A verification of the 'triangle' method for obtaining surface soil water content and energy fluxes from remote measurements of the Normalized Difference Vegetation Index (NDVI) and surface e

Gillies, Robert R.; Kustas, William P.; Humes, K. S.

doi:10.1080/014311697217026

Cited by 634 publications

(361 citation statements)

References 0 publications

Supporting

Mentioning

346

Contrasting

Unclassified

Order By: Relevance

“…The general idea of contextual models is that the variability in LST alone or in combination with the variability in vegetation properties is linked to the surface status, e.g. soil moisture availability or energy flux partitioning at the surface (Tomás et al 2014; Timmermans, Kustas, and Andreu 2015; Moran et al 1994; Jiang and Islam 2001; Gillies, Kustas, and Humes 1997; Gillies and Carlson 1995). If the image scene contains a wide range of vegetation covers and surface states that represent conditions from potential to no ET, all pixels of the image can be scaled between the cold/wet and hot/dry extremes within the scene.…”

Section: Introductionmentioning

confidence: 99%

Estimation of evapotranspiration of temperate grassland based on high-resolution thermal and visible range imagery from unmanned aerial systems

Brenner

Zeeman

Bernhardt

et al. 2018

International Journal of Remote Sensing

View full text Add to dashboard Cite

Spatially distributed high-resolution data of land surface temperature (LST) and evapotranspiration (ET) are important information for crop water management and other applications in the agricultural sector. While satellite data can provide LST high-resolution data of 100 m, the current development of unmanned aerial systems (UAS) and affordable low-weight thermal cameras allows LST and subsequent ET to be derived at resolutions down to centimetre scale.In this study, UAS-based images in the thermal infrared (TIR) and visible spectral range were collected over a managed temperate grassland in July 2016 at the Terrestrial Environmental Observatories Networks TERENO preAlpine observatory site at Fendt, Germany. The UAS set-up included a lightweight thermal camera (Optris Pi Lightweight) and a regular digital camera (Sony α 6000) that allowed for the acquisition of thermal and optical images with a ground resolution of 5 cm and 1 cm, respectively. Three TIR-based ET models of different complexity were applied and the resulting ET estimates were compared to the Eddy covariance (EC) observations of turbulent energy fluxes and also to the evaporative fraction. While the Deriving Atmosphere Turbulent Transport Useful To Dummies Using Temperature (DATTUTDUT) model and the Triangle Method belong to the group of simpler contextual models, the Two-Source Energy Balance (TSEB) model incorporates a more physically based formulation of the surface energy balance. In addition to the comparison of UAS-based estimates of latent heat fluxes to EC observations, the effect of the spatial resolution of the model imagery input on the modelled results was analysed by running the models with imagery from the native resolution of the acquired images to resolutions that were aggregated up to 30 m.The results show that both contextual models are sensitive to the input image resolution and that the agreement with the EC observations improves with increasing image resolution. The TSEB model assumes that LST pixels represent a mixed signal of the soil and canopy components, thus an image resolution coarse enough to ensure this assumption should be chosen. However, with the exception of the native image resolution of 5 cm, we found no effect of image resolution on the spatially weighted mean TSEB estimates.For the studied grassland, the comparison of model estimates with EC observations indicates that all three models are able to reproduce observed energy fluxes with comparable accuracy with mean absolute errors of ET between 20 and 40 W m−2. The TSEB model showed larger deviations from the reference observations under cloudy conditions with rapid fluctuations of LST within the 30 min averaging period for EC. The two contextual models yielded similar results for most of the flights. The good performance of the DATTUTDUT model, which had the lowest input requirements of the three models, is especially promising in view of the application of UAS for routine near-real-time ET monitoring.

show abstract

Section: Introductionmentioning

confidence: 99%

Estimation of evapotranspiration of temperate grassland based on high-resolution thermal and visible range imagery from unmanned aerial systems

Brenner

Zeeman

Bernhardt

et al. 2018

International Journal of Remote Sensing

View full text Add to dashboard Cite

show abstract

“…The LST-SAT relationship is dependent on soil moisture (SM) for sites with low NDVIs, since wet soils exchange latent heat mainly, leaving LST similar to SAT, and dry soils give large LST-SAT differences. The relationship between LST and NDVI results in a triangular shape and the slope of the curve has been related to SM [18] and surface evapotranspiration. Unfortunately, neither SM remotely-sensed products nor ground data were available at the spatial resolution of the study.…”

Section: Geographical Datamentioning

confidence: 99%

“…Unfortunately, neither SM remotely-sensed products nor ground data were available at the spatial resolution of the study. LST and NDVI variables, which some authors use for SM estimation [18], were already included in the SAT approach. Finally, Ninyerola et al [14] considered geographical variables as important climate factors to include.…”

Section: Geographical Datamentioning

confidence: 99%

Land Surface Air Temperature Retrieval From EOS-MODIS Images

Niclòs

Valiente

Barberà

et al. 2014

IEEE Geosci. Remote Sensing Lett.

View full text Add to dashboard Cite

Abstract-The knowledge of the spatial and temporal patterns of Surface Air Temperature (SAT) is essential to monitor a region's climate and meteorology, quantify surface exchange processes, improve climatic and meteorological model results, and study health and economic impacts. This work analyzed correlations between SAT and geophysical land surface variables, Land Surface Temperature (LST) mainly, to establish operative techniques to obtain spatially-continuous land SAT maps from satellite data, unlike data provided by meteorological station networks. The correlations were analyzed by using EOS-MODIS images, meteorological station network data, and geographical variables. Linear regressions with MODIS-retrieved LST data gave SAT with uncertainties higher than ±2K during daytime and of ±1.8K at night-time. Nevertheless, SAT uncertainties decreased up to ±1.2K when other satellite-retrieved surface parameters, i.e. vegetation index and albedo, together with meteorological and geographical data were considered as terms of multivariable regressions. The equations finally proposed were shown to work properly for different land covers.

show abstract

“…Both masks also remove pixels contaminated with clouds. Once the area has been separated into land and sea, the land region is analysed using the LST estimation procedure described in [5], [6], [9], while the sea area is processed using the algorithm defined in [11] for SST estimation. After both procedures are accomplished, the hybrid result (containing data from both sources) is returned in the form of a single product.…”

Section: Fig 5 Lst/vi Space Graphic Representation Containing Lst Dmentioning

confidence: 99%

Characterizing Surface and Air Temperature in the Baltic Sea Coastal Area Using Remote Sensing Techniques and Gis

Chybicki

Kulawiak

Łubniewski

2016

Polish Maritime Research

View full text Add to dashboard Cite

show abstract

A verification of the 'triangle' method for obtaining surface soil water content and energy fluxes from remote measurements of the Normalized Difference Vegetation Index (NDVI) and surface e

Cited by 634 publications

References 0 publications

Estimation of evapotranspiration of temperate grassland based on high-resolution thermal and visible range imagery from unmanned aerial systems

Estimation of evapotranspiration of temperate grassland based on high-resolution thermal and visible range imagery from unmanned aerial systems

Land Surface Air Temperature Retrieval From EOS-MODIS Images

Characterizing Surface and Air Temperature in the Baltic Sea Coastal Area Using Remote Sensing Techniques and Gis

Contact Info

Product

Resources

About