Articles | Volume 20, issue 11
https://doi.org/10.5194/hess-20-4409-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-20-4409-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
02 Nov 2016
Research article |
| 02 Nov 2016
Remote sensing algorithm for surface evapotranspiration considering landscape and statistical effects on mixed pixels
Zhi Qing Peng
State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, 100101, China
University of Chinese Academy of Sciences, Beijing, 100049, China
State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, 100101, China
Jin Jun Jiao
State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, 100101, China
University of Chinese Academy of Sciences, Beijing, 100049, China
Ti Zhou
State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, 100101, China
University of Chinese Academy of Sciences, Beijing, 100049, China
Qinhuo Liu
State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, 100101, China
Joint Center for Global Change Studies (JCGCS), Beijing, 100875, China
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Cited
13 citations as recorded by crossref.
- Uncertainty assessment of satellite remote-sensing-based evapotranspiration estimates: a systematic review of methods and gaps B. Tran et al. 10.5194/hess-27-4505-2023
- Estimating Subpixel Surface Heat Fluxes through Applying Temperature-Sharpening Methods to MODIS Data X. Li et al. 10.3390/rs9080836
- Estimating daily evapotranspiration based on a model of evaporative fraction (EF) for mixed pixels F. Li et al. 10.5194/hess-23-949-2019
- Multi-scale analysis of six evapotranspiration products across China: Accuracy, uncertainty and spatiotemporal pattern L. Zuo et al. 10.1016/j.jhydrol.2024.132516
- Analysis of the Spatial Variability of Land Surface Variables for ET Estimation: Case Study in HiWATER Campaign X. Li et al. 10.3390/rs10010091
- A framework for assessing urban greenery's effects and valuing its ecosystem services Y. Andersson-Sköld et al. 10.1016/j.jenvman.2017.09.071
- Estimation of daily evapotranspiration and irrigation water efficiency at a Landsat-like scale for an arid irrigation area using multi-source remote sensing data Y. Ma et al. 10.1016/j.rse.2018.07.019
- A Data Fusion Modeling Framework for Retrieval of Land Surface Temperature from Landsat-8 and MODIS Data G. Zhao et al. 10.3390/s20154337
- Modelling High-Resolution Actual Evapotranspiration through Sentinel-2 and Sentinel-3 Data Fusion R. Guzinski et al. 10.3390/rs12091433
- Estimation of land surface heat fluxes based on visible infrared imaging radiometer suite data: case study in northern China X. Li & X. Xin 10.1117/1.JRS.11.046012
- Estimating Evapotranspiration over Heterogeneous Surface with Sentinel-2 and Sentinel-3 Data: A Case Study in Heihe River Basin T. Lian et al. 10.3390/rs14061349
- Assessing the Effects of Spatial Scales on Regional Evapotranspiration Estimation by the SEBAL Model and Multiple Satellite Datasets: A Case Study in the Agro-Pastoral Ecotone, Northwestern China X. Li et al. 10.3390/rs13081524
- A dataset of high-resolution land surface temperature inversion for the China-Pakistan Economic Corridor (2013 – 2018) G. Zhao et al. 10.11922/csdata.2018.0055.zh
13 citations as recorded by crossref.
- Uncertainty assessment of satellite remote-sensing-based evapotranspiration estimates: a systematic review of methods and gaps B. Tran et al. 10.5194/hess-27-4505-2023
- Estimating Subpixel Surface Heat Fluxes through Applying Temperature-Sharpening Methods to MODIS Data X. Li et al. 10.3390/rs9080836
- Estimating daily evapotranspiration based on a model of evaporative fraction (EF) for mixed pixels F. Li et al. 10.5194/hess-23-949-2019
- Multi-scale analysis of six evapotranspiration products across China: Accuracy, uncertainty and spatiotemporal pattern L. Zuo et al. 10.1016/j.jhydrol.2024.132516
- Analysis of the Spatial Variability of Land Surface Variables for ET Estimation: Case Study in HiWATER Campaign X. Li et al. 10.3390/rs10010091
- A framework for assessing urban greenery's effects and valuing its ecosystem services Y. Andersson-Sköld et al. 10.1016/j.jenvman.2017.09.071
- Estimation of daily evapotranspiration and irrigation water efficiency at a Landsat-like scale for an arid irrigation area using multi-source remote sensing data Y. Ma et al. 10.1016/j.rse.2018.07.019
- A Data Fusion Modeling Framework for Retrieval of Land Surface Temperature from Landsat-8 and MODIS Data G. Zhao et al. 10.3390/s20154337
- Modelling High-Resolution Actual Evapotranspiration through Sentinel-2 and Sentinel-3 Data Fusion R. Guzinski et al. 10.3390/rs12091433
- Estimation of land surface heat fluxes based on visible infrared imaging radiometer suite data: case study in northern China X. Li & X. Xin 10.1117/1.JRS.11.046012
- Estimating Evapotranspiration over Heterogeneous Surface with Sentinel-2 and Sentinel-3 Data: A Case Study in Heihe River Basin T. Lian et al. 10.3390/rs14061349
- Assessing the Effects of Spatial Scales on Regional Evapotranspiration Estimation by the SEBAL Model and Multiple Satellite Datasets: A Case Study in the Agro-Pastoral Ecotone, Northwestern China X. Li et al. 10.3390/rs13081524
- A dataset of high-resolution land surface temperature inversion for the China-Pakistan Economic Corridor (2013 – 2018) G. Zhao et al. 10.11922/csdata.2018.0055.zh
Latest update: 23 Apr 2025
Short summary
A remote sensing algorithm named temperature sharpening and flux aggregation (TSFA) was applied to HJ-1B satellite data to estimate evapotranspiration over heterogeneous surface considering landscape and statistical effects on mixed pixels. Footprint validation results showed TSFA was more accurate and less uncertain than other two upscaling methods. Additional analysis and comparison showed TSFA can capture land surface heterogeneities and integrate the effect of landscapes within mixed pixels.
A remote sensing algorithm named temperature sharpening and flux aggregation (TSFA) was applied...
