Zhao-Liang Li

Chinese Academy of Agricultural Sciences

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Pei Leng

Institute of Agricultural Resources and Regional Planning

Si‐Bo Duan

Institute of Agricultural Resources and Regional Planning

Bo‐Hui Tang

Kunming University of Science and Technology

Hua Wu

University of Electronic Science and Technology of China

Ronglin Tang

Institute of Geographic Sciences and Natural Resources Research

Maofang Gao

Institute of Agricultural Resources and Regional Planning

Guofei Shang

Hebei GEO University

Xiangyang Liu

Chinese Academy of Agricultural Sciences

Xia Zhang

Shanxi Cardiovascular Hospital

Kun‐Shan Chen

Guilin University of Technology

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Chinese Academy of Sciences

149

University of Chinese Academy of Sciences

Institute of Geographic Sciences and Natural Resources Research

Chinese Academy of Agricultural Sciences

State Key Laboratory of Remote Sensing Science

Institute of Agricultural Resources and Regional Planning

Beijing Normal University

Ministry of Agriculture and Rural Affairs

Aerospace Information Research Institute

Centre National de la Recherche Scientifique

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Land Surface Temperature Retrieval From Landsat 8 Thermal Infrared Data Over Urban Areas Considering Geometry Effect: Method and Application

IEEE Transactions on Geoscience and Remote Sensing (2021)

Ru Chen Si‐Bo Duan Xiaoguang Jiang Zhao-Liang Li Yazhen Jiang

Accurate retrieval of land surface temperature (LST) over urban areas is of great significance for urban thermal environment monitoring. In previous studies, most of the urban LST retrieval methods were developed based on the assumption of a flat surface without considering the influence of urban 3-D geometry structure, which has a significant impact on the retrieval accuracy of LST over urban areas. In this study, a radiative transfer equation (RTE)-based single-channel method was developed to retrieve LST with urban geometry effect correction from the Landsat 8 thermal infrared (TIR) data in band 10. The increase in adjacent radiance from the surrounding pixels and the decrease in atmospheric downwelling radiance caused by urban geometry structure were taken into account in this method. Because it is difficult to directly validate the retrieval accuracy of LST over urban areas using in situ LST measurements, the performance of the RTE-based LST retrieval method was evaluated via comparing brightness temperature (BT) at the top of the atmosphere (TOA) simulated by the discrete anisotropic radiative transfer (DART) model and the urban RTE over three subregions. There is a good agreement between BT at the TOA simulated by the DART model and the urban RTE, with a root-mean-squared error (RMSE) of less than 0.25 K. The variations in LST retrieved with urban geometry effect correction over different local climate zones (LCZs) were analyzed. In general, built-up LCZs have relatively higher LST than land cover LCZs. The differences between LST retrieved without/with urban geometry effect correction over different LCZs are greater than 0.2 K. The largest average LST difference over built-up LCZs is approximately 0.9 K, whereas that over land cover LCZs is approximately 0.65 K. LST retrieved without/with urban geometry effect correction was used to calculate urban heat island intensity (UHII) in terms of the LCZ-based method. The results indicate that UHII calculated from LST with urban geometry effect correction is lower than that calculated from LST without urban geometry effect correction, with an average difference of approximately 0.5 K.

10.1109/tgrs.2021.3088482

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Citations (32)

Detection of Coal Fire Dynamics and Propagation Direction from Multi-Temporal Nighttime Landsat SWIR and TIR Data: A Case Study on the Rujigou Coalfield, Northwest (NW) China

Remote Sensing (2014)

Hongyuan Huo Xiaoguang Jiang Xianfeng Song Zhao-Liang Li Zhuoya Ni

Coal fires are common and serious phenomena in most coal-producing countries in the world. Coal fires not only burn valuable non-renewable coal reserves but also severely affect the local and global environment. The Rujigou coalfield in Shizuishan City, Ningxia, NW China, is well known for being a storehouse of anthracite coal. This coalfield is also known for having more coal fires than most other coalfields in China. In this study, an attempt was made to study the dynamics of coal fires in the Rujigou coalfield, from 2001 to 2007, using multi-temporal nighttime Landsat data. The multi-temporal nighttime short wave infrared (SWIR) data sets based on a fixed thresholding technique were used to detect and monitor the surface coal fires and the nighttime enhanced thematic mapper (ETM+) thermal infrared (TIR) data sets, based on a dynamic thresholding technique, were used to identify the thermal anomalies related to subsurface coal fires. By validating the coal fires identified in the nighttime satellite data and the coal fires extracted from daytime satellite data with the coal fire map (CFM) manufactured by field survey, we found that the results from the daytime satellite data had higher omission and commission errors than the results from the nighttime satellite data. Then, two aspects of coal fire dynamics were analyzed: first, a quantitative analysis of the spatial changes in the extent of coal fires was conducted and the results showed that, from 2001 to 2007, the spatial extent of coal fires increased greatly to an annual average area of 0.167 km2; second, the spreading direction and propagation of coal fires was analyzed and predicted from 2001 to 2007, and these results showed that the coal fires generally spread towards the north or northeast, but also spread in some places toward the east.

