scholarly journals Estimation of Daily Terrestrial Latent Heat Flux with High Spatial Resolution from MODIS and Chinese GF-1 Data

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2811
Author(s):  
Xiangyi Bei ◽  
Yunjun Yao ◽  
Lilin Zhang ◽  
Yi Lin ◽  
Shaomin Liu ◽  
...  
Keyword(s):  
Heat Flux ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Spatial Resolution ◽  
Water Resource Management ◽  
Vegetation Indices ◽  
Great Promise ◽  
Wide Field ◽  
Spatiotemporal Resolution ◽  
High Spatiotemporal Resolution

Reliable estimates of terrestrial latent heat flux (LE) at high spatial and temporal resolutions are of vital importance for energy balance and water resource management. However, currently available LE products derived from satellite data generally have high revisit frequency or fine spatial resolution. In this study, we explored the feasibility of the high spatiotemporal resolution LE fusion framework to take advantage of the Moderate Resolution Imaging Spectroradiometer (MODIS) and Chinese GaoFen-1 Wide Field View (GF-1 WFV) data. In particular, three-fold fusion schemes based on Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM) were employed, including fusion of surface reflectance (Scheme 1), vegetation indices (Scheme 2) and high order LE products (Scheme 3). Our results showed that the fusion of vegetation indices and further computing LE (Scheme 2) achieved better accuracy and captured more detailed information of terrestrial LE, where the determination coefficient (R2) varies from 0.86 to 0.98, the root-mean-square error (RMSE) ranges from 1.25 to 9.77 W/m2 and the relative RSME (rRMSE) varies from 2% to 23%. The time series of merged LE in 2017 using the optimal Scheme 2 also showed a relatively good agreement with eddy covariance (EC) measurements and MODIS LE products. The fusion approach provides spatiotemporal continuous LE estimates and also reduces the uncertainties in LE estimation, with an increment in R2 by 0.06 and a decrease in RMSE by 23.4% on average. The proposed high spatiotemporal resolution LE estimation framework using multi-source data showed great promise in monitoring LE variation at field scale, and may have value in planning irrigation schemes and providing water management decisions over agroecosystems.

scholarly journals ERTFM: An Effective Model to Fuse Chinese GF-1 and MODIS Reflectance Data for Terrestrial Latent Heat Flux Estimation

2021 ◽  
Vol 13 (18) ◽  
pp. 3703
Author(s):  
Lilin Zhang ◽  
Yunjun Yao ◽  
Xiangyi Bei ◽  
Yufu Li ◽  
Ke Shang ◽  
...  
Keyword(s):  
Heat Flux ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Spatial Resolution ◽  
Spatial Scales ◽  
Irrigation Management ◽  
Fusion Model ◽  
Spatiotemporal Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Reflectance Data

Coarse spatial resolution sensors play a major role in capturing temporal variation, as satellite images that capture fine spatial scales have a relatively long revisit cycle. The trade-off between the revisit cycle and spatial resolution hinders the access of terrestrial latent heat flux (LE) data with both fine spatial and temporal resolution. In this paper, we firstly investigated the capability of an Extremely Randomized Trees Fusion Model (ERTFM) to reconstruct high spatiotemporal resolution reflectance data from a fusion of the Chinese GaoFen-1 (GF-1) and the Moderate Resolution Imaging Spectroradiometer (MODIS) products. Then, based on the merged reflectance data, we used a Modified-Satellite Priestley–Taylor (MS–PT) algorithm to generate LE products at high spatial and temporal resolutions. Our results illustrated that the ERTFM-based reflectance estimates showed close similarity with observed GF-1 images and the predicted NDVI agreed well with observed NDVI at two corresponding dates (r = 0.76 and 0.86, respectively). In comparison with other four fusion methods, including the widely used spatial and temporal adaptive reflectance fusion model (STARFM) and the enhanced STARFM, ERTFM had the best performance in terms of predicting reflectance (SSIM = 0.91; r = 0.77). Further analysis revealed that LE estimates using ERTFM-based data presented more detailed spatiotemporal characteristics and provided close agreement with site-level LE observations, with an R2 of 0.81 and an RMSE of 19.18 W/m2. Our findings suggest that the ERTFM can be used to improve LE estimation with high frequency and high spatial resolution, meaning that it has great potential to support agricultural monitoring and irrigation management.

