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Dr. Yanfei Ma
Handan College

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0 Fusing
0 Irrigation Management
0 Remote Sensing
0 Evapotranspiration
0 SEBS

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Journal article
Published: 09 April 2021 in Land
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Land surface evapotranspiration (ET) and gross primary productivity (GPP) are critical components in terrestrial ecosystems with water and carbon cycles. Large-scale, high-resolution, and accurately quantified ET and GPP values are important fundamental data for freshwater resource management and help in understanding terrestrial carbon and water cycles in an arid region. In this study, the revised surface energy balance system (SEBS) model and MOD17 GPP algorithm were used to estimate daily ET and GPP at 100 m resolution based on multi-source satellite remote sensing data to obtain surface biophysical parameters and meteorological forcing data as input variables for the model in the midstream oasis area of the Heihe River Basin (HRB) from 2010 to 2016. Then, we further calculated the ecosystem water-use efficiency (WUE). We validated the daily ET, GPP, and WUE from ground observations at a crop oasis station and conducted spatial intercomparisons of monthly and annual ET, GPP, and WUE at the irrigation district and cropland oasis scales. The site-level evaluation results show that ET and GPP had better performance than WUE at the daily time scale. Specifically, the deviations in the daily ET, GPP, and WUE data compared with ground observations were small, with a root mean square error (RMSE) and mean absolute percent error (MAPE) of 0.75 mm/day and 26.59%, 1.13 gC/m2 and 36.62%, and 0.50 gC/kgH2O and 39.83%, respectively. The regional annual ET, GPP, and WUE varied from 300 to 700 mm, 200 to 650 gC/m2, and 0.5 to 1.0 gC/kgH2O, respectively, over the entire irrigation oasis area. It was found that annual ET and GPP were greater than 550 mm and 500 gC/m2, and annual oasis cropland WUE had strong invariability and was maintained at approximately 0.85 gC/kgH2O. The spatial intercomparisons from 2010 to 2016 revealed that ET had similar spatial patterns to GPP due to tightly coupled carbon and water fluxes. However, the WUE spatiotemporal patterns were slightly different from both ET and GPP, particularly in the early and late growing seasons for the oasis area. Our results demonstrate that spatial full coverage and reasonably fine spatiotemporal variation and variability could significantly improve our understanding of water-saving irrigation strategies and oasis agricultural water management practices in the face of water shortage issues.

ACS Style

Junxia Yan; Yanfei Ma; Dongyun Zhang; Zechen Li; Weike Zhang; Zhenhua Wu; Hui Wang; Lihua Wen. High-Resolution Monitoring and Assessment of Evapotranspiration and Gross Primary Production Using Remote Sensing in a Typical Arid Region. Land 2021, 10, 396 .

AMA Style

Junxia Yan, Yanfei Ma, Dongyun Zhang, Zechen Li, Weike Zhang, Zhenhua Wu, Hui Wang, Lihua Wen. High-Resolution Monitoring and Assessment of Evapotranspiration and Gross Primary Production Using Remote Sensing in a Typical Arid Region. Land. 2021; 10 (4):396.

Chicago/Turabian Style

Junxia Yan; Yanfei Ma; Dongyun Zhang; Zechen Li; Weike Zhang; Zhenhua Wu; Hui Wang; Lihua Wen. 2021. "High-Resolution Monitoring and Assessment of Evapotranspiration and Gross Primary Production Using Remote Sensing in a Typical Arid Region." Land 10, no. 4: 396.

Journal article
Published: 13 March 2021 in Agricultural Water Management
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Potential evapotranspiration (PET) is an important consideration in the study of agricultural water management and climate change. Although a number of studies have already explored the effects of climate factors on changes in PET, the quantitative effects of various driving factors needs to be further studied, as most studies have not accounted for vegetation dynamics by characterizing changes in leaf area and stomatal resistance. Here, we used the Shuttleworth–Wallace (S-W) model based on climate, vegetation, and energy factors to quantitatively analyze the effects of various driving factors at multiple spatial scales over the main grain-producing area of China (MGPAC) from 1982 to 2016. The S-W model had a satisfactory performance because S-W based Standardized Precipitation Evapotranspiration Index (SPEI) had a higher determination coefficient (0.33 VS. 0.26) than Penman-Monteith based SPEI for soil moisture standardized anomaly over MGPAC. MGPAC had a mean annual PET of 926.20 mm and showed a marked increase of 3.844 mm yr−1 during the study period. Evergreen broadleaf forest and grassland had the highest and lowest annual average PET values (1535.65 mm and 633.67 mm), respectively. Although climate factors could directly explain 79.42% of the PET increase over the MGPAC, vegetation dynamics were also identified to be a non-negligible factor explaining the increase in PET (directly explaining 18.91% of the PET trend). Specifically, vegetation dynamics contributed to explaining 67.30% and 48.91% of the PET trend in the Huang-Huai-Hai and Loess Plateau regions. These findings are closely related to changes in the temperature and leaf area index (LAI), which notably increased by 0.04 °C yr−1 (P < 0.01) and 0.0038 m2 m−2 yr−1 (P < 0.01), respectively. Regarding single drivers, variation in temperature and LAI significantly increased the PET by 3.582 mm yr−1 (P < 0.01) and 1.127 mm yr−1 (P < 0.01) across the MGPAC, respectively. This study can provide a new insight to improve agricultural production and management in China.

