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The interactions between crops and the atmosphere significantly impact surface energy and hydrology budgets, climate, crop yield, and agricultural management. In this study, a multipass land data assimilation scheme (MLDAS) is proposed based on the Noah-MP-Crop model. The ensemble Kalman filter (EnKF) method is used to jointly assimilate the leaf area index (LAI), soil moisture, and solar-induced chlorophyll fluorescence (SIF) observations to predict sensible (H) and latent (LE) heat fluxes, gross primary productivity (GPP), etc. Such joint assimilation is demonstrated to be effective in constraining the model state variables (i.e., leaf biomass and soil moisture) and optimizing key crop-model parameters (i.e., specific leaf area, SLA, and maximum rate of carboxylation, Vcmax). The performance of the MLDAS is evaluated against observations at two AmeriFlux cropland sites, revealing good an agreement with the observed H, LE, and GPP. When using optimized model parameters (SLA and Vcmax) and jointly assimilating LAI, soil moisture, and SIF observations, the MLDAS produces 34.28%, 26.90%, and 51.82% lower root mean square deviations (RMSDs) for daily H, LE, and GPP estimates compared with the Noah-MP-Crop open loop simulation. Our findings also indicate that the H and LE predictions are more sensitive to soil moisture measurements, while the GPP simulations are more affected by LAI and SIF observations. The results indicate that performances of physical models can be greatly improved by assimilating multi-source observations within MLDAS.
Tongren Xu; Fei Chen; Xinlei He; Michael Barlage; Zhe Zhang; Shaomin Liu; Xiangping He. Improve the Performance of the Noah‐MP‐Crop Model by Jointly Assimilating Soil Moisture and Vegetation Phenology Data. Journal of Advances in Modeling Earth Systems 2021, 13, 1 .
AMA StyleTongren Xu, Fei Chen, Xinlei He, Michael Barlage, Zhe Zhang, Shaomin Liu, Xiangping He. Improve the Performance of the Noah‐MP‐Crop Model by Jointly Assimilating Soil Moisture and Vegetation Phenology Data. Journal of Advances in Modeling Earth Systems. 2021; 13 (7):1.
Chicago/Turabian StyleTongren Xu; Fei Chen; Xinlei He; Michael Barlage; Zhe Zhang; Shaomin Liu; Xiangping He. 2021. "Improve the Performance of the Noah‐MP‐Crop Model by Jointly Assimilating Soil Moisture and Vegetation Phenology Data." Journal of Advances in Modeling Earth Systems 13, no. 7: 1.
The accurate estimation of the temperature sensitivity of ecosystem respiration (Q10) is important to understanding the terrestrial ecosystem carbon cycle, especially in northern high‐latitude regions (NHLs). Q10 estimated by the conventional approach at the annual scale is influenced by seasonal confounding effects. Based on singular spectrum analysis (SSA), scale‐dependent parameter estimation (SCAPE) is considered an effective approach to eliminate confounding effects. Nevertheless, the performance of the decomposition and reconstruction schemes in the SCAPE approach in Q10 estimation remains limited, which hampers its further application in larger‐scale systems. In this study, we utilized an improved scale‐dependent parameter estimation (iSCAPE) approach to analyze trends of the unconfounded Q10 and its environmental controls in NHLs. The results showed that in NHLs, the confounding effects in forest ecosystems were smaller than those in cropland and grassland ecosystems. The apparent Q10 estimated by the conventional approach varied among 32 sites with a mean value of 2.82 (95% confidence interval (CI): 2.72‐2.91), while the mean intrinsic Q10 estimated by the iSCAPE approach across the 32 sites was 1.53 (95% CI: 1.48‐1.57). The apparent Q10 increased with the annual mean temperature. The intrinsic Q10 decreased with the increasing of spatial temperature gradient. The current study indicates that ecosystem respiration in NHLs is less sensitive to climate warming than previously reported. The seasonality of ecosystem respiration should be eliminated when estimating Q10 to avoid overestimating climate‐carbon cycle feedback.
Dongxing Wu; Shaomin Liu; Xiuchen Wu; Xiaofan Yang; Tongren Xu; Ziwei Xu; Hanyu Shi. Diagnosing the Temperature Sensitivity of Ecosystem Respiration in Northern High‐Latitude Regions. Journal of Geophysical Research: Biogeosciences 2021, 126, 1 .
AMA StyleDongxing Wu, Shaomin Liu, Xiuchen Wu, Xiaofan Yang, Tongren Xu, Ziwei Xu, Hanyu Shi. Diagnosing the Temperature Sensitivity of Ecosystem Respiration in Northern High‐Latitude Regions. Journal of Geophysical Research: Biogeosciences. 2021; 126 (4):1.
Chicago/Turabian StyleDongxing Wu; Shaomin Liu; Xiuchen Wu; Xiaofan Yang; Tongren Xu; Ziwei Xu; Hanyu Shi. 2021. "Diagnosing the Temperature Sensitivity of Ecosystem Respiration in Northern High‐Latitude Regions." Journal of Geophysical Research: Biogeosciences 126, no. 4: 1.
Successfully applied in the carbon research area, sun-induced chlorophyll fluorescence (SIF) has raised the interest of researchers from the water research domain. However, current works focused on the empirical relationship between SIF and plant transpiration (T), while the mechanistic linkage between them has not been fully explored. Two mechanism methods were developed to estimate T via SIF, namely the water-use efficiency (WUE) method and conductance method based on the carbon–water coupling framework. The T estimated by these two methods was compared with T partitioned from eddy covariance instrument measured evapotranspiration at four different sites. Both methods showed good performance at the hourly (R2 = 0.57 for the WUE method and 0.67 for the conductance method) and daily scales (R2 = 0.67 for the WUE method and 0.78 for the conductance method). The developed mechanism methods provide theoretical support and have a great potential basis for deriving ecosystem T by satellite SIF observations.
Huaize Feng; Tongren Xu; Liangyun Liu; Sha Zhou; Jingxue Zhao; Shaomin Liu; Ziwei Xu; Kebiao Mao; Xinlei He; Zhongli Zhu; Linna Chai. Modeling Transpiration with Sun-Induced Chlorophyll Fluorescence Observations via Carbon-Water Coupling Methods. Remote Sensing 2021, 13, 804 .