Anthracite

Thematic Mapper

10.3390/rs6021234

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Citations (49)

A practical algorithm for estimating surface soil moisture using combined optical and thermal infrared data

International Journal of Applied Earth Observation and Geoinformation (2016)

Pei Leng Xiaoning Song Si‐Bo Duan Zhao-Liang Li

FluxNet

Shortwave radiation

Ellipse

10.1016/j.jag.2016.07.004

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Citations (55)

An Improved Algorithm for Retrieving Land Surface Emissivity and Temperature From MSG-2/SEVIRI Data

IEEE Transactions on Geoscience and Remote Sensing (2013)

Caixia Gao Zhao-Liang Li Shi Qiu Bo‐Hui Tang Hua Wu

This paper presents an improved algorithm for simultaneously retrieving both land surface emissivity (LSE) and land surface temperature (LST) using data from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on board the MSG-2 satellite. First, the temperature-independent spectral index-based method for LSE retrieval is reviewed and improved in terms of three aspects: atmospheric correction, fitting of the bidirectional reflectivity model, and retrieval of the LSE in SEVIRI channel 10. Then, the generalized split-window method with seven unknown coefficients is used to derive the LST. Finally, this improved algorithm is applied to several MSG-2/SEVIRI data sets over a study area with geospatial coverage of latitude 30 ° N-45 ° N and longitude 15 ° W-15 ° E, and using detailed cases, the modifications to the original LSE/LST retrieval methods are shown to be effective and reasonable. In addition, the SEVIRI-derived LSTs are cross-validated primarily using the Moderate Resolution Imaging Spectroradiometer-derived validated LST data extracted from the MOD11B1 product on two clear-sky days (August 22, 2009 and July 3, 2008). The validation results indicate that more than 70% of the differences are within 2.5 K and that the LST differences tend to be lower at night than in the day, which may result from the homogeneous thermal conditions at night.

Moderate-resolution imaging spectroradiometer

Longitude

10.1109/tgrs.2013.2271510

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Citations (14)

Depolarized Scattering of Rough Surface With Dielectric Inhomogeneity and Spatial Anisotropy

IEEE Transactions on Geoscience and Remote Sensing (2020)

Ying Yang Kun‐Shan Chen Xiaofeng Yang Zhao-Liang Li Jiangyuan Zeng

This article presents a new index, polarizationconversion ratio (PCR) to characterize depolarized bistatic scattering from rough surfaces with dielectric inhomogeneity and spatial anisotropy.We then investigate the dependence of PCR on both surface and radar parameters.Numerical results show that the distribution of PCR on the scattering plane varies with the polarization state of the incident wave and incident angle.The PCR clusters more in the cross-plane for horizontally polarized incidence.However, for vertically polarized incidence, the PCR disperses as "triangular shape" on the whole scattering plane with a sharp valley occurring in the incident plane.The following points can be drawn: 1) the inhomogeneity effectively enhances the PCR in the cross-plane; 2) the effect of anisotropy on the PCR is relatively weak, because the scattering is less affected by correlation length; 3) the impacts of surface rms height on the PCR are negative on the whole scattering plane; and 4) as the background permittivity increases, at the horizontally polarized incidence, the PCR is enhanced in the backward and forward regions, while at vertically polarized incidence, it is enhanced in the incident plane and the forward region.As is demonstrated, the PCR is an effective measure of the sensitivity of depolarization, making it potentially useful as a new reliable index for surface parameter inversion.

Plane of incidence

Forward scatter

10.1109/tgrs.2020.2999543

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Citations (9)

Land surface emissivity retrieval from combined mid-infrared and thermal infrared data of MSG-SEVIRI

Remote Sensing of Environment (2006)

Geng‐Ming Jiang Zhao-Liang Li Françoise Nerry

Diurnal cycle

10.1016/j.rse.2006.07.015

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Citations (130)

Impact of nonlinearity and discontinuity on the spatial scaling effects of the leaf area index retrieved from remotely sensed data

International Journal of Remote Sensing (2012)