ACS Style

Haigen Zhao; Yanfei Ma. Effects of various driving factors on potential evapotranspiration trends over the main grain-production area of China while accounting for vegetation dynamics. Agricultural Water Management 2021, 250, 106854 .

AMA Style

Haigen Zhao, Yanfei Ma. Effects of various driving factors on potential evapotranspiration trends over the main grain-production area of China while accounting for vegetation dynamics. Agricultural Water Management. 2021; 250 ():106854.

Chicago/Turabian Style

Haigen Zhao; Yanfei Ma. 2021. "Effects of various driving factors on potential evapotranspiration trends over the main grain-production area of China while accounting for vegetation dynamics." Agricultural Water Management 250, no. : 106854.

Preprint content
Published: 23 March 2020
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Accurate estimation of surface evapotranspiration (ET) with high quality and fine spatiotemporal resolution is one of the biggest obstacles for routine applications of remote sensing in eco-hydrological studies and water resource management at basin scale. Integrating multi-source remote sensing data is one of the main ideas for many scholars to obtain synthesized frequent high spatial resolution surface ET. This study was based on the theoretically robust surface energy balance system (SEBS) model, which the model mechanism needs further investigation, including the applicability and the influencing factors, such as local environment, heterogeneity of the landscape, and optimized parametric scheme, for improving estimation accuracy. In addition, due to technical and budget limitations, so far, no single sensor provides both high spatial resolution and high temporal resolution. Optical remote sensing data is missing due to frequent cloud contamination and other poor atmospheric conditions. The passive microwave (PW) remote sensing has a better ability in overcoming the influences of clouds and rainy. The accurate "all-weather" ET estimation method had been proposed through blending multi-source remote sensing data acquired by optical, thermal infrared (TIR) and PW remote sensors on board polar satellite platforms. The estimation had been carried out for daily ET of the River Source Region in Southwest China, and then the "All-weather" remotely sensed ET results showed that the daily ET estimates had a mean absolute percent error (MAPE) of 36% and a root mean square error (RMSE) of 0.88 mm/day relative to ground measurements from 12 eddy covariance (EC) sites in the study area. The validation results indicated good accuracy using multi-source remote sensing data in cloudy and mountainous regions.

ACS Style

Yanfei Ma; Ji Zhou; Shaomin Liu. Monitoring of "All-weather" Evapotranspiration Using Multi-source Remote Sensing Imagery in Cloudy and Mountainous Regions in Southwest China. 2020, 1 .

AMA Style

Yanfei Ma, Ji Zhou, Shaomin Liu. Monitoring of "All-weather" Evapotranspiration Using Multi-source Remote Sensing Imagery in Cloudy and Mountainous Regions in Southwest China. . 2020; ():1.

Chicago/Turabian Style

Yanfei Ma; Ji Zhou; Shaomin Liu. 2020. "Monitoring of "All-weather" Evapotranspiration Using Multi-source Remote Sensing Imagery in Cloudy and Mountainous Regions in Southwest China." , no. : 1.