AMA StyleHuaize Feng, Tongren Xu, Liangyun Liu, Sha Zhou, Jingxue Zhao, Shaomin Liu, Ziwei Xu, Kebiao Mao, Xinlei He, Zhongli Zhu, Linna Chai. Modeling Transpiration with Sun-Induced Chlorophyll Fluorescence Observations via Carbon-Water Coupling Methods. Remote Sensing. 2021; 13 (4):804.
Chicago/Turabian StyleHuaize Feng; Tongren Xu; Liangyun Liu; Sha Zhou; Jingxue Zhao; Shaomin Liu; Ziwei Xu; Kebiao Mao; Xinlei He; Zhongli Zhu; Linna Chai. 2021. "Modeling Transpiration with Sun-Induced Chlorophyll Fluorescence Observations via Carbon-Water Coupling Methods." Remote Sensing 13, no. 4: 804.
Drought, a natural hydrometeorological phenomenon, has been more frequent and more widespread due to climate change. Water availability strongly regulates the coupling (or trade-off) between carbon uptake via photosynthesis and water loss through transpiration, known as water-use efficiency (WUE). Understanding the effects of drought on WUE across different vegetation types and along the wet to dry gradient is paramount to achieving better understanding of ecosystem functioning in response to climate change. We explored the physiological and environmental control on ecosystem WUE in response to drought using observations for 44 eddy covariance flux sites in the Northern Hemisphere. We quantified the response of WUE to drought and the relative contributions of gross primary production (GPP) and evapotranspiration (ET) to the variations of WUE. We also examined the control of physiological and environmental factors on monthly WUE under different moisture conditions. Cropland had a peak WUE value under moderate drought conditions, while grassland, deciduous broadleaf forest (DBF), evergreen broadleaf forest (EBF), and evergreen needleleaf forest (ENF) had peak WUE under slight drought conditions. WUE was mainly driven by GPP for cropland, grassland, DBF, and ENF but was mainly driven by ET for EBF. Vapor pressure deficit (VPD) and canopy conductance (Gc) were the most important factors regulating WUE. Moreover, WUE had negative responses to air temperature, precipitation, and VPD but had a positive response to Gc and ecosystem respiration. Our findings highlight the different effects of biotic and abiotic factors on WUE among different vegetation types and the important roles of VPD and Gc in controlling ecosystem WUE in response to drought.
Jingxue Zhao; Huaize Feng; Tongren Xu; Jingfeng Xiao; Rossella Guerrieri; Shaomin Liu; Xiuchen Wu; Xinlei He; Xiangping He. Physiological and environmental control on ecosystem water use efficiency in response to drought across the northern hemisphere. Science of The Total Environment 2020, 758, 143599 .
AMA StyleJingxue Zhao, Huaize Feng, Tongren Xu, Jingfeng Xiao, Rossella Guerrieri, Shaomin Liu, Xiuchen Wu, Xinlei He, Xiangping He. Physiological and environmental control on ecosystem water use efficiency in response to drought across the northern hemisphere. Science of The Total Environment. 2020; 758 ():143599.
Chicago/Turabian StyleJingxue Zhao; Huaize Feng; Tongren Xu; Jingfeng Xiao; Rossella Guerrieri; Shaomin Liu; Xiuchen Wu; Xinlei He; Xiangping He. 2020. "Physiological and environmental control on ecosystem water use efficiency in response to drought across the northern hemisphere." Science of The Total Environment 758, no. : 143599.
Significant water quality changes have been observed in the Dongting Lake region due to environmental changes and the strong influence of human activities. To protect and manage Dongting Lake, the long-term dynamics of the water surface and algal bloom areas were systematically analyzed and quantified for the first time based on 17 years of Moderate Resolution Imaging Spectroradiometer (MODIS) observations. The traditional methods (index-based threshold algorithms) were optimized by a dynamic learning neural network (DL-NN) to extract and identify the water surface area and algal bloom area while reducing the extraction complexity and improving the extraction accuracy. The extraction accuracy exceeded 94.5% for the water and algal bloom areas, and the analysis showed decreases in the algal bloom and water surface areas from 2001–2017. Additionally, the variations in the water surface and algal bloom areas are greatly affected by human activities and climatic factors. The results of these analyses can help us better monitor human contamination in Dongting Lake and take measures to control the water quality during certain periods, which is crucial for future management. Moreover, the traditional methods optimized by the DL-NN used in this study can be extended to other inland lakes to assess and monitor long-term temporal and spatial variations in algal bloom areas and can also be used to acquire baseline information for future assessments of the water quality of lakes.
Mengmeng Cao; Kebiao Mao; Xinyi Shen; Tongren Xu; Yibo Yan; Zijin Yuan. Monitoring the Spatial and Temporal Variations in The Water Surface and Floating Algal Bloom Areas in Dongting Lake Using a Long-Term MODIS Image Time Series. Remote Sensing 2020, 12, 3622 .
AMA StyleMengmeng Cao, Kebiao Mao, Xinyi Shen, Tongren Xu, Yibo Yan, Zijin Yuan. Monitoring the Spatial and Temporal Variations in The Water Surface and Floating Algal Bloom Areas in Dongting Lake Using a Long-Term MODIS Image Time Series. Remote Sensing. 2020; 12 (21):3622.
Chicago/Turabian StyleMengmeng Cao; Kebiao Mao; Xinyi Shen; Tongren Xu; Yibo Yan; Zijin Yuan. 2020. "Monitoring the Spatial and Temporal Variations in The Water Surface and Floating Algal Bloom Areas in Dongting Lake Using a Long-Term MODIS Image Time Series." Remote Sensing 12, no. 21: 3622.
To investigate oasis-desert microclimate effects, we performed a series of numerical simulations in an idealized oasis-desert system based on an improved computational fluid dynamics (CFD) model for simulating atmospheric boundary layer flows, air temperature and humidity. Numerical simulations were designed based on the hydrometeorological observations obtained during the HiWATER-MUSOEXE (Heihe Watershed Allied Telemetry Experimental Research, Multi-Scale Observation Experiment on Evapotranspiration over heterogeneous land surfaces) campaign. The results are summarized as follows: (1) Oasis-desert interactions are significantly affected by background wind conditions. We observed the oasis-desert local circulation under calm background wind conditions and the oasis thermal internal boundary layer under low wind speed conditions induced by hydrothermal contracts. These interactions will disappear when the background wind speed is sufficiently high, and there is only an oasis dynamic internal boundary layer caused by the aerodynamic roughness length contrast. (2) Oasis-desert interactions lead to a series of microclimate effects, including the oasis cold-wet island effect, air humidity inversion effect within the surrounding desert and oasis wind shield effect, which are important for the stability and sustainability of the oases-desert ecosystem. (3) The hydrothermal conditions due to the difference between the oasis and desert, the vegetation fraction and distribution patterns impact the oasis-desert microclimate effects. The intensity of oasis-desert interactions increases with the land surface temperature (LST) difference in the oasis-desert. The oasis-desert interactions are gradually strengthened with the increase of the vegetation fraction within the oasis. Integrated ecological and economic benefits of the oasis, the oasis vegetation pattern, which includes the croplands and shelterbelts staggered within the oasis and the shelterbelts surrounding the outside, is beneficial to limiting the loss of water vapor and preventing sandstorms from the oasis. The findings of the current study improve the fundamental understanding of the microclimate and provide implications for maintaining the sustainability of oasis-desert ecosystems.