scholarly journals Estimation of High-Resolution Global Monthly Ocean Latent Heat Flux from MODIS SST Product and AMSR-E Data

2020 ◽  
Vol 2020 ◽  
pp. 1-19
Author(s):  
Xiaowei Chen ◽  
Yunjun Yao ◽  
Shaohua Zhao ◽  
Yufu Li ◽  
Kun Jia ◽  
...  
Keyword(s):  
Heat Flux ◽  
Spatial Distribution ◽  
High Resolution ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Spatial Resolution ◽  
Satellite Data ◽  
High Spatial Resolution ◽  
Accurate Estimation ◽  
The Difference

Accurate estimation of satellite-derived ocean latent heat flux (LHF) at high spatial resolution remains a major challenge. Here, we estimate monthly ocean LHF at 4 km spatial resolution over 5 years using bulk algorithm COARE 3.0, driven by satellite data and meteorological variables from reanalysis. We validated the estimated ocean LHF by multiyear observations and by comparison with seven ocean LHF products. Validation results from monthly observations at 96 widely distributed buoy sites from three buoy site arrays (TAO, PIRATA, and RAMA) indicated a bias of less than 7 W/m2 with R2 of more than 0.80 (p<0.01) and with a King–Gupta efficiency (KGE) of over 0.84. Our estimated ocean LHF also performs well in simulating annual variability and predicting between-site variability, as indicated by a bias of lower than 6 W/m2 and an R2 of more than 0.84 (p<0.01). Overall, the average KGE for estimated ocean LHF increased by 18%–23% compared to other LHF products, indicating robust LHF estimation performance. Importantly, our estimated annual ocean LHF has similar global spatial distribution compared to other LHF products, although there are general differences in LHF values due to the difference in the models and the spatial resolution.

scholarly journals Analyzing influence of spatial resolution on the estimated evapotranspiration by using remote sensing data over an oasis area in Northwestern China

2009 ◽  
Vol 6 (1) ◽  
pp. 1321-1345
Author(s):  
H. Tian ◽  
J. Wen ◽  
Z. B. Su ◽  
Y. M. Ma ◽  
L. Wang ◽  
...  
Keyword(s):  
Heat Flux ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Spatial Resolution ◽  
Land Surface ◽  
Large Scale ◽  
Northwestern China ◽  
Retrieval Algorithm ◽  
Modis Data ◽  
Relative Errors

Abstract. In this paper, the influence of spatial resolution on the precision of estimates was analyzed through evapotranspiration (ET hereafter) modeling over a typical oasis in northwestern China by using the Landsat-TM and MODIS data. A relatively high consistency was observed between the TM-based latent heat flux and daily ET estimates and in-situ measurements, with relative errors of 9.7% and 8.8%, respectively. Despite lower precision of the relative errors of 22.4% and 17.0%, respectively, the MODIS-based latent heat flux and ET estimates can effectively depict the basic trend of the spatial distribution of the land surface processes. When the visible and near-infrared information of 250 m resolution was syncretized into MODIS LST retrieval algorithm, the precision of latent heat flux prediction was improved evidently. Additionally, the diurnal variation of the reference ET fraction shows that the temporal upscaling method of ET is suitable for the study area. In spite of suffering the influence of the heterogeneity of land surface, the moderate resolution MODIS data, combined with the parameterization model of land surface energy flux applied in this investigation, are suitable for the ET mapping at large scale while high-resolution data can serve as an important supplement.

