收稿：2021-04-25，
纸质出版：2021-08-07
移动端阅览
与混合像元的地表温度相比，植被和土壤的组分温度具有更明确的物理意义。因此，本文提出了一种从具有广泛应用的极轨卫星地表温度产品中分离出植被和土壤组分温度的算法。该算法使用温度日变化模型作为桥梁连接极轨卫星一日内的两次观测，利用多像元数据进行模型求解，从而得到过境时刻的地表植被和土壤组分温度。论文针对MODIS数据开展了地表组分温度的反演，并利用实测站点数据和高分辨率卫星数据对反演结果进行了验证。结果表明，该算法可以提供合理的植被和土壤组分温度信息，反演温度的误差变化范围为1.4 K到2.5 K。此外，对观测时刻组合方式的分析表明该算法只需要一次白天观测和一次夜晚观测就可以得到精度较好的分离结果，并且两次观测可以来自于不同传感器，进一步表明了算法具有良好的可操作性。
The component temperature encapsulates more physical meaning than Land Surface Temperature (LST) and better meets the requirements of estimating evapotranspiration
monitoring drought and other studies. The polar-orbit satellites can observe the entire globe with a high spatial resolution and a modest temporal resolution from 1980 to present
and therefore have more wide applications than geostationary satellites. For these reasons
the study focuses on the methodology for estimating vegetation and soil component temperatures from polar-orbit satellite data.
To meet operational and accurate requirements
the study proposed to use multi-temporal and multi-pixel data to separate the vegetation and soil component temperature. Specifically
a well-studied Diurnal Temperature Cycles (DTC) model was applied to link the two observations on one day
and then the moving-window technology was used to add available observations for solving the retrieval model. In addition
a spatial weighting matrix was adopted to improve the limitation of using multi-pixel data.
The proposed algorithm was implemented by using Moderate Resolution Imaging Spectroradiometer (MODIS) data
and was evaluated by using in-situ measurements on Skukuza site and high-resolution Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data
respectively. In the case of the validation of field data
the separation accuracy of component temperatures is about 2 K
and RMSEs of daytime vegetation
nighttime vegetation
daytime soil
and nighttime soil are 2.3 K
2.5 K
1.5 K and 1.9 K
respectively. The better performance at daytime is resulted from the fact that DTC model cannot describe the temperature decrease at night well. Regarding with the validation of ASTER data
the separation accuracies of the vegetation and soil component are 1.4 K and 1.7 K
respectively. The vegetation component is slightly overestimated (bias = 0.3 K) while the soil component is slightly underestimated (bias = -0.7 K)
which is because of the systematic error between MODIS LST and ASTER LST. Moreover
this study also analyzed the influence of different time groups. Firstly
the combinations of one daytime moment and one nighttime moment can provide same estimation with high accuracy while the performance of the combination of two daytime moments is worse. The result is expected because two daytime moments are close to the maximum temperature moment
and therefore more sensitivity to temperature variation. Secondly
the performance of the time group from two sensors or one sensor is basically same
indicating that the time group is not limited by the sensor.
This study proposed an algorithm for separating vegetation and soil component temperatures from polar-orbit satellite land surface temperatures. The practical method need only two observations from single or different sensors
i.e.
one in daytime and the other one in nighttime
which makes it available for almost all sensors. The validation of field data and high-resolution data indicated that the separation accuracy is about 2 K and the best up to 1.4 K. Considering its accuracy
operationality and robustness
the proposed method would be an effective tool for separating component temperatures.