Rui Liu; Andrey Sogachev; Xiaofan Yang; Shaomin Liu; Tongren Xu; Junjie Zhang. Investigating microclimate effects in an oasis-desert interaction zone. Agricultural and Forest Meteorology 2020, 290, 107992 .
AMA StyleRui Liu, Andrey Sogachev, Xiaofan Yang, Shaomin Liu, Tongren Xu, Junjie Zhang. Investigating microclimate effects in an oasis-desert interaction zone. Agricultural and Forest Meteorology. 2020; 290 ():107992.
Chicago/Turabian StyleRui Liu; Andrey Sogachev; Xiaofan Yang; Shaomin Liu; Tongren Xu; Junjie Zhang. 2020. "Investigating microclimate effects in an oasis-desert interaction zone." Agricultural and Forest Meteorology 290, no. : 107992.
The Heihe River Basin (HRB), with unique landscapes and coexisting cold and arid regions, is the second largest endorheic basin in northwestern China. The Heihe integrated observatory network was established in 2007, which included multi-element, multiscale, distributed, and incorporating satellite-airborne-ground based observations via Internet of Things technology; these observations span the main land cover of the basin. This observatory provides a great opportunity to analyze the spatiotemporal variation in evapotranspiration (ET) in the HRB, and ET characteristics were investigated on three scales (typical ecosystems, oasis-desert systems, watershed) taking the HRB as a research object. The average annual ET in typical ecosystems is approximately 380–530 mm upstream (alpine meadow, Qinghai spruce, shrub), 640–1000 mm midstream (maize, wetland), 610–680 mm downstream (riparian forest), and 190 mm and 50 mm in midstream and downstream desert surfaces, respectively. The ET from plant surfaces is strongly controlled by available energy in upstream and midstream regions, while it is controlled by vapor pressure deficit (VPD) and surface conductance downstream. The ET in oasis and desert systems is characterized by three gradients: plant, residential area/barren land, and desert, with a maximum difference of annual ET more than 500 mm. This difference is primarily caused by variations of soil moisture among different underlying surfaces. For watershed ET, higher ET was observed upstream, and it decreased from midstream to downstream, with the highest values in the oasis. The annual ET in the main plant surfaces was approximately 500–700 mm, 600–800 mm, and 600–700 mm in the up-, mid-, and downstream regions, respectively, while the ET was approximately 100–250 mm and 50–200 mm in desert and barren or sparsely vegetation surfaces in the mid- and downstream regions, respectively. The spatiotemporal variations of ET were primarily influenced by land cover, soil moisture, vegetation condition and available energy. The results improve our understanding of the spatiotemporal variations in ET in the HRB and apply to comparable endorheic basins with similar climatic and landscape conditions.
Ziwei Xu; Shaomin Liu; Zhongli Zhu; Ji Zhou; Wenjiao Shi; Tongren Xu; Xiaofan Yang; Yuan Zhang; Xinlei He. Exploring evapotranspiration changes in a typical endorheic basin through the integrated observatory network. Agricultural and Forest Meteorology 2020, 290, 108010 .
AMA StyleZiwei Xu, Shaomin Liu, Zhongli Zhu, Ji Zhou, Wenjiao Shi, Tongren Xu, Xiaofan Yang, Yuan Zhang, Xinlei He. Exploring evapotranspiration changes in a typical endorheic basin through the integrated observatory network. Agricultural and Forest Meteorology. 2020; 290 ():108010.
Chicago/Turabian StyleZiwei Xu; Shaomin Liu; Zhongli Zhu; Ji Zhou; Wenjiao Shi; Tongren Xu; Xiaofan Yang; Yuan Zhang; Xinlei He. 2020. "Exploring evapotranspiration changes in a typical endorheic basin through the integrated observatory network." Agricultural and Forest Meteorology 290, no. : 108010.
This study investigated the feasibility of partitioning the available energy between sensible (H) and latent (LE) heat fluxes via variational assimilation of reference-level air temperature and specific humidity. For this purpose, sequences of reference-level air temperature and specific humidity were assimilated into an atmospheric boundary layer model (ABL) within a variational data assimilation (VDA) framework to estimate H and LE. The VDA approach was tested at six sites (namely, Arou, Audubon, Bondville, Brookings, Desert, and Willow Creek) with contrasting climatic and vegetative conditions. The unknowns of the VDA system were the neutral bulk heat transfer coefficient (CHN) and evaporative fraction (EF). EF estimates were found to agree well with observations in terms of magnitude and day-to-day fluctuations in wet/densely vegetated sites but degraded in dry/sparsely vegetated sites. Similarly, in wet/densely vegetated sites, the variations in the CHN estimates were found to be consistent with those of the leaf area index (LAI) while this consistency deteriorated in dry/sparely vegetated sites. The root mean square errors (RMSEs) of daily H and LE estimates at the Arou site (wet) were 25.43 (Wm−2) and 55.81 (Wm−2), which are respectively 57.6% and 45.4% smaller than those of 60.00 (Wm−2) and 102.21 (Wm−2) at the Desert site (dry). Overall, the results show that the VDA system performs well at wet/densely vegetated sites (e.g., Arou and Willow Creek), but its performance degrades at dry/slightly vegetated sites (e.g., Desert and Audubon). These outcomes show that the sequences of reference-level air temperature and specific humidity have more information on the partitioning of available energy between the sensible and latent heat fluxes in wet/densely vegetated sites than dry/slightly vegetated sites.
Elahe Tajfar; Sayed M. Bateni; Essam Heggy; Tongren Xu. Feasibility of Estimating Turbulent Heat Fluxes via Variational Assimilation of Reference-Level Air Temperature and Specific Humidity Observations. Remote Sensing 2020, 12, 1065 .