Journal article
Published: 26 August 2019 in Remote Sensing
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This study simultaneously analyzed and evaluated the meteorological drought-monitoring utility of the following four satellite-based, quantitative precipitation estimation (QPE) products: the Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis 3B43V7 (TRMM-3B43), the Climate Hazards Group InfraRed Precipitation with Station (CHIRPS), the Climate Prediction Center Morphing Technique gauge-satellite blended product (CMORPH-BLD), and the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR). Data from 2000 to 2016 was used at global scale. The global Climate Research Unit (CRU) Version 4.02 was used as reference data to assess QPE products. The Standardized Precipitation Evapotranspiration Index (SPEI) drought index was chosen as an example to evaluate the drought utility of four QPE products. The results indicate that CHIRPS has the best performance in Europe, Oceania, and Africa; the PERSIANN-CDR has the best performance in North America, South America, and Asia; the CMORPH-BLD has the worst statistical indices in all continents. Although four QPE products showed satisfactory performance for most of the world according to SPEI statistics, poor drought monitoring ability occurred in Southeast Asia, Central Africa, the Tibetan plateau, the Himalayas, and Amazonia. The PERSIANN-CDR achieves the best performance of the four QPE products in most regions except for Africa; CHIRPS and TRMM-3B43 have comparable performances. According to the spatial probability of detection (POD) and false alarm ratio (FAR) of the SPEI, more than 50% of all drought events cannot be accurately identified by QPE products in regions with sparse gauge distribution. In other regions, such as the southeastern USA, southeastern China, and South Africa, QPE products capture more than 75% of drought events. Temporally, all datasets (except for CMORPH-BLD) can detect all typical drought events, namely, in the southeastern US in 2007, western Europe in 2003, Kenya in 2006, and Central Asia in 2008. The study concludes that CHIRPS and TRMM-3B43 can be used as near-real-time drought monitoring techniques whereas PERSIANN-CDR might be more suitable for long-term historical drought analysis.

ACS Style

Haigen Zhao; Yanfei Ma. Evaluating the Drought-Monitoring Utility of Four Satellite-Based Quantitative Precipitation Estimation Products at Global Scale. Remote Sensing 2019, 11, 2010 .

AMA Style

Haigen Zhao, Yanfei Ma. Evaluating the Drought-Monitoring Utility of Four Satellite-Based Quantitative Precipitation Estimation Products at Global Scale. Remote Sensing. 2019; 11 (17):2010.

Chicago/Turabian Style

Haigen Zhao; Yanfei Ma. 2019. "Evaluating the Drought-Monitoring Utility of Four Satellite-Based Quantitative Precipitation Estimation Products at Global Scale." Remote Sensing 11, no. 17: 2010.

Journal article
Published: 27 August 2018 in Journal of Geophysical Research: Atmospheres
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Evapotranspiration (ET) is a vital variable for land‐atmosphere interactions that links surface energy balance, water and carbon cycles. The in‐situ techniques can measure ET accurately but the observations have limited spatial and temporal coverage. Modeling approaches have been used to estimate ET at broad spatial and temporal scales, while accurately simulating ET at regional scales remains a major challenge. In this study, we upscale ET from eddy covariance flux tower sites to the regional scale with machine learning algorithms. Five machine learning algorithms are employed for ET upscaling including artificial neural network (ANN), Cubist, deep belief network (DBN), random forest (RF), and support vector machine (SVM). The machine learning methods are trained and tested at 36 flux towers sites (65 site years) across the Heihe River Basin (HRB) and are then applied to estimate ET for each grid cell (1 km × 1 km) within the watershed and for each day over the period 2012‐2016. The ANN, Cubist, RF, and SVM algorithms have almost identical performance in estimating ET and have slightly lower root mean square error (RMSE) than DBN at the site scale. The RF algorithm has slightly lower relative uncertainty at the regional scale than other methods based on three cornered hat (TCH) method. Additionally, the machine learning methods perform better over densely vegetated conditions than barren land or sparsely vegetated conditions. The regional ET generated from the machine learning approaches captured the spatial and temporal patterns of ET at the regional scale.

ACS Style

Tongren Xu; Zhixia Guo; Shaomin Liu; Xinlei He; Yangfanyu Meng; Ziwei Xu; Youlong Xia; Jingfeng Xiao; Yuan Zhang; Yanfei Ma; Lisheng Song. Evaluating Different Machine Learning Methods for Upscaling Evapotranspiration from Flux Towers to the Regional Scale. Journal of Geophysical Research: Atmospheres 2018, 123, 8674 -8690.

AMA Style

Tongren Xu, Zhixia Guo, Shaomin Liu, Xinlei He, Yangfanyu Meng, Ziwei Xu, Youlong Xia, Jingfeng Xiao, Yuan Zhang, Yanfei Ma, Lisheng Song. Evaluating Different Machine Learning Methods for Upscaling Evapotranspiration from Flux Towers to the Regional Scale. Journal of Geophysical Research: Atmospheres. 2018; 123 (16):8674-8690.

Chicago/Turabian Style

Tongren Xu; Zhixia Guo; Shaomin Liu; Xinlei He; Yangfanyu Meng; Ziwei Xu; Youlong Xia; Jingfeng Xiao; Yuan Zhang; Yanfei Ma; Lisheng Song. 2018. "Evaluating Different Machine Learning Methods for Upscaling Evapotranspiration from Flux Towers to the Regional Scale." Journal of Geophysical Research: Atmospheres 123, no. 16: 8674-8690.