Bian Z J , Cao B , Li H , Du Y M , Song L S , Fan W J , Xiao Q and Liu Q H . 2017 . A robust inversion algorithm for surface leaf and soil temperatures using the vegetation clumping index . Remote Sensing , 9 ( 8 ): 780 [ DOI: 10.3390/rs9080780 http://dx.doi.org/10.3390/rs9080780 ]
Bian Z J , Li H , Göttsche F M , Li R B , Du Y M , Ren H Z , Cao B , Xiao Q and Liu Q H . 2020 . Retrieving soil and vegetation temperatures from dual-angle and multipixel satellite observations . IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing , 13 : 5536 - 5549 [ DOI: 10.1109/JSTARS.2020.3024190 http://dx.doi.org/10.1109/JSTARS.2020.3024190 ]
Duan S B and Li Z L . 2015 . Intercomparison of operational land surface temperature products derived from MSG-SEVIRI and Terra/Aqua-MODIS data . IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing , 8 ( 8 ): 4163 - 4170 [ DOI: 10.1109/JSTARS.2015.2441096 http://dx.doi.org/10.1109/JSTARS.2015.2441096 ]
Duan S B , Li Z L , Cheng J and Leng P . 2017 . Cross-satellite comparison of operational land surface temperature products derived from MODIS and ASTER data over bare soil surfaces . ISPRS Journal of Photogrammetry and Remote Sensing , 126 : 1 - 10 [ DOI: 10.1016/j.isprsjprs.2017.02.003 http://dx.doi.org/10.1016/j.isprsjprs.2017.02.003 ]
Ermida S L , DaCamara C C , Trigo I F , Pires A C , Ghent D and Remedios J . 2017 . Modelling directional effects on remotely sensed land surface temperature . Remote Sensing of Environment , 190 : 56 - 69 [ DOI: 10.1016/j.rse.2016.12.008 http://dx.doi.org/10.1016/j.rse.2016.12.008 ]
Ghent D . 2014 . Maximising the benefits of satellite LST within the user community: ESA DUE GlobTemperature // AGU Fall Meeting Abstracts . Washington, DC, USA : American Geophysical Union
Gillespie A , Rokugawa S , Matsunaga T , Cothern J S , Hook S and Kahle A B . 1998 . A temperature and emissivity separation algorithm for Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images . IEEE Transactions on Geoscience and Remote Sensing , 36 ( 4 ): 1113 - 1126 [ DOI: 10.1109/36.700995 http://dx.doi.org/10.1109/36.700995 ]
He J L , Zhao W , Li A N , Wen F P and Yu D J . 2019 . The impact of the terrain effect on land surface temperature variation based on Landsat-8 observations in mountainous areas . International Journal of Remote Sensing , 40 ( 5/6 ): 1808 - 1827 [ DOI: 10.1080/01431161.2018.1466082 http://dx.doi.org/10.1080/01431161.2018.1466082 ]
Hong F L , Zhan W F , Göttsche F M , Liu Z H , Zhou J , Huang F , Lai J M and Li M C . 2018 . Comprehensive assessment of four-parameter diurnal land surface temperature cycle models under clear-sky . ISPRS Journal of Photogrammetry and Remote Sensing , 142 : 190 - 204 [ DOI: 10.1016/j.isprsjprs.2018.06.008 http://dx.doi.org/10.1016/j.isprsjprs.2018.06.008 ]
Inamdar A K , French A , Hook S , Vaughan G and Luckett W . 2008 . Land surface temperature retrieval at high spatial and temporal resolutions over the southwestern United States . Journal of Geophysical Research : Atmospheres , 113 ( D7 ): D 07107 [ DOI: 10.1029/2007JD009048 http://dx.doi.org/10.1029/2007JD009048 ]
Jia L , Li Z L , Menenti M , Su Z , Verhoef W and Wan Z . 2003 . A practical algorithm to infer soil and foliage component temperatures from bi-angular ATSR-2 data . International Journal of Remote Sensing , 24 ( 23 ): 4739 - 4760 [ DOI: 10.1080/0143116031000101576 http://dx.doi.org/10.1080/0143116031000101576 ]
Kallel A , Ottlé C , Le Hegarat-Mascle S , Maignan F and Courault D . 2013 . Surface temperature downscaling from multiresolution instruments based on Markov models . IEEE Transactions on Geoscience and Remote Sensing , 51 ( 3 ): 1588 - 1612 [ DOI: 10.1109/TGRS.2012.2207461 http://dx.doi.org/10.1109/TGRS.2012.2207461 ]