Hua Wu Bo‐Hui Tang Zhao-Liang Li

Abstract This article addresses the major scaling problems in leaf area index (LAI) retrieval for a heterogeneous surface associated with (1) the nonlinearity in the relationships between remotely sensed reflectances and LAI products, (2) the discontinuity caused by the mixture of contrasting cover types that is categorized as the dominating type within a large-scale pixel, and (3) the algorithm for the dominant cover type being used for the retrieval of the LAI in that large-scale mixed pixel. Through mathematical analysis, two scaling models (a component-based model and a pixel-based model) are proposed on the basis of the Taylor series expansion with the corresponding textural and contextural parameters (i.e. variance–covariance matrices and component fractions) to correct for the scaling effects among LAI products at different scales. These models express the magnitude of the scaling effects for the nonlinear and discontinuous situations as a function of (1) the degree of nonlinearity quantified by the second derivative of the retrieval function, (2) the spatial heterogeneity quantified by variance–covariance matrices, and (3) the component fractions in the large-scale mixed pixel. To evaluate the proposed scaling models, a scaling correction test is performed and analysed on a SPOT (Système Pour l'Observation de la Terre) image for two vegetation types. The component fractions have proven to be the main reason for the scaling effects in a mixed pixel. Compared to the results before scaling, using either of the two proposed models greatly reduces the retrieval errors that the scaling effects cause. The relative scaling effects of the LAI may be up to 55% in an uncorrected, large-scale mixed pixel. However, the relative scaling errors can be as low as 2% with the intra-component textural parameters and about 13% with the intra-pixel textural parameters. Because the scaling effects can be corrected for the spatial heterogeneity caused either by density changes within the same cover or by cover type changes, our work indicates that the proposed scaling models are promising and feasible. Acknowledgements The authors thank anonymous referees for their comments and suggestions that have significantly improved the article. This work was supported by the Chinese 973 Programme under Grant 2007CB714402 and the Hi-Tech Research and Development Programme of China (863 Plan Programme) under Grant 2008AA121805.

Discontinuity (linguistics)

10.1080/01431161.2012.716537

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Citations (32)

Prediction of vegetation phenology with atmospheric reanalysis over semiarid grasslands in Inner Mongolia

The Science of The Total Environment (2021)

Xue-Qing Ma Pei Leng Qian‐Yu Liao Yun-Jing Geng Xia Zhang

Growing season

10.1016/j.scitotenv.2021.152462

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Citations (18)

Development of a split-window algorithm for estimating sea surface temperature from the Chinese Gaofen-5 data

International Journal of Remote Sensing (2018)

Yuanyuan Chen Si‐Bo Duan Jélila Labed Zhao-Liang Li

Sea surface temperature (SST) is an essential climate variable that can be used to assess climate change. One kind of method commonly used to estimate SST based on remote-sensing measurements is the split-window (SW) algorithm. However, the derivation of the linear SW algorithm does not appear to reflect reality because some assumptions and approximations were used. Moreover, the quadratic SW equation cannot be interpreted theoretically although it maintains the structure of the linear SW equation. The Gaofen-5 (GF-5) satellite launch is planned for 2018. Focusing on exploring the mechanism of the SW algorithm using GF-5 data, this study investigated the assumptions and approximations used to derive the linear SW technique. Two revised equations of these assumptions and approximations were developed. Combining the revised equations, a nonlinear SW algorithm was obtained that could be simplified to the quadratic equation. Compared with previous research, this study focuses more on the theoretical interpretation and improves our understanding of the semi-empirical quadratic SW equation. The matchup data set produced by the European Organization for the Exploitation of Meteorological Satellites Ocean and Sea Ice Satellite Application Facility was used to validate the quadratic SW algorithm. A bias of −0.05 K and a RMSE of 0.53 K were obtained.

Linear equation

Data set

10.1080/01431161.2018.1488295

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Citations (20)

Land Surface Reflectance Retrieval from Hyperspectral Data Collected by an Unmanned Aerial Vehicle over the Baotou Test Site

PLoS ONE (2013)

Si‐Bo Duan Zhao-Liang Li Bo‐Hui Tang Hua Wu Lingling Ma

To evaluate the in-flight performance of a new hyperspectral sensor onboard an unmanned aerial vehicle (UAV-HYPER), a comprehensive field campaign was conducted over the Baotou test site in China on 3 September 2011. Several portable reference reflectance targets were deployed across the test site. The radiometric performance of the UAV-HYPER sensor was assessed in terms of signal-to-noise ratio (SNR) and the calibration accuracy. The SNR of the different bands of the UAV-HYPER sensor was estimated to be between approximately 5 and 120 over the homogeneous targets, and the linear response of the apparent reflectance ranged from approximately 0.05 to 0.45. The uniform and non-uniform Lambertian land surface reflectance was retrieved and validated using in situ measurements, with root mean square error (RMSE) of approximately 0.01-0.07 and relative RMSE of approximately 5%-12%. There were small discrepancies between the retrieved uniform and non-uniform Lambertian land surface reflectance over the homogeneous targets and under low aerosol optical depth (AOD) conditions (AOD = 0.18). However, these discrepancies must be taken into account when adjacent pixels had large land surface reflectance contrast and under high AOD conditions (e.g. AOD = 1.0).

10.1371/journal.pone.0066972

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Citations (22)