Journal article
Published: 18 August 2018 in Journal of Geophysical Research: Atmospheres
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Oases are unique heterogeneous landscapes that coexist within the Gobi desert in the arid and semi‐arid regions, which are vital for agricultural production and economic development. The heterogeneity of the land surface with vegetation will significantly influence the wind dynamics and airflow characteristics. The current study utilized an integrated approach, combining the Computational Fluid Dynamics (CFD) method with the k ‐ ɛ turbulence model and high‐resolution ground‐measurement data to analyze the wind dynamics over an oasis. Specifically, 1) the Weather Research and Forecast model (WRF) data was used as boundary conditions to initiate the simulations; 2) the canopy Leaf Area Density (LAD) estimated from Airborne Laser Scanning (ALS) data was added as the source terms of the momentum and turbulence transport equations, which represented the highly heterogeneous vegetation structures in the oasis area. CFD‐simulated wind field results agreed well with the flux observation matrix data (17 tower measurements in a 5.5 km × 5.5 km experimental area). The spatial and temporal variations of wind fields affected by heterogeneous land surfaces were successfully captured. The CFD‐simulated wind fields also clearly showed the “wind shield effect” over highly heterogeneous land surfaces, wherein the existence of shorter and longer wind‐speed reduction areas at the windward and leeward sides of the shelterbelts contribute to protecting farmlands and orchards from wind erosion. In addition, the current approach of estimating aerodynamic roughness length (z0m) based on high‐resolution CFD‐simulated wind profiles was demonstrated to be a promising method of capturing wind dynamics over heterogeneous surfaces.

ACS Style

Rui Liu; Shaomin Liu; Xiaofan Yang; Hui Lu; Xiaoduo Pan; Ziwei Xu; Yanfei Ma; Tongren Xu. Wind Dynamics Over a Highly Heterogeneous Oasis Area: An Experimental and Numerical Study. Journal of Geophysical Research: Atmospheres 2018, 123, 8418 -8440.

AMA Style

Rui Liu, Shaomin Liu, Xiaofan Yang, Hui Lu, Xiaoduo Pan, Ziwei Xu, Yanfei Ma, Tongren Xu. Wind Dynamics Over a Highly Heterogeneous Oasis Area: An Experimental and Numerical Study. Journal of Geophysical Research: Atmospheres. 2018; 123 (16):8418-8440.

Chicago/Turabian Style

Rui Liu; Shaomin Liu; Xiaofan Yang; Hui Lu; Xiaoduo Pan; Ziwei Xu; Yanfei Ma; Tongren Xu. 2018. "Wind Dynamics Over a Highly Heterogeneous Oasis Area: An Experimental and Numerical Study." Journal of Geophysical Research: Atmospheres 123, no. 16: 8418-8440.

Journal article
Published: 14 August 2018 in Remote Sensing of Environment
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The estimation of land-surface evapotranspiration (ET) at high spatial and temporal resolutions is important for management and planning of agricultural water resources, but available remote sensing data generally have either high spatial resolution or high temporal resolution. To overcome this limitation, we evaluated the use of a data fusion scheme, Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM), to determine the surface parameters needed to estimate daily ET at a Landsat-like scale (100 m). In particular, we fused Moderate Resolution Imaging Spectroradiometer (MODIS) data with Landsat Enhanced Thematic Mapper Plus (ETM+) data in analysis of the Heihe River Basin (HRB), an arid region of Northwest China. The surface parameters were then used to drive the revised Surface Energy Balance System (SEBS) model to estimate daily ET at a spatial resolution of 100 m for this an arid irrigation area during the crop growth period (April to October) in 2012. The results showed that the daily ET estimates had a mean absolute percent error (MAPE) of 12% and a root mean square error (RMSE) of 0.81 mm/day relative to ground measurements from 18 eddy covariance (EC) sites in the study area. The validation results indicated good accuracy for land cover types of maize and vegetables, a slight overestimation for residential and wetland sites, and a slight underestimation for orchard site. Our comparison of the input parameter fusion approach (IPFA) and the ET fusion approach (ETFA) with field measurements indicated the IPFA was superior than the ETFA for land surfaces with high spatial heterogeneity. Furthermore, our high spatiotemporal ET estimates indicated that irrigation water efficiencies of the irrigation districts (mean: 70%) and villages (mean: 62%) had large spatial heterogeneity. These results point to the need for calculating ET at a high spatiotemporal resolution for monitoring and improving irrigation water efficiency at local scales. Our findings suggest that the proposed framework of estimating daily ET at a Landsat-like scale using multi-source data may also be applicable to other heterogeneous landscapes by providing a foundation for management of water resources at the basin or finer scales.