AMA StyleElahe Tajfar, Sayed M. Bateni, Essam Heggy, Tongren Xu. Feasibility of Estimating Turbulent Heat Fluxes via Variational Assimilation of Reference-Level Air Temperature and Specific Humidity Observations. Remote Sensing. 2020; 12 (7):1065.
Chicago/Turabian StyleElahe Tajfar; Sayed M. Bateni; Essam Heggy; Tongren Xu. 2020. "Feasibility of Estimating Turbulent Heat Fluxes via Variational Assimilation of Reference-Level Air Temperature and Specific Humidity Observations." Remote Sensing 12, no. 7: 1065.
In this study, a Bayesian-based three-cornered hat (BTCH) method is developed to improve the estimation of terrestrial evapotranspiration (ET) by integrating multisource ET products without using any a priori knowledge. Ten long-term (30 years) gridded ET datasets from statistical or empirical, remotely-sensed, and land surface models over contiguous United States (CONUS) are integrated by the BTCH and ensemble mean (EM) methods. ET observations from eddy covariance towers (ETEC) at AmeriFlux sites and ET values from the water balance method (ETWB) are used to evaluate the BTCH- and EM-integrated ET estimates. Results indicate that BTCH performs better than EM and all the individual parent products. Moreover, the trend of BTCH-integrated ET estimates, and their influential factors (e.g., air temperature, normalized differential vegetation index, and precipitation) from 1982 to 2011 are analyzed by the Mann–Kendall method. Finally, the 30-year (1982 to 2011) total water storage anomaly (TWSA) in the Mississippi River Basin (MRB) is retrieved based on the BTCH-integrated ET estimates. The TWSA retrievals in this study agree well with those from the Gravity Recovery and Climate Experiment (GRACE).
Xinlei He; Tongren Xu; Youlong Xia; Sayed M. Bateni; Zhixia Guo; Shaomin Liu; Kebiao Mao; Yuan Zhang; Huaize Feng; Jingxue Zhao. A Bayesian Three-Cornered Hat (BTCH) Method: Improving the Terrestrial Evapotranspiration Estimation. Remote Sensing 2020, 12, 878 .
AMA StyleXinlei He, Tongren Xu, Youlong Xia, Sayed M. Bateni, Zhixia Guo, Shaomin Liu, Kebiao Mao, Yuan Zhang, Huaize Feng, Jingxue Zhao. A Bayesian Three-Cornered Hat (BTCH) Method: Improving the Terrestrial Evapotranspiration Estimation. Remote Sensing. 2020; 12 (5):878.
Chicago/Turabian StyleXinlei He; Tongren Xu; Youlong Xia; Sayed M. Bateni; Zhixia Guo; Shaomin Liu; Kebiao Mao; Yuan Zhang; Huaize Feng; Jingxue Zhao. 2020. "A Bayesian Three-Cornered Hat (BTCH) Method: Improving the Terrestrial Evapotranspiration Estimation." Remote Sensing 12, no. 5: 878.
Recently, a number of studies estimated evapotranspiration (ET) via variational assimilation of land surface temperature (LST) data from Moderate Resolution Imaging Spectroradiometer (MODIS). Their unknown parameters are neutral bulk heat transfer coefficient (CHN) (that scales the sum of sensible and latent heat fluxes), and evaporative fraction (EF) (that represents the partitioning of available energy between sensible and latent heat fluxes). The variational data assimilation (VDA) approaches estimate CHN and EF by minimizing the difference between the MODIS LST observations and model estimates. The applicability of these studies is limited only to clear-sky conditions where MODIS LST data are available. Even when the sky is clear, they cannot robustly update the initial guess of EF (i.e., the a priori EF value) because of the low temporal resolution of MODIS LST data. This study overcomes these shortcomings by 1) using the random forest (RF) method to obtain a reasonable the a priori EF value, and 2) assimilating the all-weather LST data (which are obtained by merging thermal infrared and passive microwave observations) into the VDA approach. The VDA approach is applied to the Source Regions of Rivers (SRR) in southwest China with heavy cloud covers. Results show that the RF method obtains a reasonably accurate the a priori EF value. Compared to assimilating the MODIS LST product, assimilation of all-weather LST data lead to an improvement in the ET estimates, especially in regions with dense clouds. Comparison of ET estimates with the measurements at four sites (i.e., Dangxiong, Linzhi, Naqu, and Qomolangma) in the SRR shows that the VDA approach can accurately estimate ET in cloudy conditions. Finally, the three-cornered hat (TCH) method is employed to assess the relative uncertainty of ET estimates over the SRR.
Xinlei He; Tongren Xu; Sayed M. Bateni; Michael Ek; Shaomin Liu; Fei Chen. Mapping regional evapotranspiration in cloudy skies via variational assimilation of all-weather land surface temperature observations. Journal of Hydrology 2020, 585, 124790 .
AMA StyleXinlei He, Tongren Xu, Sayed M. Bateni, Michael Ek, Shaomin Liu, Fei Chen. Mapping regional evapotranspiration in cloudy skies via variational assimilation of all-weather land surface temperature observations. Journal of Hydrology. 2020; 585 ():124790.
Chicago/Turabian StyleXinlei He; Tongren Xu; Sayed M. Bateni; Michael Ek; Shaomin Liu; Fei Chen. 2020. "Mapping regional evapotranspiration in cloudy skies via variational assimilation of all-weather land surface temperature observations." Journal of Hydrology 585, no. : 124790.
It is very important to understand the temporal and spatial variations of land surface temperature (LST) in Africa to determine the effects of temperature on agricultural production. Although thermal infrared remote sensing technology can quickly obtain surface temperature information, it is greatly affected by clouds and rainfall. To obtain a complete and continuous dataset on the spatiotemporal variations in LST in Africa, a reconstruction model based on the moderate resolution imaging spectroradiometer (MODIS) LST time series and ground station data was built to refactor the LST dataset (2003–2017). The first step in the reconstruction model is to filter low-quality LST pixels contaminated by clouds and then fill the pixels using observation data from ground weather stations. Then, the missing pixels are interpolated using the inverse distance weighting (IDW) method. The evaluation shows that the accuracy between reconstructed LST and ground station data is high (root mean square er–ror (RMSE) = 0.84 °C, mean absolute error (MAE) = 0.75 °C and correlation coefficient (R) = 0.91). The spatiotemporal analysis of the LST indicates that the change in the annual average LST from 2003–2017 was weak and the warming trend in Africa was remarkably uneven. Geographically, “the warming is more pronounced in the north and the west than in the south and the east”. The most significant warming occurred near the equatorial region in South Africa (slope > 0.05, R > 0.61, p < 0.05) and the central (slope = 0.08, R = 0.89, p < 0.05) regions, and a nonsignificant decreasing trend occurred in Botswana. Additionally, the mid-north region (north of Chad, north of Niger and south of Algeria) became colder (slope > −0.07, R = 0.9, p < 0.05), with a nonsignificant trend. Seasonally, significant warming was more pronounced in winter, mostly in the west, especially in Mauritania (slope > 0.09, R > 0.9, p < 0.5). The response of the different types of surface to the surface temperature has shown variability at different times, which provides important information to understand the effects of temperature changes on crop yields, which is critical for the planning of agricultural farming systems in Africa.
