An Efficient Approach for Pixel Decomposition to Increase the Spatial Resolution of Land Surface Temperature Images from MODIS Thermal Infrared Band Data

文献类型： 外文期刊

第一作者： Wang, Fei

作者： Wang, Fei;Song, Caiying;Zhao, Shuhe;Qin, Zhihao;Li, Wenjuan;Karnieli, Arnon;Zhao, Shuhe

作者机构：

关键词： pixel decomposition;land surface temperature;spatial resolution;MODIS;ASTER

期刊名称：SENSORS （ 影响因子：3.576； 五年影响因子：3.735 ）

ISSN： 1424-8220

年卷期： 2015 年 15 卷 1 期

页码：

收录情况： SCI

摘要： Land surface temperature (LST) images retrieved from the thermal infrared (Tilt) band data of Moderate Resolution Imaging Spectroradiometer (MODIS) have much lower spatial resolution than the MODIS visible and near-infrared (VNIR) band data. The coarse pixel scale of MODIS LST images (1000 m under nadir) have limited their capability in applying to many studies required high spatial resolution in comparison of the MODIS VNIR band data with pixel scale of 250-500 m. In this paper we intend to develop an efficient approach for pixel decomposition to increase the spatial resolution of MODIS LST image using the VNIR band data as assistance. The unique feature of this approach is to maintain the thermal radiance of parent pixels in the MODIS LST image unchanged after they are decomposed into the sub-pixels in the resulted image. There are two important steps in the decomposition: initial temperature estimation and final temperature determination. Therefore the approach can be termed double-step pixel decomposition (DSPD). Both steps involve a series of procedures to achieve the final result of decomposed LST image, including classification of the surface patterns, establishment of LST change with normalized difference of vegetation index (NDVI) and building index (NDBI), reversion of LST into thermal radiance through Planck equation, and computation of weights for the sub-pixels of the resulted image. Since the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) with much higher spatial resolution than MODIS data was on-board the same platform (Terra) as MODIS for Earth observation, an experiment had been done in the study to validate the accuracy and efficiency of our approach for pixel decomposition. The ASTER LST image was used as the reference to compare with the decomposed LST image. The result showed that the spatial distribution of the decomposed LST image was very similar to that of the ASTER LST image with a root mean square error (RMSE) of 2.7 K for entire image. Comparison with the evaluation DisTrad (E-DisTrad) and re-sampling methods for pixel decomposition also indicate that our DSPD has the lowest RMSE in all cases, including urban region, water bodies, and natural terrain. The obvious increase in spatial resolution remarkably uplifts the capability of the coarse MODIS LST images in highlighting the details of LST variation. Therefore it can be concluded that, in spite of complicated procedures, the proposed DSPD approach provides an alternative to improve the spatial resolution of MODIS LST image hence expand its applicability to the real world.

分类号：

  • 相关文献

[1]Evaluation of ASTER-Like Daily Land Surface Temperature by Fusing ASTER and MODIS Data during the HiWATER-MUSOEXE. Yang, Guijun,Sun, Chenhong,Zhao, Chunjiang,Weng, Qihao,Weng, Qihao,Pu, Ruiliang,Gao, Feng,Li, Hua. 2016

[2]An algorithm to retrieve land surface temperature from ASTER thermal band data for agricultural drought monitoring. Qin, Zhihao,Li, Wenjuan,Gao, Maofang,Zhang, Hong'ou,Qin, Zhihao. 2006

[3]Estimation of land surface emissivity for Landsat TM6 and its application to Lingxian Region in north China. Qin, Zhihao,Li, Wenjuan,Gao, Maofang,Zhang, Hong'ou,Qin, Zhihao. 2006

[4]Estimation of subpixel temperature over a heterogeneous area using an endmember index based technique. Yang Guijun,Huang Wenjiang,Wang Jihua,Zhao Chunjiang. 2011

[5]Estimation of Regional Leaf Area Index by Remote Sensing Inversion of PROSAIL Canopy Spectral Model. Li Shu-min,Li Hong,Zhou Lian-di,Sun Dan-feng. 2009

[6]Estimation of subpixel land surface temperature using an endmember index based technique: A case examination on ASTER and MODIS temperature products over a heterogeneous area. Yang, Guijun,Yang, Guijun,Yang, Guijun,Zhao, Chunjiang,Huang, Wenjiang,Wang, Jihua,Pu, Ruiliang.