ACS Style

Yanfei Ma; Shaomin Liu; Lisheng Song; Ziwei Xu; Yaling Liu; Tongren Xu; Zhongli Zhu. Estimation of daily evapotranspiration and irrigation water efficiency at a Landsat-like scale for an arid irrigation area using multi-source remote sensing data. Remote Sensing of Environment 2018, 216, 715 -734.

AMA Style

Yanfei Ma, Shaomin Liu, Lisheng Song, Ziwei Xu, Yaling Liu, Tongren Xu, Zhongli Zhu. Estimation of daily evapotranspiration and irrigation water efficiency at a Landsat-like scale for an arid irrigation area using multi-source remote sensing data. Remote Sensing of Environment. 2018; 216 ():715-734.

Chicago/Turabian Style

Yanfei Ma; Shaomin Liu; Lisheng Song; Ziwei Xu; Yaling Liu; Tongren Xu; Zhongli Zhu. 2018. "Estimation of daily evapotranspiration and irrigation water efficiency at a Landsat-like scale for an arid irrigation area using multi-source remote sensing data." Remote Sensing of Environment 216, no. : 715-734.

Journal article
Published: 10 July 2018 in Journal of Geophysical Research: Atmospheres
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Land surface evapotranspiration (ET) is an important component of the surface energy budget and water cycle. To solve the problem of the spatial‐scale mismatch between in situ observations and remotely sensed ET, it is necessary to find the most appropriate upscaling approach for acquiring ground truth ET data at the satellite pixel scale. Based on a data set from two flux observation matrices in the middle stream and downstream of the Heihe River Basin, six upscaling methods were intercompared via direct validation and cross validation. The results showed that the area‐weighted method performed better than the other five upscaling methods introducing auxiliary variables (the integrated Priestley‐Taylor equation, weighted area‐to‐area regression kriging [WATARK], artificial neural network, random forest [RF], and deep belief network methods) over homogeneous underlying surfaces. Over moderately heterogeneous underlying surfaces, the WATARK method performed better. However, the RF method performed better over highly heterogeneous underlying surfaces. A combined method (using the area‐weighted and WATARK methods for homogeneous and moderately heterogeneous underlying surfaces, respectively, and using the RF method for highly heterogeneous underlying surfaces) was proposed to acquire the daily ground truth ET data at the satellite pixel scale, and the errors in the ground truth ET data were evaluated. The Dual Temperature Difference (DTD) and ETMonitor were validated using ground truth ET data, which solve the problem of the spatial‐scale mismatch and quantify uncertainties in the validation process.

ACS Style

Xiang Li; Shaomin Liu; Huaixiang Li; Yanfei Ma; Jianghao Wang; Yuan Zhang; Ziwei Xu; Tongren Xu; Lisheng Song; Xiaofan Yang; Zheng Lu; Zeyu Wang; Zhixia Guo. Intercomparison of Six Upscaling Evapotranspiration Methods: From Site to the Satellite Pixel. Journal of Geophysical Research: Atmospheres 2018, 123, 6777 -6803.

AMA Style

Xiang Li, Shaomin Liu, Huaixiang Li, Yanfei Ma, Jianghao Wang, Yuan Zhang, Ziwei Xu, Tongren Xu, Lisheng Song, Xiaofan Yang, Zheng Lu, Zeyu Wang, Zhixia Guo. Intercomparison of Six Upscaling Evapotranspiration Methods: From Site to the Satellite Pixel. Journal of Geophysical Research: Atmospheres. 2018; 123 (13):6777-6803.

Chicago/Turabian Style

Xiang Li; Shaomin Liu; Huaixiang Li; Yanfei Ma; Jianghao Wang; Yuan Zhang; Ziwei Xu; Tongren Xu; Lisheng Song; Xiaofan Yang; Zheng Lu; Zeyu Wang; Zhixia Guo. 2018. "Intercomparison of Six Upscaling Evapotranspiration Methods: From Site to the Satellite Pixel." Journal of Geophysical Research: Atmospheres 123, no. 13: 6777-6803.

Journal article
Published: 01 January 2017 in Journal of Applied Meteorology and Climatology
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A unique and intensive flux observation matrix was established during May to September of 2012 in an oasis–desert area located in the middle reaches of the Heihe River basin, China. The flux observation matrix included 22 eddy covariance systems belonging to the first thematic experiment of the Heihe Watershed Allied Telemetry Experimental Research (HiWATER) project. The energy balance closure ratio (EBR) was assessed and possible mechanisms were investigated using remote sensing data. The results showed that 1) the EBR was in the range of 0.78–1.04 at all sites with an average EBR of 0.92, and 2) the calculated daily EBR exhibited better performance than the 30-min averages. 3) The heat storage cannot be ignored during the crop growing season. An improvement of approximately 6% in the total closure was found after considering the heat storage terms (canopy and photosynthesis storage) in the energy budget at the maize surface, and the canopy and photosynthesis showed approximately equal contributions of 3% for each storage term. The results also showed that 4) the land heterogeneous surface had a significant effect on the EBR. The EBR decreased with land surface heterogeneity increasing (taking the standard deviation of the surface temperature in the eddy covariance system source area as an index). The EBR also decreased when irrigation occurred and increased after irrigation was completed. The advection or secondary circulation broke the closed system of the energy balance given the phenomenon of EBR increasing when the advection or secondary circulation occurred.