Nusseiba NourEldeen; Kebiao Mao; Zijin Yuan; Xinyi Shen; Tongren Xu; Zhihao Qin. Analysis of the Spatiotemporal Change in Land Surface Temperature for a Long-Term Sequence in Africa (2003–2017). Remote Sensing 2020, 12, 488 .
AMA StyleNusseiba NourEldeen, Kebiao Mao, Zijin Yuan, Xinyi Shen, Tongren Xu, Zhihao Qin. Analysis of the Spatiotemporal Change in Land Surface Temperature for a Long-Term Sequence in Africa (2003–2017). Remote Sensing. 2020; 12 (3):488.
Chicago/Turabian StyleNusseiba NourEldeen; Kebiao Mao; Zijin Yuan; Xinyi Shen; Tongren Xu; Zhihao Qin. 2020. "Analysis of the Spatiotemporal Change in Land Surface Temperature for a Long-Term Sequence in Africa (2003–2017)." Remote Sensing 12, no. 3: 488.
The retrieval of canopy and soil component temperatures for estimating evapotranspiration in the two source energy balance (TSEB) model depends on a relatively accurate partitioning of soil/substrate evaporation and canopy transpiration along with the soil and vegetation temperature components. To avoid the need for a Priestley-Taylor based transpiration formulation, this study applies the TSEB model using radiometric land surface temperature observations at multiple view angles from an airborne sensor for estimating soil and canopy temperatures directly. This direct partitioning between soil and canopy temperatures applied with the TSEB formulation improved the agreement between observed and modeled surface heat fluxes, reducing mean absolute percentage error (MAPE) in latent heat fluxes (LE) with flux tower observations from nearly 20% using the original Priestley-Taylor based TSEB model (TSEB-PT) to 15% using TSEB with thermal infrared observations from two substantially different view angles (TSEB-2AG) to nearly 5% using multiple (~6) view angles (TSEB-6AG). Moreover, TSEB-6AG is shown to compute physically realistic spatially-distributed LE for a range of vegetation cover and environmental conditions over the imaged domain. Values of MAPE for sensible heat (H) tended to be larger for all three models due to the fact that tower measurements tended to be located in well irrigated and densely vegetated sites having relatively low H values. This increased accuracy of soil and vegetation component temperature separation using multiangle radiometric temperature observations is useful for evaluating the utility of single and dual view angle thermal radiometer measurements currently available for applying the TSEB model.
Lisheng Song; Zunjian Bian; William P. Kustas; Shaomin Liu; Qing Xiao; Hector Nieto; Ziwei Xu; Yang Yang; Tongren Xu; Xujun Han. Estimation of surface heat fluxes using multi-angular observations of radiative surface temperature. Remote Sensing of Environment 2020, 239, 111674 .
AMA StyleLisheng Song, Zunjian Bian, William P. Kustas, Shaomin Liu, Qing Xiao, Hector Nieto, Ziwei Xu, Yang Yang, Tongren Xu, Xujun Han. Estimation of surface heat fluxes using multi-angular observations of radiative surface temperature. Remote Sensing of Environment. 2020; 239 ():111674.
Chicago/Turabian StyleLisheng Song; Zunjian Bian; William P. Kustas; Shaomin Liu; Qing Xiao; Hector Nieto; Ziwei Xu; Yang Yang; Tongren Xu; Xujun Han. 2020. "Estimation of surface heat fluxes using multi-angular observations of radiative surface temperature." Remote Sensing of Environment 239, no. : 111674.
Water use efficiency (WUE) measures the tradeoff between carbon uptake and water consumption in terrestrial ecosystems. It remains unclear how the responses of WUE to drought vary with drought severity. We assessed the spatio-temporal variations of ecosystem WUE and its responses to drought for terrestrial ecosystems in Southwest China over the period 2000–2017. The annual WUE values varied with vegetation type in the region: Forests (3.25 gC kg−1H2O) > shrublands (2.00 gC kg−1H2O) > croplands (1.76 gC kg−1H2O) > grasslands (1.04 gC kg−1H2O). During the period 2000–2017, frequent droughts occurred in Southwest China, and overall, drought had an enhancement effect on WUE. However, the effects of drought on WUE varied with vegetation type and drought severity. Croplands were the most sensitive to drought, and slight water deficiency led to the decline of cropland WUE. Over grasslands, mild drought increased its WUE while moderate and severe drought reduced its WUE. For forests and shrublands, mild and moderate drought increased their WUE, and only severe drought reduce their WUE, indicating that these ecosystems had stronger resistance to drought. Assessing the patterns and trends of ecosystem WUE and its responses to drought are essential for understanding plant water use strategy and informing ecosystem water management.
Jingxue Zhao; Tongren Xu; Jingfeng Xiao; Shaomin Liu; Kebiao Mao; Lisheng Song; Yunjun Yao; Xinlei He; Huaize Feng. Responses of Water Use Efficiency to Drought in Southwest China. Remote Sensing 2020, 12, 199 .
AMA StyleJingxue Zhao, Tongren Xu, Jingfeng Xiao, Shaomin Liu, Kebiao Mao, Lisheng Song, Yunjun Yao, Xinlei He, Huaize Feng. Responses of Water Use Efficiency to Drought in Southwest China. Remote Sensing. 2020; 12 (1):199.
Chicago/Turabian StyleJingxue Zhao; Tongren Xu; Jingfeng Xiao; Shaomin Liu; Kebiao Mao; Lisheng Song; Yunjun Yao; Xinlei He; Huaize Feng. 2020. "Responses of Water Use Efficiency to Drought in Southwest China." Remote Sensing 12, no. 1: 199.
