On the relationship between thermal emissivity and the normalized difference vegetation index for natural surfaces

Griend, Adriaan A. Van de; Owe, Manfred

doi:10.1080/01431169308904400

Cited by 617 publications

(246 citation statements)

References 33 publications

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“…In this study, we have tested in HCMC with sample areas just as vegetation and bare soil, with the size much bigger than one pixel to determine NDVI of soil and vegetation; then, have determined the emissivity of soil and vegetation from the empirical formula of Van de Griend and Owe (1993) [22], then have calculated the fraction of vegetation cover Pv to provide input for Valor and Caselles method to determine the emissivity for each pixel of the study area.…”

Section: Estimation Of Surface Emissivitymentioning

confidence: 99%

“…Effective emissivity of a pixel can be estimated by adding up the contributions of plant and soil emissivity contained in that. Van de Griend and Owe (1993) [22] carried out experiments by directly measuring emissivity and reflectance in the visible and infrared spectrum for areas with homogeneous characteristics to calculate NDVI and found empirical relationship between emissivity and NDVI. ε = 1.0094 + 0.047*ln(NDVI)…”

Section: Estimation Of Surface Emissivitymentioning

confidence: 99%

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Urban Thermal Environment and Heat Island in Ho Chi Minh City, Vietnam from Remote Sensing Data

Thi¹,

B²,

M³

2017

Preprint

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Abstract:In urban area, one of the great problem is the rise of temperature, which leads to form the urban heat island effect. This paper refers to the trend of the urban surface temperature extracted from the Landsat images from which to consider changes in the formation of surface urban heat island for the north of Ho Chi Minh city in period 1995-2015. Research has identified land surface temperature from thermal infrared band, according to the ability of the surface emission based on characteristics of normalized difference vegetation index NDVI. The results showed that temperature fluctuated over the city with a growing trend and the gradual expansion of the area of the high-temperature zone towards the suburbs. Within 20 years, the trend of the formation of surface urban heat island with two typical locations showed a clear difference between the surface temperature of urban areas and rural areas with space expansion of heat island in 4 times in 2015 compared to 1995. An extreme heat island located in the inner city has an area of approximately 18% compared to the total area of the region. Since then, the solution to reduce the impact of urban heat island has been proposed, in order to protect the urban environment and the lives of residents in Ho Chi Minh City becoming better.

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Section: Estimation Of Surface Emissivitymentioning

confidence: 99%

Section: Estimation Of Surface Emissivitymentioning

confidence: 99%

Urban Thermal Environment and Heat Island in Ho Chi Minh City, Vietnam from Remote Sensing Data

Thi¹,

B²,

M³

2017

Preprint

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“…where S in is the incoming short wave radiation (W m 2 ), L in is the incoming long wave radiation (W m 2 ), L out is the outgoing long wave radiation (W m 2 ), r is the surface albedo, which can be retrieved from Band 1, 2, 3, 4, 5, and 7 of Landsat5 TM (Chen and Ohring, 1984;Koepke et al, 1985;Bastiaanssen et al, 1998a;Bastiaanssen, 2000;Wang et al, 2000), ε is the surface emissivity, which can be estimated by the Normal Difference Vegetation Index (NDVI) retrieved from the red and near infrared bands using semi-empirical relationships ( Van de Griend and Owe, 1993;Bastiaanssen et al, 1998a), T sur is the surface temperature (K), which can be retrieved by the thermal infrared band, Band 4853 6 of Landsat5 TM (Bastiaanssen, 2000;Chander and Markham, 2003). The atmospheric emissivity ε a can be estimated from atmospheric temperature and humidity (Brutsaert, 1975), is the Stefan-Boltzman constant (5Ð67 ð 10 8 W m 2 K 4 ).…”

Section: Model Similaritiesmentioning

confidence: 99%

Intercomparison of remote sensing‐based models for estimation of evapotranspiration and accuracy assessment based on SWAT