ACS Style

Ziwei Xu; Yanfei Ma; Shaomin Liu; Wenjiao Shi; Jiemin Wang. Assessment of the Energy Balance Closure under Advective Conditions and Its Impact Using Remote Sensing Data. Journal of Applied Meteorology and Climatology 2017, 56, 127 -140.

AMA Style

Ziwei Xu, Yanfei Ma, Shaomin Liu, Wenjiao Shi, Jiemin Wang. Assessment of the Energy Balance Closure under Advective Conditions and Its Impact Using Remote Sensing Data. Journal of Applied Meteorology and Climatology. 2017; 56 (1):127-140.

Chicago/Turabian Style

Ziwei Xu; Yanfei Ma; Shaomin Liu; Wenjiao Shi; Jiemin Wang. 2017. "Assessment of the Energy Balance Closure under Advective Conditions and Its Impact Using Remote Sensing Data." Journal of Applied Meteorology and Climatology 56, no. 1: 127-140.

Journal article
Published: 01 December 2016 in Agricultural and Forest Meteorology
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ACS Style

Shaomin Liu; Ziwei Xu; Lisheng Song; QianYi Zhao; Yong Ge; Tongren Xu; Yanfei Ma; Zhongli Zhu; Zhenzhen Jia; Fen Zhang. Upscaling evapotranspiration measurements from multi-site to the satellite pixel scale over heterogeneous land surfaces. Agricultural and Forest Meteorology 2016, 230-231, 97 -113.

AMA Style

Shaomin Liu, Ziwei Xu, Lisheng Song, QianYi Zhao, Yong Ge, Tongren Xu, Yanfei Ma, Zhongli Zhu, Zhenzhen Jia, Fen Zhang. Upscaling evapotranspiration measurements from multi-site to the satellite pixel scale over heterogeneous land surfaces. Agricultural and Forest Meteorology. 2016; 230-231 ():97-113.

Chicago/Turabian Style

Shaomin Liu; Ziwei Xu; Lisheng Song; QianYi Zhao; Yong Ge; Tongren Xu; Yanfei Ma; Zhongli Zhu; Zhenzhen Jia; Fen Zhang. 2016. "Upscaling evapotranspiration measurements from multi-site to the satellite pixel scale over heterogeneous land surfaces." Agricultural and Forest Meteorology 230-231, no. : 97-113.

Journal article
Published: 01 September 2016 in Journal of Hydrology
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ACS Style

Lisheng Song; William P. Kustas; Shaomin Liu; Paul D. Colaizzi; Héctor Nieto; Ziwei Xu; Yanfei Ma; Mingsong Li; Tongren Xu; Nurit Agam; Judy A. Tolk; Steven Evett. Applications of a thermal-based two-source energy balance model using Priestley-Taylor approach for surface temperature partitioning under advective conditions. Journal of Hydrology 2016, 540, 574 -587.

AMA Style

Lisheng Song, William P. Kustas, Shaomin Liu, Paul D. Colaizzi, Héctor Nieto, Ziwei Xu, Yanfei Ma, Mingsong Li, Tongren Xu, Nurit Agam, Judy A. Tolk, Steven Evett. Applications of a thermal-based two-source energy balance model using Priestley-Taylor approach for surface temperature partitioning under advective conditions. Journal of Hydrology. 2016; 540 ():574-587.

Chicago/Turabian Style

Lisheng Song; William P. Kustas; Shaomin Liu; Paul D. Colaizzi; Héctor Nieto; Ziwei Xu; Yanfei Ma; Mingsong Li; Tongren Xu; Nurit Agam; Judy A. Tolk; Steven Evett. 2016. "Applications of a thermal-based two-source energy balance model using Priestley-Taylor approach for surface temperature partitioning under advective conditions." Journal of Hydrology 540, no. : 574-587.

Journal article
Published: 01 August 2016 in International Journal of Remote Sensing
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ACS Style

Huizhen Zhou; Shaomin Liu; Jianjun He; Qiang Wen; Lisheng Song; Yanfei Ma. A new model for the automatic relative radiometric normalization of multiple images with pseudo-invariant features. International Journal of Remote Sensing 2016, 37, 4554 -4573.