Estimation of turbulent heat fluxes via variational data assimilation (VDA) approaches has been the subject of several studies. The VDA approaches need an adjoint model that is difficult to derive. In this study, remotely sensed land surface temperature (LST) data from Moderate Resolution Imaging Spectroradiometer (MODIS) are assimilated into the heat diffusion equation within an ensemble Kalman smoother (EnKS) approach to estimate turbulent heat fluxes. The EnKS approach is tested in the Heihe River Basin (HRB) in northwest China. The results show that the EnKS approach can estimate turbulent heat fluxes by assimilating low temporal resolution LST data from MODIS. The findings indicate that the EnKS approach perform fairly well in various hydrological and vegetative conditions. The estimated sensible (H) and latent (LE) heat fluxes are compared with the corresponding observations from large aperture scintillometer systems (LAS) at three sites (namely, Arou, Daman, and Sidaoqiao) in the HRB. The turbulent heat flux estimates from EnKS agree reasonably well with the observations, and are comparable to those of the VDA approach. The EnKS approach also provides statistical information on the H and LE estimates. It is found that the uncertainties of H and LE estimates are higher over wet and/or densely vegetated areas (grassland and forest) compared to the dry and/or slightly vegetated areas (cropland, shrubland, and barren land).
Xinlei He; Tongren Xu; Sayed M. Bateni; Christopher M.U. Neale; Shaomin Liu; Thomas Auligne; Kaicun Wang; Shoudong Zhu. Mapping Regional Turbulent Heat Fluxes via Assimilation of MODIS Land Surface Temperature Data into an Ensemble Kalman Smoother Framework. Earth and Space Science 2019, 6, 2423 -2442.
AMA StyleXinlei He, Tongren Xu, Sayed M. Bateni, Christopher M.U. Neale, Shaomin Liu, Thomas Auligne, Kaicun Wang, Shoudong Zhu. Mapping Regional Turbulent Heat Fluxes via Assimilation of MODIS Land Surface Temperature Data into an Ensemble Kalman Smoother Framework. Earth and Space Science. 2019; 6 (12):2423-2442.
Chicago/Turabian StyleXinlei He; Tongren Xu; Sayed M. Bateni; Christopher M.U. Neale; Shaomin Liu; Thomas Auligne; Kaicun Wang; Shoudong Zhu. 2019. "Mapping Regional Turbulent Heat Fluxes via Assimilation of MODIS Land Surface Temperature Data into an Ensemble Kalman Smoother Framework." Earth and Space Science 6, no. 12: 2423-2442.
Satellite-derived terrestrial latent heat flux (LE) models are useful tools to understand regional surface energy and water cycle processes for terrestrial ecosystems in the Heihe River basin (HRB) of Northwest China. This study developed a satellite-derived hybrid LE model parameterized by three soil moisture (SM) constraints: SM, relative humidity (RH), and diurnal air temperature range (DT); and assessed model performance and sensitivity. We used MODerate Resolution Imaging Spectroradiometer (MODIS) and eddy covariance (EC) data from 12 EC flux tower sites across the HRB. The hybrid model was trained using observed LE over 2012/2013–2014, and validated using observed LE for 2015 and leave-one-out cross-validation. The results show that the three SM constraints schemes exhibited some modeling differences at the flux tower site scale. LE estimation using SM achieved the highest correlation (R2 = 0.87, p < 0.01) and lowest root mean square error (RMSE = 20.1 W/m2) compared to schemes using RH or DT schemes. We then produced regional daily LE maps at 1 km × 1 km across the HRB for 2013–2015. Regional analysis shows that our LE estimates from all three constraint models exhibited large spatial variability and strong seasonal and annual variations, attributed to differences in parameterizing the model water constraints. This study provides data and model based evidence to improve satellite-derived hybrid LE models with regard to water constraints.
Yunjun Yao; Yuhu Zhang; Qiang Liu; Shaomin Liu; Kun Jia; Xiaotong Zhang; Ziwei Xu; Tongren Xu; Jiquan Chen; Joshua B. Fisher. Evaluation of a satellite-derived model parameterized by three soil moisture constraints to estimate terrestrial latent heat flux in the Heihe River basin of Northwest China. Science of The Total Environment 2019, 695, 133787 .
AMA StyleYunjun Yao, Yuhu Zhang, Qiang Liu, Shaomin Liu, Kun Jia, Xiaotong Zhang, Ziwei Xu, Tongren Xu, Jiquan Chen, Joshua B. Fisher. Evaluation of a satellite-derived model parameterized by three soil moisture constraints to estimate terrestrial latent heat flux in the Heihe River basin of Northwest China. Science of The Total Environment. 2019; 695 ():133787.
Chicago/Turabian StyleYunjun Yao; Yuhu Zhang; Qiang Liu; Shaomin Liu; Kun Jia; Xiaotong Zhang; Ziwei Xu; Tongren Xu; Jiquan Chen; Joshua B. Fisher. 2019. "Evaluation of a satellite-derived model parameterized by three soil moisture constraints to estimate terrestrial latent heat flux in the Heihe River basin of Northwest China." Science of The Total Environment 695, no. : 133787.
Terrestrial biophysical variables play an essential role in quantifying the amount of energy budget, water cycle, and carbon sink over the Three-River Headwaters Region of China (TRHR). However, direct field observations are missing in this region, and few studies have focused on the long-term spatiotemporal variations of terrestrial biophysical variables. In this study, we evaluated the spatiotemporal dynamics of biophysical variables including meteorological variables, vegetation, and evapotranspiration (ET) over the TRHR, and analyzed the response of vegetation and ET to climate change in the period from 1982 to 2015. The main input gridded datasets included meteorological reanalysis data, a satellite-based vegetation index dataset, and the ET product developed by a process-based Priestley–Taylor algorithm. Our results illustrate that: (1) The air temperature and precipitation over the TRHR increased by 0.597 °C and 41.1 mm per decade, respectively, while the relative humidity and surface downward shortwave radiation declined at a rate of 0.9% and 1.8 W/m2 per decade during the period 1982–2015, respectively. We also found that a ‘dryer warming’ tendency and a ‘wetter warming’ tendency existed in different areas of the TRHR. (2) Due to the predominant ‘wetter warming’ tendency characterized by the increasing temperature and precipitation, more than 56.8% of areas in the TRHR presented a significant increment in vegetation (0.0051/decade, p < 0.05), particularly in the northern and western meadow areas. When energy was the limiting factor for vegetation growth, temperature was a considerably more important driving factor than precipitation. (3) The annual ET of the TRHR increased by 3.34 mm/decade (p < 0.05) with an annual mean of 230.23 mm/year. More importantly, our analysis noted that ET was governed by terrestrial water supply, e.g., soil moisture and precipitation in the arid region of the western TRHR. By contrast, atmospheric evaporative demand derived by temperature and relative humidity was the primary controlling factor over the humid region of the southeastern TRHR. It was noted that land management activities, e.g., irrigation, also had a nonnegligible impact on the temporal and spatial variation of ET.