Gao

Long

2008

Hydrological Processes

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Abstract:An intercomparison of daily actual evapotranspiration (ET) estimates from the single-source models (SEBAL and SEBS) and the two-source models (P-TSEB and S-TSEB) using remotely sensed data was performed to examine their utilities and limitations under a wide range of land covers and different meteorological conditions. The accuracy of ET estimates from remote sensing-based models of a selected watershed on 23 June 2005 (DOY 174) presenting large air drying power and marked contrast in underlying surface characteristics, and 25 July 2005, (DOY 206) in contrast to the meteorological and underlying surface conditions of DOY 174, were evaluated in terms of SWAT-based ET. The ET estimates from the two methodologies are shown to be comparable, indicating that S-TSEB has the highest accuracy with relative errors of 2Ð2% and 5Ð6% with reference to SWAT-based ET for DOY 174 and 206, respectively. Hence it was selected to be the basis for performing an intercomparison with other remote sensing-based models. Single-source models are very sensitive to KB 1 parameter, rendering marked differences in ET estimates because of different treatments of roughness length for heat transfer. SEBAL and SEBS yielded mean absolute percentage difference (MAPD) versus S-TSEB within 26Ð22% and 26Ð56% for DOY 174 and within 9Ð11% and 11Ð69% for DOY 206, respectively, indicating their applicability to higher vegetation cover and soil moisture availability areas under small air drying power condition. P-TSEB generated MAPD versus S-TSEB within 41Ð15% for DOY 174 and 8Ð79% for DOY 206, implying that P-TSEB is highly consistent with S-TSEB under small air drying power and less contrast in soil moisture conditions, whereas noticeable discrepancies occur under large air drying power and marked contrast in soil moisture circumstances, in particular for sparse cover. The performance of P-TSEB largely depends on the meteorological and underlying surface conditions, both exerting significant influences on the extent of coupling between vegetation and soil.

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“…Also, NDVI contributed to the LST calculations for the single-channel thermal infrared (TIR) imagery such as Landsat by providing surface material emissivity values to calculate LST. [4] found that thermal emissivity was logarithmically correlated with NDVI for natural surface and pointed out its potential use in energy balance with satellite thermal images. This was further studied by [5] that land surface emissivity was retrieved from NDVI to investigate the coupling of surface temperature and emissivity for soil and vegetation type covers.…”

Section: Introductionmentioning

confidence: 99%

Anomalous Variations of NDVI for a Non-Vegetated Urban Industrial Area of Gumi, Korea

Bhang

2014

AJRS

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NDVI is often used to investigate how vegetation contributes to the surface urban heat islands (SUHI) effect.Generally, NDVIs obtained for partially vegetated or built-up areas have been found to be less than 0.4. However, anomalous NDVIs that are inconsistent with established concepts and relationships are frequently obtained for non-vegetated urban land cover. It is possible that these anomalous NDVIs have been distorted by the surface colors and patterns of rooftops. Therefore, we obtained NDVIs for an urban industrial area of Gumi, South Korea, and investigated how these NDVIs were affected by such surface colors and patterns. By assessing 148 factory rooftops, obtained NDVIs indeed showed a tendency to be affected by the surface colors and patterns of rooftops. A color classification of white, blue, purple, and red revealed that blue-and purple-colored rooftops resulted in higher NDVIs than other rooftops. Moreover, these rooftops were sometimes misidentified as forest and vegetation. The color tone, affected by brightness intensity, also contributed to the NDVIs obtained for blue-and purple-colored rooftops. Extreme cases showed that NDVIs obtained for rooftop surfaces could attain values indicative of dense vegetation (i.e., NDVIs ≥ 0.6), when blue-colored rooftops were combined with complex surface patterns that generated more shadow. From these results, we concluded that the established relationship between LST and NDVI is likely to be invalid for non-vegetated urban industrial areas, and that NDVIs obtained for such areas should be used with caution, particularly in studies of the SUHI effect.

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On the relationship between thermal emissivity and the normalized difference vegetation index for natural surfaces

Cited by 617 publications

References 33 publications

Urban Thermal Environment and Heat Island in Ho Chi Minh City, Vietnam from Remote Sensing Data

Urban Thermal Environment and Heat Island in Ho Chi Minh City, Vietnam from Remote Sensing Data

Intercomparison of remote sensing‐based models for estimation of evapotranspiration and accuracy assessment based on SWAT

Anomalous Variations of NDVI for a Non-Vegetated Urban Industrial Area of Gumi, Korea

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