Li Z L , Tang B H , Wu H , Ren H Z , Yan G J , Wan Z M , Trigo I F and Sobrino J A . 2013 . Satellite-derived land surface temperature: current status and perspectives . Remote Sensing of Environment , 131 : 14 - 37 [ DOI: 10.1016/j.rse.2012.12.008 http://dx.doi.org/10.1016/j.rse.2012.12.008 ]
Liu Q , Yan C Y , Xiao Q , Yan G J and Fang L . 2012 . Separating vegetation and soil temperature using airborne multiangular remote sensing image data . International Journal of Applied Earth Observation and Geoinformation , 17 : 66 - 75 [ DOI: 10.1016/j.jag.2011.10.003 http://dx.doi.org/10.1016/j.jag.2011.10.003 ]
Liu X Y , Tang B H and Li Z L . 2018 . Evaluation of three parametric models for estimating directional thermal radiation from simulation, airborne, and satellite data . Remote Sensing , 10 ( 3 ): 420 [ DOI: 10.3390/rs10030420 http://dx.doi.org/10.3390/rs10030420 ]
Liu X Y , Tang B H , Li Z L , Zhou C H , Wu W B and Rasmussen M O . 2020 . An improved method for separating soil and vegetation component temperatures based on diurnal temperature cycle model and spatial correlation . Remote Sensing of Environment , 248 : 111979 [ DOI: 10.1016/j.rse.2020.111979 http://dx.doi.org/10.1016/j.rse.2020.111979 ]
Liu X Y , Tang B H , Wu H , Tang R L , Li Z L and Shang G F . 2019 . A method for angular normalization of land surface temperature products based on component temperatures and fractional vegetation cover // IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium . Yokohama, Japan : IEEE : 1849 - 1852 [ DOI: 10.1109/IGARSS.2019.8899823 http://dx.doi.org/10.1109/IGARSS.2019.8899823 ]
McMillen D P . 2004 . Geographically weighted regression: the analysis of spatially varying relationships . American Journal of Agricultural Economics , 86 ( 2 ): 554 - 556 [ DOI: 10.1111/j.0002-9092.2004.600_2.x http://dx.doi.org/10.1111/j.0002-9092.2004.600_2.x ]
Mu X H , Song W J , Gao Z , McVicar T R , Donohue R J and Yan G J . 2018 . Fractional vegetation cover estimation by using multi-angle vegetation index . Remote Sensing of Environment , 216 : 44 - 56 [ DOI: 10.1016/j.rse.2018.06.022 http://dx.doi.org/10.1016/j.rse.2018.06.022 ]
Norman J M and Becker F . 1995 . Terminology in thermal infrared remote sensing of natural surfaces . Remote Sensing Reviews , 12 ( 3/4 ): 159 - 173 [ DOI: 10.1080/02757259509532284 http://dx.doi.org/10.1080/02757259509532284 ]
Pinheiro A C T , Privette J L and Guillevic P . 2006 . Modeling the observed angular anisotropy of land surface temperature in a savanna . IEEE Transactions on Geoscience and Remote Sensing , 44 ( 4 ): 1036 - 1047 [ DOI: 10.1109/TGRS.2005.863827 http://dx.doi.org/10.1109/TGRS.2005.863827 ]
Pinheiro A C T , Privette J L , Mahoney R and Tucker C J . 2004 . Directional effects in a daily AVHRR land surface temperature dataset over Africa . IEEE Transactions on Geoscience and Remote Sensing , 42 ( 9 ): 1941 - 1954 [ DOI: 10.1109/TGRS.2004.831886 http://dx.doi.org/10.1109/TGRS.2004.831886 ]
Quan J L , Chen Y H , Zhan W F , Wang J F , Voogt J and Li J . 2014 . A hybrid method combining neighborhood information from satellite data with modeled diurnal temperature cycles over consecutive days . Remote Sensing of Environment , 155 : 257 - 274 [ DOI: 10.1016/j.rse.2014.08.034 http://dx.doi.org/10.1016/j.rse.2014.08.034 ]
Song L S , Bian Z J , Kustas W P , Liu S M , Xiao Q , Nieto H , Xu Z W , Yang Y , Xu T R and Han X J . 2020 . Estimation of surface heat fluxes using multi-angular observations of radiative surface temperature . Remote Sensing of Environment , 239 : 111674 [ DOI: 10.1016/j.rse.2020.111674 http://dx.doi.org/10.1016/j.rse.2020.111674 ]
Song L S , Liu S M , Kustas W P , Zhou J and Ma Y F . 2015 . Using the surface temperature-albedo space to separate regional soil and vegetation temperatures from ASTER data . Remote Sensing , 7 ( 5 ): 5828 - 5848 [ DOI: 10.3390/rs70505828 http://dx.doi.org/10.3390/rs70505828 ]