AMA Style

Huizhen Zhou, Shaomin Liu, Jianjun He, Qiang Wen, Lisheng Song, Yanfei Ma. A new model for the automatic relative radiometric normalization of multiple images with pseudo-invariant features. International Journal of Remote Sensing. 2016; 37 (19):4554-4573.

Chicago/Turabian Style

Huizhen Zhou; Shaomin Liu; Jianjun He; Qiang Wen; Lisheng Song; Yanfei Ma. 2016. "A new model for the automatic relative radiometric normalization of multiple images with pseudo-invariant features." International Journal of Remote Sensing 37, no. 19: 4554-4573.

Journal article
Published: 01 August 2016 in Remote Sensing of Environment
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ACS Style

Guanghui Huang; Xin Li; Chunlin Huang; Shaomin Liu; Yanfei Ma; Hao Chen. Representativeness errors of point-scale ground-based solar radiation measurements in the validation of remote sensing products. Remote Sensing of Environment 2016, 181, 198 -206.

AMA Style

Guanghui Huang, Xin Li, Chunlin Huang, Shaomin Liu, Yanfei Ma, Hao Chen. Representativeness errors of point-scale ground-based solar radiation measurements in the validation of remote sensing products. Remote Sensing of Environment. 2016; 181 ():198-206.

Chicago/Turabian Style

Guanghui Huang; Xin Li; Chunlin Huang; Shaomin Liu; Yanfei Ma; Hao Chen. 2016. "Representativeness errors of point-scale ground-based solar radiation measurements in the validation of remote sensing products." Remote Sensing of Environment 181, no. : 198-206.

Journal article
Published: 29 May 2015 in Remote Sensing
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Validation and performance evaluations are beneficial for developing methods that estimate the remotely sensed land surface temperature (LST). However, such evaluations for Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data are rare. By selecting the middle reach of the Heihe River basin (HRB), China, as the study area, the atmospheric correction (AC), mono-window (MW), single-channel (SC), and split-window (SW) methods were evaluated based on in situ measured LSTs. Results demonstrate that the influences of surface heterogeneity on the validation are significant in the study area. For the AC, MW, and SC methods, the LSTs estimated from channel 13 are more accurate than those from channel 14 in general cases. When the in situ measured atmospheric profiles are available, the AC method has the highest accuracy, with a root-mean squared error (RMSE) of about 1.4–1.5 K at the homogenous oasis sites. In actual application without sufficient in situ measured inputs, the MW method is highly accurate; the RMSE is around 1.5–1.6 K. The SC method systematically overestimates LSTs and it is sensitive to error in the water vapor content. The two SW methods are simple to use but their performances are limited by accuracies, revealed by the simulation dataset. Therefore, when the in situ atmospheric profiles are available, the AC method is recommended to generate reliable ASTER LSTs for modeling the eco-hydrological processes in the middle reach of the HRB. When sufficient in situ measured inputs are not available, the MW method can be used instead.

ACS Style

Ji Zhou; Mingsong Li; Shaomin Liu; Zhenzhen Jia; Yanfei Ma. Validation and Performance Evaluations of Methods for Estimating Land Surface Temperatures from ASTER Data in the Middle Reach of the Heihe River Basin, Northwest China. Remote Sensing 2015, 7, 7126 -7156.

AMA Style

Ji Zhou, Mingsong Li, Shaomin Liu, Zhenzhen Jia, Yanfei Ma. Validation and Performance Evaluations of Methods for Estimating Land Surface Temperatures from ASTER Data in the Middle Reach of the Heihe River Basin, Northwest China. Remote Sensing. 2015; 7 (6):7126-7156.

Chicago/Turabian Style

Ji Zhou; Mingsong Li; Shaomin Liu; Zhenzhen Jia; Yanfei Ma. 2015. "Validation and Performance Evaluations of Methods for Estimating Land Surface Temperatures from ASTER Data in the Middle Reach of the Heihe River Basin, Northwest China." Remote Sensing 7, no. 6: 7126-7156.

