Remote sensing based evapotranspiration and runoff modeling of agricultural, forest and urban flux sites in Denmark: From field to macro-scale

Boegh, Eva; Poulsen, Robert Nøddebo; Butts, M. B.; Abrahamsen, Per; Dellwik, Ebba; Hansen, Søren; Hasager, Charlotte Bay; Ibrom, Andreas; Loerup, J.-K.; Pilegaard, Kim; Soegaard, H.

doi:10.1016/j.jhydrol.2009.08.029

Cited by 68 publications

(33 citation statements)

References 46 publications

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“…On the other hand, although fewer studies have used the MESMA approach to calculate urban heat fluxes, simple spectral mixture analyses have proven to be efficient for describing urban heat flux terms [70,71]. Qualitatively, our results complement the findings of a small number of previous studies that revealed the potential of spectral mixture analysis for depicting urban surface energy fluxes.…”

Section: Significance and Future Worksupporting

confidence: 80%

An Assessment of Urban Surface Energy Fluxes Using a Sub-Pixel Remote Sensing Analysis: A Case Study in Suzhou, China

Fang

Dong

et al. 2016

IJGI

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Urban surface energy fluxes are closely associated with land-cover types (LCTs) and critical biophysical compositions. This study aims to assess the contribution of LCTs, vegetation fractional coverage (VFC) and percentage of impervious surface area (ISA%) to urban surface energy fluxes using remote sensing. An advanced urban surface energy flux algorithm was used to combine satellite imagery and meteorological station data to investigate the thermal environments in the city of Suzhou, China. The land cover abundances retrieved by multiple endmember spectral unmixing analysis (MESMA) were used to retrieve the per-pixel sensible heat flux (H) and latent heat flux (LE). The resultant heat fluxes were assessed using evaporation pan data collected from meteorological stations and ratios of the heat fluxes to the net radiation (Rn). Furthermore, spatial patterns of urban heat energy were investigated using an integrated analysis among land surface temperature (LST), heat fluxes, LCTs, VFC and ISA%. The high values of H and LST were found over the urbanized areas, which also had low values of LE. Conversely, the vegetated area was characterized with high LEs, as well as low LSTs and Hs. Moreover, a statistically-significant correlation (p < 0.05; R 2 = 0.88) was observed between LE and VFC at the zonal level, and a statistically-significant correlation (p < 0.05; R 2 = 0.90) was exhibited between H and ISA%. It is concluded that VFC, ISA% and LCTs are promising for delineating urban heat fluxes. Overall, this study indicates that remote sensing techniques can be used to quantify urban thermal environments.

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Section: Significance and Future Worksupporting

confidence: 80%

An Assessment of Urban Surface Energy Fluxes Using a Sub-Pixel Remote Sensing Analysis: A Case Study in Suzhou, China

Fang

Dong

et al. 2016

IJGI

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“…The results were validated and were found to closely approximate ground-based measurements. Boegh et al (2009) used the water balance equation and investigated its relationship to ET for natural vegetation through the vegetation parameters of LAI and crop coefficient. They found a close agreement between canopy growth and ET rates, predominantly in forests.…”

Section: Relationship Between Non-agricultural Mixed Vegetation Indicmentioning

confidence: 99%

Remote sensing techniques for predicting evapotranspiration from mixed vegetated surfaces

Nouri

Beecham

Anderson

et al. 2014

Urban Water Journal

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Evapotranspiration (ET) is a key component of the hydrological cycle however it is also the most difficult factor to quantify. In recent decades, estimating ET has been improved by advances in remote sensing, particularly in agricultural studies. However, quantifying ET from mixed vegetation environs, particularly urban parklands, is still challenging due to the heterogeneity of plant species, canopy covers, microclimates, and because of costly methodological requirements. Several studies have recently been conducted in agriculture and forestry which may be useful for mixed landscape vegetation studies with some modifications. This review describes general remote sensing-based approaches to estimate ET and describes their advantages and disadvantages. Most of these approaches need extensive time investment, medium to high skill levels and are quite expensive. However, in addition to the reviewed methods, the authors recommend combining remotely sensed vegetation indices and ground-based techniques for ET estimation of mixed landscape vegetation such as urban parklands.

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“…Despite these apparent obstacles, a number of successful VI methods have been developed to estimate ET a in a wide variety of landscape types, including rainforests (Juarez et al 2008), arctic tundra and boreal forests (Mu et al 2009Zhang et al 2009b), riparian zones (Nagler et al 2005a(Nagler et al , b, 2009aMurray et al 2009;Scott et al 2008;Barz et al 2009), desert phreatophyte communities ), semi-arid grasslands (Alfieri et al 2009;Nagler et al 2007) and shrublands ), sparse desert shrublands (Glenn et al 2008b), and mixed landscapes at the regional (Juarez et al 2008;Boegh et al 2009;Scheffield et al 2009;Wang et al 2007;Wang and Liang 2008;Leuning et al 2008;Li et al 2009;Zhang et al 2009a), continental (Cleugh et al 2007;Guerschman et al 2009;Yang et al 2006) and global Fisher et al 2008) scales of measurement. Examples are presented in Table 1.…”

Section: Overview Of Approachesmentioning

confidence: 99%

Vegetation Index Methods for Estimating Evapotranspiration by Remote Sensing

2010

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Evapotranspiration (ET) is the largest term after precipitation in terrestrial water budgets. Accurate estimates of ET are needed for numerous agricultural and natural resource management tasks and to project changes in hydrological cycles due to potential climate change. We explore recent methods that combine vegetation indices (VI) from satellites with ground measurements of actual ET (ET a ) and meteorological data to project ET a over a wide range of biome types and scales of measurement, from local to global estimates. The majority of these use time-series imagery from the Moderate Resolution Imaging Spectrometer on the Terra satellite to project ET over seasons and years. The review explores the theoretical basis for the methods, the types of ancillary data needed, and their accuracy and limitations. Coefficients of determination between modeled ET a and measured ET a are in the range of 0.45-0.95, and root mean square errors are in the range of 10-30% of mean ET a values across biomes, similar to methods that use thermal infrared bands to estimate ET a and within the range of accuracy of the ground measurements by which they are calibrated or validated. The advent of frequent-return satellites such as Terra and planed replacement platforms, and the increasing number of moisture and carbon flux tower sites over the globe, have made these methods feasible. Examples of operational

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Remote sensing based evapotranspiration and runoff modeling of agricultural, forest and urban flux sites in Denmark: From field to macro-scale

Cited by 68 publications

References 46 publications

An Assessment of Urban Surface Energy Fluxes Using a Sub-Pixel Remote Sensing Analysis: A Case Study in Suzhou, China

An Assessment of Urban Surface Energy Fluxes Using a Sub-Pixel Remote Sensing Analysis: A Case Study in Suzhou, China

Remote sensing techniques for predicting evapotranspiration from mixed vegetated surfaces

Vegetation Index Methods for Estimating Evapotranspiration by Remote Sensing

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