Tang B H . 2018 . Nonlinear split-window algorithms for estimating land and sea surface temperatures from simulated Chinese gaofen-5 satellite data . IEEE Transactions on Geoscience and Remote Sensing , 56 ( 11 ): 6280 - 6289 [ DOI: 10.1109/TGRS.2018.2833859 http://dx.doi.org/10.1109/TGRS.2018.2833859 ]
Thome K , Palluconi F , Takashima T and Masuda K . 1998 . Atmospheric correction of ASTER . IEEE Transactions on Geoscience and Remote Sensing , 36 ( 4 ): 1199 - 1211 [ DOI: 10.1109/36.701026 http://dx.doi.org/10.1109/36.701026 ]
Vermote E F , Roger J C and Ray J P . 2015 . MODIS surface reflectance user's guide. MODIS land surface reflectance science computing facility, version, 1 . 4 [2018-03-15] https://modis-land.gsfc.nasa.gov/pdf/MOD09_UserGuide_v1.4.pdf https://modis-land.gsfc.nasa.gov/pdf/MOD09_UserGuide_v1.4.pdf
Wan Z M and Dozier J . 1996 . A generalized split-window algorithm for retrieving land-surface temperature from space . IEEE Transactions on Geoscience and Remote Sensing , 34 ( 4 ): 892 - 905 [ DOI: 10.1109/36.508406 http://dx.doi.org/10.1109/36.508406 ]
Xie F , Shao H L , Liu Z H , Liu C Y , Zhang C X , Yang G , Wang J Y and Cai N B . 2016 . Retrieval of the pixel component temperatures from multi-band thermal infrared image using Bayesian inversion technique // Proceedings of SPIE , Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques and Applications VI. New Delhi, India : SPIE : 98802 A [ DOI: 10.1117/12.2227579 http://dx.doi.org/10.1117/12.2227579 ]
Zhan W F , Chen Y H , Zhou J and Li J . 2011 . An algorithm for separating soil and vegetation temperatures with sensors featuring a single thermal channel . IEEE Transactions on Geoscience and Remote Sensing , 49 ( 5 ): 1796 - 1809 [ DOI: 10.1109/TGRS.2010.2082555 http://dx.doi.org/10.1109/TGRS.2010.2082555 ]
Zhan W F , Chen Y H , Zhou J , Wang J F , Liu W Y , Voogt J , Zhu X L , Quan J L and Li J . 2013 . Disaggregation of remotely sensed land surface temperature: literature survey, taxonomy, issues, and caveats . Remote Sensing of Environment , 131 : 119 - 139 [ DOI: 10.1016/j.rse.2012.12.014 http://dx.doi.org/10.1016/j.rse.2012.12.014 ]
Zhang R H , Sun X M , Wang W M , Xu J P , Zhu Z L and Tian J . 2005 . An operational two-layer remote sensing model to estimate surface flux in regional scale: physical background . Science in China Series D : Earth Sciences , 48 ( Supp. 1 ): 225 - 244 [ DOI: 10.1360/05zd0023 http://dx.doi.org/10.1360/05zd0023 ]
Zhao W , Li A N , Bian J H , Jin H A and Zhang Z J . 2014 . A synergetic algorithm for mid-morning land surface soil and vegetation temperatures estimation using MSG-SEVIRI products and TERRA-MODIS products . Remote Sensing , 6 ( 3 ): 2213 - 2238 [ DOI: 10.3390/rs6032213 http://dx.doi.org/10.3390/rs6032213 ]
Zhu W B , Jia S F and Lv A F . 2017 . A time domain solution of the Modified Temperature Vegetation Dryness Index (MTVDI) for continuous soil moisture monitoring . Remote Sensing of Environment , 200 : 1 - 17 [ DOI: 10.1016/j.rse.2017.07.032 http://dx.doi.org/10.1016/j.rse.2017.07.032 ]
Zhan C , Tang B H and Li Z L . 2018 . Retrieval and validation of land surface temperature for atmospheres with air temperature inversion . Journal of Remote Sensing , 22 ( 1 ): 28 - 37
战川 , 唐伯惠 , 李召良 . 2018 . 近地表大气逆温条件下的地表温度遥感反演与验证 . 遥感学报 , 22 ( 1 ): 28- 37 [ DOI: 10.11834/jrs.20187043 http://dx.doi.org/10.11834/jrs.20187043 ]
Li Z L , Duan S B , Tang B H , Wu H , Ren H Z , Yan G J , Tang R L and Leng P . 2016 . Review of methods for land surface temperature derived from thermal infrared remotely sensed data . Journal of Remote Sensing , 20 ( 5 ): 899 - 920
李召良 , 段四波 , 唐伯惠 , 吴骅 , 任华忠 , 阎广建 , 唐荣林 , 冷佩 . 2016 . 热红外地表温度遥感反演方法研究进展 . 遥感学报 , 20 ( 5 ): 899- 920 [ DOI: 10.11834/jrs.20166192 http://dx.doi.org/10.11834/jrs.20166192 ]
相关作者
相关机构
京公网安备11010802024621
