Land surface temperature and emissivity estimation from passive sensor data: Theory and practice-current trends

Dash, Prasanjit; Göttsche, Frank-M.; Olesen, F.; Fischer, H.

doi:10.1080/01431160110115041

Cited by 503 publications

(281 citation statements)

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“…Satellite TIR sensors measure radiances at the top of the atmosphere, from which brightness temperatures (also known as blackbody temperatures) can be derived using Plank's law (Dash et al 2002). It is recognized that the water vapor content does vary over time due to seasonality and inter-annual variability of the atmospheric conditions.…”

Section: Retrieval Of Lst From the Landsat 7 Etm+ Imagesmentioning

confidence: 99%

An approach to analyzing the intensity of the daytime surface urban heat island effect at a local scale

2008

Environ Monit Assess

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Section: Retrieval Of Lst From the Landsat 7 Etm+ Imagesmentioning

confidence: 99%

An approach to analyzing the intensity of the daytime surface urban heat island effect at a local scale

2008

Environ Monit Assess

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“…While more accurate q estimates may be provided by passive microwave remote sensor observations, they are at extremely coarse spatial resolutions (25 -50 km) [Jackson, 1997a;Entekhabi et al, 2004], arguably unsuited to heterogeneous Mediterranean ecosystems. Instead, estimates of T s from passive remote sensors (at infrared bands) are more attractive because they are more robust and also available at higher spatial resolutions: for instance, images from the AVHRR sensor are at 1100 m spatial resolution and daily temporal resolution, while images of the ASTER sensor mounted on Terra satellite are at 90 m spatial resolution and 16-day temporal resolution [Dash et al, 2002;Kustas et al, 2003]. For this reason, we investigate the possibility to estimate land surface fluxes from T s remote observations in heterogeneous ecosystems.…”

Section: Introductionmentioning

confidence: 99%

Soil moisture and vegetation controls on evapotranspiration in a heterogeneous Mediterranean ecosystem on Sardinia, Italy

Detto

Montaldo

Albertson

et al. 2006

Water Resources Research

200

241

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[1] Micrometeorological measurements of evapotranspiration (ET) can be difficult to interpret and use for validating model calculations in the presence of land cover heterogeneity. Land surface fluxes, soil moisture (q), and surface temperatures (T s ) data were collected by an eddy correlation-based tower located at the Orroli (Sardinia) experimental field (covered by woody vegetation, grass, and bare soil) from April 2003 to July 2004. Two Quickbird high-resolution images (summer 2003 and spring 2004) were acquired for depicting the contrasting land cover components. A procedure is presented for estimating ET in heterogeneous ecosystems as the residual term of the energy balance using T s observations, a two-dimensional footprint model, and the Quickbird images. Two variations on the procedure are successfully implemented: a proposed two-source random model (2SR), which treats the heat sources of each land cover component separately but computes the bulk heat transfer coefficient as spatially homogeneous, and a common two-source tile model. For 2SR, new relationships between the interfacial transfer coefficient and the roughness Reynolds number are estimated for the two bare soil-woody vegetation and grass-woody vegetation composite surfaces. The ET versus q relationships for each land cover component were also estimated, showing that that the woody vegetation has a strong tolerance to long droughts, transpiring at rates close to potential for even the driest conditions. Instead, the grass is much less tolerant to q deficits, and the switch from grass to bare soil following the rainy season had a significant impact on ET.

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“…Crucial findings considering the application of TIR remote sensing in urban environments were reported by Voogt and Oke in numerous studies, e.g., [28][29][30]. Theoretical background, several problems and recent developments in this field are summarized in detailed reviews by [31][32][33]. As a practical application, Dousset et al (2011) have demonstrated the use of satellite data for monitoring the 2003 heat wave in the metropolitan area of Paris.…”

Section: State Of the Artmentioning

confidence: 99%

Multiple Regression Analysis for Unmixing of Surface Temperature Data in an Urban Environment

Wicki

Parlow

2017

Remote Sensing

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Global climate change and increasing urbanization worldwide intensify the need for a better understanding of human heat stress dynamics in urban systems. During heat waves, which are expected to increase in number and intensity, the development of urban cool islands could be a lifesaver for many elderly and vulnerable people. The use of remote sensing data offers the unique possibility to study these dynamics with spatially distributed large datasets during all seasons of the year and including day and night-time analysis. For the city of Basel 32 high-quality Landsat 8 (L8) scenes are available since 2013, enabling comprehensive statistical analysis. Therefore, land surface temperature (LST) is calculated using L8 thermal infrared (TIR) imagery (stray light corrected) applying improved emissivity and atmospheric corrections. The data are combined with a land use/land cover (LULC) map and evaluated using administrative residential units. The observed dependence of LST on LULC is analyzed using a thermal unmixing approach based on a multiple linear regression (MLR) model, which allows for quantifying the gradual influence of different LULC types on the LST precisely. Seasonal variations due to different solar irradiance and vegetation cover indicate a higher dependence of LST on the LULC during the warmer summer months and an increasing influence of the topography and albedo during the colder seasons. Furthermore, the MLR analysis allows creating predicted LST images, which can be used to fill data gaps like in SLC-off Landsat 7 ETM+ data.

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Land surface temperature and emissivity estimation from passive sensor data: Theory and practice-current trends

Cited by 503 publications

References 0 publications

An approach to analyzing the intensity of the daytime surface urban heat island effect at a local scale

An approach to analyzing the intensity of the daytime surface urban heat island effect at a local scale

Soil moisture and vegetation controls on evapotranspiration in a heterogeneous Mediterranean ecosystem on Sardinia, Italy

Multiple Regression Analysis for Unmixing of Surface Temperature Data in an Urban Environment

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