English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Evapotranspiration (ET) plays an important role in surface–atmosphere\udinteractions and can be monitored using remote sensing data. However, surface\udheterogeneity, including the inhomogeneity of landscapes and surface\udvariables, significantly affects the accuracy of ET estimated from satellite\uddata. The objective of this study is to assess and reduce the uncertainties\udresulting from surface heterogeneity in remotely sensed ET using Chinese\udHJ-1B satellite data, which is of 30 m spatial resolution in VIS/NIR bands\udand 300 m spatial resolution in the thermal-infrared (TIR) band. A temperature-sharpening and flux aggregation scheme (TSFA) was developed to obtain accurate heat fluxes from the HJ-1B satellite data. The IPUS (input parameter upscaling) and TRFA (temperature resampling and flux aggregation) methods were used to compare with the TSFA in this study. The three methods represent three typical\udschemes used to handle mixed pixels from the simplest to the most complex.\udIPUS handles all surface variables at coarse resolution of 300 m in this\udstudy, TSFA handles them at 30 m resolution, and TRFA handles them at 30 and\ud300 m resolution, which depends on the actual spatial resolution. Analyzing\udand comparing the three methods can help us to get a better understanding of\udspatial-scale errors in remote sensing of surface heat fluxes. In\udsitu data collected during HiWATER-MUSOEXE (Multi-Scale Observation\udExperiment on Evapotranspiration over heterogeneous land surfaces of the\udHeihe Watershed Allied Telemetry Experimental Research) were used to validate\udand analyze the methods. ET estimated by TSFA exhibited the best agreement\udwith in situ observations, and the footprint validation results\udshowed that the R2, MBE, and RMSE values of the sensible heat flux (H) were 0.61, 0.90, and 50.99 W m−2,\udrespectively, and those for the latent heat flux (LE) were 0.82,\ud−20.54, and 71.24 W m−2, respectively. IPUS\udyielded the largest errors in ET estimation. The RMSE of LE between the TSFA\udand IPUS methods was 51.30 W m−2, and the RMSE of LE between\udthe TSFA and TRFA methods was 16.48 W m−2. Furthermore,\udadditional analysis showed that the TSFA method can capture the subpixel\udvariations of land surface temperature and the influences of various\udlandscapes within mixed pixels

Remote sensing algorithm for surface evapotranspiration considering landscape and statistical effects on mixed pixels