Thermal Emissivity And Infrared Temperature Dependence On Plant Canopy Architecture And View Angle

Chen, Jialin; Goel, Narendra S.

doi:10.1109/igarss.1990.688853

Cited by 21 publications

(15 citation statements)

References 8 publications

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“…Averaged measurements of leaf temperature provide a close empirical measurement of directional vegetation kinetic temperature (hereafter referred to as canopy temperature), and also approximate the radiative temperature for the canopy that we expect at low zenith angles given that the leaves are large, the canopy is closed, and emissivity of leaves is known to be high (Norman, Chen, & Goel, 1990). Unfortunately, a mismatch of 1 to 1.5 h between the in situ LiCor measurements and the closest flight line prevented us from using these raw leaf temperature measurements as validation data.…”

Section: Field Datamentioning

confidence: 99%

Improved surface temperature estimates with MASTER/AVIRIS sensor fusion

Grigsby

Hulley

Roberts

et al. 2015

Remote Sensing of Environment

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a b s t r a c tLand surface temperature (LST) is an important parameter in many ecological studies. The current Root Mean Square Error (RMSE) in standard MODIS and ASTER LST products is greater than 1 K, and for ASTER can be as large as 4 K for graybody pixels such as vegetation. Errors of 3 to 8 K have been observed for ASTER in humid conditions, making knowledge of atmospheric water vapor content critical in retrieving accurate LST. For this reason improved accuracy in LST measurements through the synthesis of visible-to-shortwave-infrared (VSWIR) derived water vapor maps and Thermal-Infrared (TIR) data is one goal of the Hyperspectral Infrared Imager, or HyspIRI, mission. The 2011 ER-2 Delano/Lost Hills flights acquired data with both the MODIS/ASTER Simulator (MASTER) and Airborne Visible InfraRed Imaging Spectrometer (AVIRIS) instruments flown concurrently. This study compares LST retrieval accuracies from the standard JPL MASTER temperature products produced using the temperature-emissivity separation (TES) algorithm, and the water vapor scaling (WVS) atmospheric correction method proposed for HyspIRI. The two retrieval methods are run both with and without high spatial resolution AVIRIS-derived water vapor maps to assess the improvement from VSWIR synthesis. We find improvement using VSWIR derived water vapor maps, with the WVS method being most accurate overall. For closed canopy agricultural vegetation we observed temperature retrieval RMSEs of 0.49 K and 0.70 K using the WVS method on MASTER data with and without AVIRIS derived water vapor, respectively.

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Section: Field Datamentioning

confidence: 99%

Improved surface temperature estimates with MASTER/AVIRIS sensor fusion

Grigsby

Hulley

Roberts

et al. 2015

Remote Sensing of Environment

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“…Thermal infrared (TIR) remote sensing is the only possible approach to retrieve LST (Coll et al, 2005) spatial resolutions and periodicities. Several factors need to be quantified in order to retrieve LST from satellite TIR data, such as, sensor radiometric calibrations (Wukelic et al, 1989), atmospheric correction (Cooper and Asrar, 1989), surface emissivity correction (Norman et al, 1990), characterization of spatial variability over land cover, and the combined effects of viewing geometry, background, and fractional vegetative cover. In estimation of LST from TIR data, the digital number of the image pixel needs to be converted into spectral radiance using the sensor calibration data (Markham and Barker, 1986) and emissivity correction.…”

Section: Introductionmentioning

confidence: 99%

Surface temperature estimation in Singhbhum Shear Zone of India using Landsat-7 ETM+ thermal infrared data

Srivastava¹,

Majumdar²,

Bhattacharya³

2009

Advances in Space Research

117

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“…There are also some preliminary indications from measurements made at the FIFE site of the changes of remotely-sensed temperatures with time and viewing angle (see Hall et al, 1992, Figure 10a, data from Vining and Blad, 1992), that the use of temporal changes may also reduce problems associated with angle of view. Some additional supporting results from the FIFE using the Cupid model (Norman et al, 1990) are shown in Figure 3(a,b). A comparison between measured and modeled directional brightness temperatures is shown in Figure 3(a) to support the validity of the model and show the importance of directional effects.…”

Section: Sensible Energy Flux Density (W/m"2)mentioning

confidence: 83%

Regional‐scale comparisons of vegetation and soil wetness with surface energy budget properties from satellite and in‐situ observations

Diak

Rabin

Gallo

et al. 1995

Remote Sensing Reviews

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This study focuses on relationships between vegetation cover, soil moisture, precipitation and evapotranspiration for the Midwest and Great Plains region of the central United States in early June 1988, the year of the Midwest drought. The data base consists of: (1) microwave estimates of soil moisture made using data from the Special Sensor Microwave/Imager (SSM/I); (2) Normalized Difference Vegetation Index (NDVI) estimates made using data from the Advanced Very High Resolution Radiometer (AVHRR); (3) surface-based Antecedent Precipitation Index (API) estimates made using precipitation records from surface reporting stations and; (4) estimates of sensible heating, evapotranspiration and an "effective" surface roughness made for the region using a combination of satellitemeasured surface "skin" temperatures from geostationary (GOES) satellites and radiosonde measurements of the time-changes of the height of the planetary boundary layer (DH) from the synoptic network. The scatter diagram of the daytime range (time-change) of surface skin temperature (DT S ) versus NDVI over the large region investigated shows a similar pattern to published results for 355 Downloaded by [Cambridge University Library] at 03:15 06 April 2015 356 G. R. DIAK ET AL.absolute skin temperature measurements versus NDVI over smaller areas (generally the size of a single watershed). Over the entire region investigated, the correlation between DT S and NDVI was poor. In the eastern section of the region, however, which was experiencing drought conditions by June 1988 (evidenced in very low API values), the correlation between DT S and NDVI was much improved. In the western section of the investigation region, with generally higher values of API (suggesting higher soil moisture content), there was a good correlation of DT S with API for areas with low NDVI. Values of a microwave-based API derived from SSM/I data generally showed similar relationships to DT S values as the surface-based API, but with slightly higher correlation coefficients. Values of the surface Bowen ratio derived from DT S and DH measurements were in qualitative agreement with the pattern of the developing drought conditions in the area, although quantitative comparisons with other the other components of the data base were less definitive. Values of an "effective" surface roughness derived from the same DT S and DH measurements showed a good correlation to NDVI.

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Thermal Emissivity And Infrared Temperature Dependence On Plant Canopy Architecture And View Angle

Cited by 21 publications

References 8 publications

Improved surface temperature estimates with MASTER/AVIRIS sensor fusion

Improved surface temperature estimates with MASTER/AVIRIS sensor fusion

Surface temperature estimation in Singhbhum Shear Zone of India using Landsat-7 ETM+ thermal infrared data

Regional‐scale comparisons of vegetation and soil wetness with surface energy budget properties from satellite and in‐situ observations

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