An analog period method for gap‐filling of latent heat flux measurements

2021 ◽  
Author(s):  
Lucas Emilio B. Hoeltgebaum ◽  
Nelson Luís Dias ◽  
Marcelo Azevedo Costa
Keyword(s):  
Heat Flux ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Gap Filling ◽  
Flux Measurements

Scanning 10-W Water Vapor DIAL for the Investigation of Atmospheric Turbulence and Land-Atmosphere Feedback

2021 ◽  
Author(s):  
Andreas Behrendt ◽  
Florian Spaeth ◽  
Volker Wulfmeyer
Keyword(s):  
Heat Flux ◽  
Water Vapor ◽  
Latent Heat ◽  
Atmospheric Turbulence ◽  
Latent Heat Flux ◽  
Climate Models ◽  
Weather Forecast ◽  
Surface Characteristics ◽  
Scanning System ◽  
Forecast Models

&lt;p&gt;We will present recent measurements made with the water vapor differential absorption lidar (DIAL) of University of Hohenheim (UHOH). This scanning system has been developed in recent years for the investigation of atmospheric turbulence and land-atmosphere feedback processes.&lt;/p&gt;&lt;p&gt;The lidar is housed in a mobile trailer and participated in recent years in a number of national and international field campaigns. We will present examples of vertical pointing and scanning measurements, especially close to the canopy. The water vapor gradients in the surface layer are related to the latent heat flux. Thus, with such low-elevation scans, the latent heat flux distribution over different surface characteristics can be monitored, which is important to verify and improve both numerical weather forecast models and climate models.&lt;/p&gt;&lt;p&gt;The transmitter of the UHOH DIAL consists of a diode-pumped Nd:YAG laser which pumps a Ti:sapphire laser. The output power of this laser is up to 10 W. Two injection seeders are used to switch pulse-to-pulse between the online and offline signals. These signals are then either directly sent into the atmosphere or coupled into a fiber and guided to a transmitting telescope which is attached to the scanner unit. The receiving telescope has a primary mirror with a dimeter of 80 cm. The backscatter signals are recorded shot to shot and are typically averaged over 0.1 to 1 s.&lt;/p&gt;

The Effect of Soil on the Summertime Surface Energy Budget of a Humid Subarctic Tundra in Northern Quebec, Canada

2021 ◽  
Vol 22 (10) ◽  
pp. 2547-2564
Author(s):  
Georg Lackner ◽  
Daniel F. Nadeau ◽  
Florent Domine ◽  
Annie-Claude Parent ◽  
Gonzalo Leonardini ◽  
...  
Keyword(s):  
Heat Flux ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Land Surface ◽  
Sensible Heat Flux ◽  
Arctic Region ◽  
Heat Fluxes ◽  
Surface Energy Budget ◽  
Turbulent Heat ◽  
Turbulent Heat Fluxes

AbstractRising temperatures in the southern Arctic region are leading to shrub expansion and permafrost degradation. The objective of this study is to analyze the surface energy budget (SEB) of a subarctic shrub tundra site that is subject to these changes, on the east coast of Hudson Bay in eastern Canada. We focus on the turbulent heat fluxes, as they have been poorly quantified in this region. This study is based on data collected by a flux tower using the eddy covariance approach and focused on snow-free periods. Furthermore, we compare our results with those from six Fluxnet sites in the Arctic region and analyze the performance of two land surface models, SVS and ISBA, in simulating soil moisture and turbulent heat fluxes. We found that 23% of the net radiation was converted into latent heat flux at our site, 35% was used for sensible heat flux, and about 15% for ground heat flux. These results were surprising considering our site was by far the wettest site among those studied, and most of the net radiation at the other Arctic sites was consumed by the latent heat flux. We attribute this behavior to the high hydraulic conductivity of the soil (littoral and intertidal sediments), typical of what is found in the coastal regions of the eastern Canadian Arctic. Land surface models overestimated the surface water content of those soils but were able to accurately simulate the turbulent heat flux, particularly the sensible heat flux and, to a lesser extent, the latent heat flux.

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