Journal article
Published: 08 May 2015 in Remote Sensing
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Soil and vegetation component temperatures in non-isothermal pixels encapsulate more physical meaning and are more applicable than composite temperatures. The component temperatures however are difficult to be obtained from thermal infrared (TIR) remote sensing data provided by single view angle observations. Here, we present a land surface temperature and albedo (T-α) space approach combined with the mono-surface energy balance (SEB-1S) model to derive soil and vegetation component temperatures. The T-α space can be established from visible and near infrared (VNIR) and TIR data provided by single view angle observations. This approach separates the soil and vegetation component temperatures from the remotely sensed composite temperatures by incorporating soil wetness iso-lines for defining equivalent soil temperatures; this allows vegetation temperatures to be extracted from the T-α space. This temperature separation methodology was applied to advanced scanning thermal emission and reflection radiometer (ASTER) VNIR and high spatial resolution TIR image data in an artificial oasis area during the entire growing season. Comparisons with ground measurements showed that the T-α space approach produced reliable soil and vegetation component temperatures in the study area. Low root mean square error (RMSE) values of 0.83 K for soil temperatures and 1.64 K for vegetation temperatures, respectively, were obtained, compared to component temperatures measurements from a ground-based thermal camera. These results support the use of soil wetness iso-lines to derive soil surface temperatures. It was also found that the estimated vegetation temperatures were extremely close to the near surface air temperature observations when the landscape is well watered under full vegetation cover. More robust soil and vegetation temperature estimates will improve estimates of soil evaporation and vegetation transpiration, leading to more reliable the monitoring of crop water stress and drought.

ACS Style

Lisheng Song; Shaomin Liu; William P. Kustas; Ji Zhou; Yanfei Ma. Using the Surface Temperature-Albedo Space to Separate Regional Soil and Vegetation Temperatures from ASTER Data. Remote Sensing 2015, 7, 5828 -5848.

AMA Style

Lisheng Song, Shaomin Liu, William P. Kustas, Ji Zhou, Yanfei Ma. Using the Surface Temperature-Albedo Space to Separate Regional Soil and Vegetation Temperatures from ASTER Data. Remote Sensing. 2015; 7 (5):5828-5848.

Chicago/Turabian Style

Lisheng Song; Shaomin Liu; William P. Kustas; Ji Zhou; Yanfei Ma. 2015. "Using the Surface Temperature-Albedo Space to Separate Regional Soil and Vegetation Temperatures from ASTER Data." Remote Sensing 7, no. 5: 5828-5848.

Journal article
Published: 26 September 2014 in IEEE Geoscience and Remote Sensing Letters
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The determination of the spatial heterogeneity of the regional evapotranspiration over a complex underlying surface in an oasis-desert region is crucial for water resource management in a river basin and aiding in irrigation decisions. The surface energy balance system (SEBS) model has been widely used to estimate surface energy fluxes. However, the parameterization of surface roughness length for momentum transfer (z 0m ) and heat transfer (z 0h ) did not perform well for a complex underlying surface. Moreover, it is difficult to estimate surface soil heat flux, i.e., G 0 , accurately at the regional scale. In this letter, the parameterization schemes of z 0m , z 0h , and G 0 were optimized. Measurements from 21 sets of eddy covariance systems were used to validate the model performance. The results show that the revised SEBS model root-mean-square errors (RMSEs) of the satellite-based sensible and latent heat fluxes (H and LE) decreased from 97.2 W · m -2 to 56.9 W · m -2 and from 102.9 W · m -2 to 74.8 W · m -2 , respectively, at the footprint scale. At the pixel scale, the RMSEs of the revised model estimates of the H and LE were 40.9 W · m -2 and 57.5 W · m -2 , respectively. The improved agreements between the estimates and the measurements indicate that the revised SEBS model is appropriate for estimating regional energy fluxes over heterogeneous oasis-desert surfaces. Furthermore, the spatial and temporal patterns of the LE in the middle reaches of the Heihe River were investigated.

ACS Style

Yanfei Ma; Shaomin Liu; Fen Zhang; Ji Zhou; Zhenzhen Jia; Lisheng Song. Estimations of Regional Surface Energy Fluxes Over Heterogeneous Oasis–Desert Surfaces in the Middle Reaches of the Heihe River During HiWATER-MUSOEXE. IEEE Geoscience and Remote Sensing Letters 2014, 12, 671 -675.

AMA Style

Yanfei Ma, Shaomin Liu, Fen Zhang, Ji Zhou, Zhenzhen Jia, Lisheng Song. Estimations of Regional Surface Energy Fluxes Over Heterogeneous Oasis–Desert Surfaces in the Middle Reaches of the Heihe River During HiWATER-MUSOEXE. IEEE Geoscience and Remote Sensing Letters. 2014; 12 (3):671-675.

Chicago/Turabian Style

Yanfei Ma; Shaomin Liu; Fen Zhang; Ji Zhou; Zhenzhen Jia; Lisheng Song. 2014. "Estimations of Regional Surface Energy Fluxes Over Heterogeneous Oasis–Desert Surfaces in the Middle Reaches of the Heihe River During HiWATER-MUSOEXE." IEEE Geoscience and Remote Sensing Letters 12, no. 3: 671-675.