A new single-channel method for estimating land surface temperature based on the image inherent information: The HJ-1B case

Chen, Feng; Yang, Song; Su, Zhongbo; He, Baoyin

doi:10.1016/j.isprsjprs.2014.11.008

Cited by 22 publications

(29 citation statements)

References 31 publications

(53 reference statements)

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“…The accuracy of the MOD11A1 has been verified and the margin error is 1.0 K [62]. Previous studies have proven MOD11A1 is the useful tool for experts and scholars to validate the accuracy of the LST retrieved from HJ-1B [63,64].…”

Section: Comparison With Modis Lst Productmentioning

confidence: 76%

Seasonal Variations of the Urban Thermal Environment Effect in a Tropical Coastal City

Yao

Chen

Qian

et al. 2017

Advances in Meteorology

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Shenzhen city was selected to analyze the Surface Urban Heat Island (SUHI) variations based on land surface temperature (LST) in four different seasons of 2015. UHI intensity (UHII) as an indicator of SUHI was established and the method of density segmentation was utilized to classify the SUHI after LSTs were normalized. The gravity center model of UHII and Moran's (a spatial autocorrelation index) were used to analyze the spatiotemporal variations of SUHI. Results indicated that LST was higher in the west than in the east of the city. The values of UHII were higher in spring and summer and lower in autumn and winter.Five profiles were drawn to analyze the distribution of UHII in different seasons, and it was found that the No. 1 path profiles, corresponding to the western urban development axis, had higher UHII than other path profiles. The center of UHII gravity shifts converged in the Longhua, Baoan, and Nanshan Districts throughout the four seasons and Moran's values were higher in summer and spring. From the UHII's spatial distribution pattern analysis, a spatially discontinuous pattern was observed in four seasons; there was a compact pattern of high temperature zones.

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Section: Comparison With Modis Lst Productmentioning

confidence: 76%

Seasonal Variations of the Urban Thermal Environment Effect in a Tropical Coastal City

Yao

Chen

Qian

et al. 2017

Advances in Meteorology

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“…(3)), two methods called the MTSC method and the IBSC method were developed accordingly, while proper assumptions were taken [10,12] . General information about these new methods is introduced as follows.…”

Section: Methodsmentioning

confidence: 99%

“…The IBSC method simply assumes that at a specific time (t), the similar pixels and P 0 are provided with identical thermal properties-with same surface temperature and emissivity [12] .…”

Section: Methodsmentioning

confidence: 99%

“…In current version, similar pixels are determined according to the spectral similarity in view of reflectance property. The spectral similarity is measured by means of root mean square deviation of the multispectral bands (for the HJ-1B, only four CCD multispectral bands are provided) [10,12] . Then the similar pixel is defined, considering that pixel measured with smaller root mean square deviation value is more likely similar to the target one.…”

Section: Methodsmentioning

confidence: 99%

“…However, the atmospheric heterogeneity is obvious at regional scale, which suggests that the retrieval procedures using parameters obtained at one station or even with none atmospheric correction probably result in potential bias [11] . In some cases, MODIS MOD 05 product might not improve the LST results, resulted from its uncertainty, although it is considered as a good resource for atmospheric correction [11,12] . Therefore, the difficulty in parameter collection possibly limits the application of the current single-channel algorithms.…”

Section: Introductionmentioning

confidence: 99%

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The new single-channel approaches for retrieving land surface temperature and the preliminary results

et al. 2014

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Two satellites named HJ-1A and HJ-1B were launched on 6 September 2008, which are intended for environment and disaster monitoring and forecasting. The infrared scanner (IRS) onboard HJ-1B has one thermal infrared band. Currently, for sensors with one thermal band (e.g. Landsat TM/ETM+ and HJ-1B), several empirical algorithms have been developed to estimate land surface temperature (LST). However, surface emissivity and atmospheric parameters which are not readily accessible to general users are required for these empirical methods. To resolve this problem, particularly for HJ-1B, new retrieval methodology is desired. According to proper assumptions, two approaches were proposed, which included the single-channel method based on temporal and spatial information (MTSC) and the image based single-channel method (IBSC). The newly developed methods are mainly for estimating LST accurately from one thermal band, even without any accurate information related to the atmospheric parameters and land surface emissivity. In this paper, we introduce and give preliminary assessments on the new approaches. Assessments generally show good agreement between the HJ-1B retrieved results and the MODIS references. Especially, over sea and water areas the biases were less than 1K while the root mean square errors were about 1K for both MTSC and IBSC methods. As expected, the MTSC method did superiorly to the IBSC method, owning to spatiotemporal information is incorporated into the MTSC method, although more experiments and comparisons should be conducted further.

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An enhanced single‐channel algorithm for retrieving land surface temperature from Landsat series data

Wang

Zhang

et al. 2016

JGR Atmospheres

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Land surface temperature (LST) is a critical parameter in the physics of Earth surface processes and is required for many applications related to ecology and environment. Landsat series satellites have provided more than 30 years of thermal information at medium spatial resolution. This paper proposes an enhanced single‐channel algorithm (SCen) for retrieving LST from Landsat series data (Landsat 4 to Landsat 8). The SCen algorithm includes three atmospheric functions (AFs), and the latitude and acquisition month of Landsat image were added to the AF models to improve LST retrieval. Performance of the SCen algorithm was assessed with both simulated and in situ data, and accuracy of three single‐channel algorithms (including the monowindow algorithm developed by Qin et al., SCQin, and the generalized single‐channel algorithm developed by Jiménez‐Muñoz and Sobrino, SCJ&S) were compared. The accuracy assessments with simulated data had root‐mean‐square deviations (RMSDs) for the SCen, SCJ&S, and SCQin algorithms of 1.363 K, 1.858 K, and 2.509 K, respectively. Validation with in situ data showed RMSDs for the SCen and SCJ&S algorithms of 1.04 K and 1.49 K, respectively. It was concluded that the SCen algorithm is very operational, has good precision, and can be used to develop an LST product for Landsat series data.

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A new single-channel method for estimating land surface temperature based on the image inherent information: The HJ-1B case

Cited by 22 publications

References 31 publications

Seasonal Variations of the Urban Thermal Environment Effect in a Tropical Coastal City

Seasonal Variations of the Urban Thermal Environment Effect in a Tropical Coastal City

The new single-channel approaches for retrieving land surface temperature and the preliminary results

An enhanced single‐channel algorithm for retrieving land surface temperature from Landsat series data

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