Xiangyi Bei; Yunjun Yao; Lilin Zhang; Tongren Xu; Kun Jia; Xiaotong Zhang; Ke Shang; Jia Xu; Xiaowei Chen. Long-Term Spatiotemporal Dynamics of Terrestrial Biophysical Variables in the Three-River Headwaters Region of China from Satellite and Meteorological Datasets. Remote Sensing 2019, 11, 1633 .
AMA StyleXiangyi Bei, Yunjun Yao, Lilin Zhang, Tongren Xu, Kun Jia, Xiaotong Zhang, Ke Shang, Jia Xu, Xiaowei Chen. Long-Term Spatiotemporal Dynamics of Terrestrial Biophysical Variables in the Three-River Headwaters Region of China from Satellite and Meteorological Datasets. Remote Sensing. 2019; 11 (14):1633.
Chicago/Turabian StyleXiangyi Bei; Yunjun Yao; Lilin Zhang; Tongren Xu; Kun Jia; Xiaotong Zhang; Ke Shang; Jia Xu; Xiaowei Chen. 2019. "Long-Term Spatiotemporal Dynamics of Terrestrial Biophysical Variables in the Three-River Headwaters Region of China from Satellite and Meteorological Datasets." Remote Sensing 11, no. 14: 1633.
Jinan City is the first pilot city for the construction of a hydroecological civilisation in China. Fifty-eight representative river sampling stations were selected through field trips and surveys, and fish were sampled in the spring, summer, and autumn of 2015. An index of fish biological integrity in Jinan City was constructed and to evaluate the hydroecological health of rivers. Canonical correlation analysis was used to select key driving factors that affect the health of the fish community. The results show that the key physical factor affecting water quality was turbidity, the key chemical factor affecting water quality was chemical oxygen demand (COD) and the key hydrological factor affecting water quality was discharge. Of all the driving factors, COD had the greatest effect on the health of the fish community, followed by discharge and turbidity. Macropodus chinensis Bloch was sensitive to changes in COD; Saurogobio dumerili Bleeker and Pseudolaubuca engraulis Nichols were sensitive to the hydrological factors of discharge and flow velocity; and Saurogobio gymnocheilus Lo and Squaliobarbus ourriculus Richardson were sensitive only to discharge. COD and discharge had a strong effect on fish survival, whereas turbidity affected fish survival but was not a major factor affecting the spatial distribution of river health. The findings can provide a reference for aquatic ecological rehabilitation in developing countries.
C. S. Zhao; Y. Yang; S. Yang; Y. Gai; C. Zhang; H. Zhang; T. Xu; X. Yin; Z. Zhang. Factors driving temporospatial heterogeneity of fish community health in Jinan City, China. Marine and Freshwater Research 2019, 70, 637 .
AMA StyleC. S. Zhao, Y. Yang, S. Yang, Y. Gai, C. Zhang, H. Zhang, T. Xu, X. Yin, Z. Zhang. Factors driving temporospatial heterogeneity of fish community health in Jinan City, China. Marine and Freshwater Research. 2019; 70 (5):637.
Chicago/Turabian StyleC. S. Zhao; Y. Yang; S. Yang; Y. Gai; C. Zhang; H. Zhang; T. Xu; X. Yin; Z. Zhang. 2019. "Factors driving temporospatial heterogeneity of fish community health in Jinan City, China." Marine and Freshwater Research 70, no. 5: 637.
Research on land surface processes at the catchment scale has drawn much attention over the past few decades, and a number of watershed observatories have been established worldwide. The Heihe River Basin (HRB), which contains the second largest inland river in China, is an ideal natural field experimental area for investigation of land surface processes involving diverse landscapes and the coexistence of cold and arid regions. The Heihe Integrated Observatory Network was established in 2007. For long-term observations, a hydrometeorological observatory, ecohydrological wireless sensor network, and satellite remote sensing are now in operation. In 2012, a multiscale observation experiment on evapotranspiration over heterogeneous land surfaces was conducted in the midstream region of the HRB, which included a flux observation matrix, wireless sensor network, airborne remote sensing, and synchronized ground measurements. Under an open data policy, the datasets have been publicly released following careful data processing and quality control. The outcomes highlight the integrated research on land surface processes in the HRB and include observed trends, scaling methods, high spatiotemporal resolution remote sensing products, and model–data integration in the HRB, all of which are helpful to other endorheic basins in the “Silk Road Economic Belt.” Henceforth, the goal of the Heihe Integrated Observatory Network is to develop an intelligent monitoring system that incorporates ground-based observatory networks, unmanned aerial vehicles, and multi-source satellites through the Internet of Things technology. Furthermore, biogeochemical processes observation will be improved, and the study of integrating ground observations, remote sensing, and large-scale models will be promoted further. Copyright © 2018. . Copyright © by the Soil Science Society of America, Inc.
Shaomin Liu; Xin Li; Ziwei Xu; Tao Che; Qing Xiao; Mingguo Ma; Qinhuo Liu; Rui Jin; Jianwen Guo; Liangxu Wang; Weizhen Wang; Yuan Qi; Hongyi Li; Tongren Xu; Youhua Ran; Xiaoli Hu; ShengJin Shi; Zhongli Zhu; Junlei Tan; Yang Zhang; Zhiguo Ren. The Heihe Integrated Observatory Network: A Basin-Scale Land Surface Processes Observatory in China. Vadose Zone Journal 2018, 17, 180072 .
AMA StyleShaomin Liu, Xin Li, Ziwei Xu, Tao Che, Qing Xiao, Mingguo Ma, Qinhuo Liu, Rui Jin, Jianwen Guo, Liangxu Wang, Weizhen Wang, Yuan Qi, Hongyi Li, Tongren Xu, Youhua Ran, Xiaoli Hu, ShengJin Shi, Zhongli Zhu, Junlei Tan, Yang Zhang, Zhiguo Ren. The Heihe Integrated Observatory Network: A Basin-Scale Land Surface Processes Observatory in China. Vadose Zone Journal. 2018; 17 (1):180072.
