficient is greater than 0.92.The linear regression analysis of surface net radiation and surface heat flux shows that the fitting accuracy is high.The soil surface temperature and canopy temperature obtained by surface temperature decomposition are feasible for monitoring drought in typical areas and simulating surface heat flux.     

城市热岛效应地表通量空间分布研究

城市化进程的加快促使更多大中城市的产生以及城市面积的扩展,导致更加严重的城市热岛现象。为了更加深入理解城市热岛效应产生根源,以西安市城区为例采用美国陆地卫星遥感数据反演或估算地表温度、植被指数以及地表通量等变量,不仅采用传统的地表温度参数理解城市热岛现象,还着重分析城市建成区和郊区的地表通量空间分布格局及其与地表温度的关系。研究发现西安城市建成区与郊区之间热环境存在显著的差异,地表温度不仅与植被覆盖状况具有密切的关系,还与地表潜热通量和实际蒸散发变量存在显著的反相关关系。详细分析表明拥有众多工厂企业的西安市莲湖区热岛效应尤为显著,而位于市中心的新城区次之,具有较大面积郊区的灞桥区热岛效应并不明显。因此城市绿地不仅影响城市建成区的地表温度空间分布,还对地表通量以及实际蒸散发的空间格局产生重要的影响,在调节城市热岛效应方面具有重要的作用。
     

Estimation of daily actual evapotranspiration from remotely sensed data under complex terrain over the upper Chao river basin in North China

Daily actual evapotranspiration over the upper Chao river basin in North China on 23 June 2005 was estimated based on the Surface Energy Balance Algorithm for Land (SEBAL), in which the parameterization schemes for calculating the instantaneous solar radiation and daily integrated radiation were improved by accounting for the variations in slope and azimuth of land surface and terrain shadow in mountainous areas. The evapotranspiration (ET) estimated from satellite data in this study for the whole watershed ranges from 0 mm to 7.3 mm day^?1 with a mean of 3.4 mm day^?1, which was validated by Penman–Monteith approaches for water body and paddy land. The comparison of ET estimates for a wide range of land cover types reflected distinct mechanisms of energy partition and water removal of various land cover types, showing differences in the spatial distribution pattern of ET, which could be not only the reflection but also the driving force of advection and local circulation that may violate the surface energy balance equation in the vertical direction. The spatial variation in daily solar radiation and ET estimates under the complex terrain of forest land were elaborated and evaluated by exploring the relationship between ET estimates and elevations for wood land and grass land. In addition, the utility and limitations of SEBAL's applicability to watersheds with various land cover types and complex terrain were analysed.     

Study on component temperatures inversion using satellite remotely sensed data

Because of the low spatial resolution of MODIS data, it is important to decompose mixed pixels to retrieve component temperatures using thermal infrared bands. Grasslands with different coverage conditions are prominent in the area under study. Because of the simple vegetation structure, radiation is less influenced by vegetation shade. If the internal structure of the component parts of the mixed pixel is ignored, the total radiation emitted by the mixed pixel is approximately the sum of the radiation emitted by each component part of the pixel, weighted according to the percentage area of each component part. Vegetation/soil component temperatures based on the sub‐pixel scale are inverted using a constrained optimization algorithm—the genetic algorithm. The study not only broadens the application of the linear spectral mixing model but also develops a practical method for component temperatures retrieval from MODIS satellite data. The results provide more precise parameters for estimation of land surface energy balance and evapotranspiration.     

Remote sensing of evapotranspiration and carbon uptake at Harvard Forest

A land surface vegetation index, defined as the difference of microwave land surface emissivity at 19 and 37 GHz, was calculated for a heavily forested area in north central Massachusetts. The microwave emissivity difference vegetation index (EDVI) was estimated from satellite SSM/I measurements at the defined wavelengths and used to estimate land surface turbulent fluxes. Narrowband visible and infrared measurements and broadband solar radiation observations were used in the EDVI retrievals and turbulent flux estimations. The EDVI values represent physical properties of crown vegetation such as vegetation water content of crown canopies. The collocated land surface turbulent and radiative fluxes were empirically linked together by the EDVI values. The EDVI values are statistically sensitive to evapotranspiration fractions (EF) with a correlation coefficient (R) greater than 0.79 under all-sky conditions. For clear skies, EDVI estimates exhibit a stronger relationship with EF than normalized difference vegetation index (NDVI). Furthermore, the products of EDVI and input energy (solar and photosynthetically active radiation) are statistically significantly correlated to evapotranspiration (R = 0.95) and CO₂ uptake flux (R = 0.74), respectively.     

A model for the estimation of fractional vegetation cover based on the relationship between vegetation and soil moisture

Based on surface temperature and the normalized difference vegetation index (NDVI), we calculated the temperature vegetation dryness index (TVDI). Using the relationship between TVDI and NDVI, we established a vegetation–soil moisture response model that captures the sensitivity of NDVI's response to changes in TVDI using a linear unmixing approach, and validated the model using Landsat Thematic Mapper (TM) images acquired in 1997, 2004 and 2006 and a Landsat Enhanced Thematic Mapper Plus (ETM+) image acquired in 2000. We determined the correlations between TVDI and field-measured soil moisture in 2006. TVDI was correlated significantly with soil moisture at depths of 0 to 10 cm and 10 to 20 cm, so TVDI can be used as an index that captures changes in soil moisture at these depths. By using fractional vegetation cover (FVC) data measured in the field to validate the estimated values, we estimated mean absolute errors of 0.043 and 0.137 for shrub and grassland vegetation coverage, respectively, demonstrating acceptable estimation accuracy. Based on these results, it is possible to estimate a region's FVC using the linear unmixing model. The results show bare land coverage values distributed similarly to TVDI values. In mountain areas, grassland coverage mostly ranged from 0.4 to 0.6. Shrub coverage mostly ranged from 0.4 to 0.6. Forest coverage was zero in most parts of the study area.