Chicago/Turabian StyleShaomin Liu; Xin Li; Ziwei Xu; Tao Che; Qing Xiao; Mingguo Ma; Qinhuo Liu; Rui Jin; Jianwen Guo; Liangxu Wang; Weizhen Wang; Yuan Qi; Hongyi Li; Tongren Xu; Youhua Ran; Xiaoli Hu; ShengJin Shi; Zhongli Zhu; Junlei Tan; Yang Zhang; Zhiguo Ren. 2018. "The Heihe Integrated Observatory Network: A Basin-Scale Land Surface Processes Observatory in China." Vadose Zone Journal 17, no. 1: 180072.
A number of studies have estimated turbulent heat fluxes by assimilating sequences of land surface temperature (LST) observations into the strong constraint-variational data assimilation (SC-VDA) approaches. The SC-VDA approaches do not account for the structural model errors and uncertainties in the micrometeorological variables. In contrast to the SC-VDA approaches, the WC-VDA approach (the so-called weak constraint-VDA) accounts for the effects of structural and model errors by adding a model error term. In this study, the WC-VDA approach is tested at six study sites with different climatic and vegetative conditions. Its performance is also compared with that of SC-VDA at the six study sites. The results show that the WC-VDA produces 10.16% and 10.15% lower root mean square errors (RMSEs) for sensible and latent heat flux estimates compared with the SC-VDA approach. The model error term can capture errors in the turbulent heat flux estimates due to errors in LST and micrometeorological measurements, as well as structural model errors, and does not allow those errors to adversely affect the turbulent heat flux estimates. The findings also indicate that the estimated model error term varies reasonably well, so as to capture the misfit between predicted and observed net radiation in different hydrological and vegetative conditions. Finally, synthetically generated positive (negative) noises are added to the hydrological input variables (e.g., LST, air temperature, air humidity, incoming solar radiation, and wind speed) to examine whether the WC-VDA approach can capture those errors. It was found that the WC-VDA approach accounts for the errors in the input data and reduces their effect on the turbulent heat flux estimates.
Xinlei He; Tongren Xu; Sayed M. Bateni; Christopher M. U. Neale; Thomas Auligne; Shaomin Liu; Kaicun Wang; Kebiao Mao; Yunjun Yao. Evaluation of the Weak Constraint Data Assimilation Approach for Estimating Turbulent Heat Fluxes at Six Sites. Remote Sensing 2018, 10, 1994 .
AMA StyleXinlei He, Tongren Xu, Sayed M. Bateni, Christopher M. U. Neale, Thomas Auligne, Shaomin Liu, Kaicun Wang, Kebiao Mao, Yunjun Yao. Evaluation of the Weak Constraint Data Assimilation Approach for Estimating Turbulent Heat Fluxes at Six Sites. Remote Sensing. 2018; 10 (12):1994.
Chicago/Turabian StyleXinlei He; Tongren Xu; Sayed M. Bateni; Christopher M. U. Neale; Thomas Auligne; Shaomin Liu; Kaicun Wang; Kebiao Mao; Yunjun Yao. 2018. "Evaluation of the Weak Constraint Data Assimilation Approach for Estimating Turbulent Heat Fluxes at Six Sites." Remote Sensing 10, no. 12: 1994.
Estimation of turbulent heat fluxes by assimilating sequences of land surface temperature (LST) measurements into variational data assimilation (VDA) frameworks has been the subject of several studies. The VDA approaches estimate turbulent heat fluxes by minimizing the difference between LST observations and estimations from the heat diffusion equation. The VDA methods have been tested only with high temporal resolution LST observations (e.g., from geostationary satellites) when applied at regional scales. Geostationary satellites can capture the diurnal cycle of LST, but they have a relatively low spatial resolution and mainly focus on low latitudes. To overcome these shortcomings, this study assimilates high spatial resolution LST data from polar orbiting satellites (e.g., Moderate Resolution Imaging Spectroradiometer, MODIS) into the combined-source (CS) and dual-source (DS) VDA schemes. An expression is developed to obtain an a priori evaporative fraction (EF) estimate from leaf area index (LAI) or apparent thermal inertia (ATI). The a priori EF estimate is used as an initial guess in the VDA approach. The results indicate that the VDA method is able to find the optimal value of EF by assimilating the low-temporal resolution MODIS LST data. The predicted turbulent heat fluxes from VDA are compared with the measurements from the large-aperture scintillometer at three sites (Arou, Daman, and Sidaoqiao) in the Heihe River Basin (located in northwest China). The findings indicate that the CS and DS VDA models perform well in various hydrological and vegetative conditions. The three-site-average root mean square errors (RMSEs) of sensible and latent heat fluxes estimates from the CS scheme are 37.44 W m−2 and 94.30 W m−2, respectively. The DS model reduces the abovementioned RMSEs by 19.82% and 21.37%, respectively. Overall, the results show that using the a priori EF estimate from the proposed expression in the VDA approach eliminates the need for the high resolution LST data from geostationary satellites, and allows the VDA method to estimate turbulent heat fluxes by assimilating LST data from polar orbiting satellites. Finally, several numerical tests are conducted to assess the effect of LST temporal sampling on the turbulent heat fluxes estimates. The results show that the LST measurement at 1400 Local Time (LT) has the most amount of information for partitioning the available energy into sensible and latent heat fluxes.
Tongren Xu; Xinlei He; Sayed M. Bateni; Thomas Auligne; Shaomin Liu; Ziwei Xu; Ji Zhou; Kebiao Mao. Mapping regional turbulent heat fluxes via variational assimilation of land surface temperature data from polar orbiting satellites. Remote Sensing of Environment 2018, 221, 444 -461.
AMA StyleTongren Xu, Xinlei He, Sayed M. Bateni, Thomas Auligne, Shaomin Liu, Ziwei Xu, Ji Zhou, Kebiao Mao. Mapping regional turbulent heat fluxes via variational assimilation of land surface temperature data from polar orbiting satellites. Remote Sensing of Environment. 2018; 221 ():444-461.
Chicago/Turabian StyleTongren Xu; Xinlei He; Sayed M. Bateni; Thomas Auligne; Shaomin Liu; Ziwei Xu; Ji Zhou; Kebiao Mao. 2018. "Mapping regional turbulent heat fluxes via variational assimilation of land surface temperature data from polar orbiting satellites." Remote Sensing of Environment 221, no. : 444-461.