[7]An Algorithm for Retrieving Land Surface Temperatures Using VIIRS Data in Combination with Multi-Sensors. Xia, Lang,Mao, Kebiao,Ma, Ying,Zhao, Fen,Qin, Zhihao,Jiang, Lipeng,Shen, Xinyi. 2014

[8]Reconstructing daily clear-sky land surface temperature for cloudy regions from MODIS data. Sun, Liang,Chen, Zhongxin,Wang, Limin,Sun, Liang,Gao, Feng,Anderson, Martha,Yang, Yun,Song, Lisheng,Hu, Bo.

[9]Evaluation of Sentinel-2A Satellite Imagery for Mapping Cotton Root Rot. Song, Xiaoyu,Zhao, Chunjiang,Yang, Guijun,Song, Xiaoyu,Zhao, Chunjiang,Yang, Guijun,Song, Xiaoyu,Yang, Chenghai,Wu, Mingquan,Hoffmann, Wesley Clint,Wu, Mingquan,Huang, Wenjiang. 2017

[10]Multi-scale geospatial agroecosystem modeling: A case study on the influence of soil data resolution on carbon budget estimates. Zhang, Xuesong,Manowitz, David H.,Izaurralde, Roberto C.,Thomson, Allison M.,West, Tristram O.,Zhang, Xuesong,Manowitz, David H.,Izaurralde, Roberto C.,Thomson, Allison M.,West, Tristram O.,Sahajpal, Ritvik,Izaurralde, Roberto C.,Zhao, Kaiguang,LeDuc, Stephen D.,Xu, Min,Xiong, Wei,Zhang, Aiping,Post, Wilfred M..

[11]Effective detection of benzoyl peroxide in flour based on parameter selection of Raman hyperspectral system. Wang, Xiaobin,Zhao, Chunjiang,Wang, Xiaobin,Zhao, Chunjiang,Huang, Wenqian,Wang, Qingyan,Liu, Chen,Yang, Guiyan,Wang, Xiaobin,Zhao, Chunjiang,Huang, Wenqian,Wang, Qingyan,Liu, Chen,Yang, Guiyan,Wang, Xiaobin,Zhao, Chunjiang,Huang, Wenqian,Wang, Qingyan,Liu, Chen,Yang, Guiyan,Wang, Xiaobin,Zhao, Chunjiang,Huang, Wenqian,Wang, Qingyan,Liu, Chen,Yang, Guiyan. 2017

[12]Retrieving and Assessing Land Surface Temperature from ASTER Data. Yang, Guijun,Shi, Yuechan,Wang, Renli. 2012

[13]Spatio-temporal variation of alpine grassland spring phenological and its response to environment factors northeastern of Qinghai-Tibetan Plateau during 2000-2016. Li, Guangyong,Jiang, Guanghui,Li, Guangyong,Bai, Ju,Jiang, Cuihong. 2017

[14]ESTIMATION OF SURFACE SOIL MOISTURE USING FENGYUN-2E (FY-2E) DATA: A CASE STUDY OVER THE SOURCE AREA OF THE YELLOW RIVER. Wang, Yawei,Song, Xiaoning,Sun, Chuan,Liu, Xin,Leng, Pei. 2016

[15]Integrating seasonal optical and thermal infrared spectra to characterize urban impervious surfaces with extreme spectral complexity: a Shanghai case study. Wang, Wei,Ji, Minhe,Yao, Xinfeng. 2016

[16]Ground temperature measurement and emissivity determination to understand the thermal anomaly and its significance on the development of an arid environmental ecosystem in the sand dunes across the Israel-Egypt border. Qin, Z,Berliner, PR,Karnieli, A.

[17]Impacts of land use/cover change on spatial variation of land surface temperature in Urumqi, China. Pei, Huan,Qin, Zhihao,Zhang, Chunling,Lu, Liping,Qin, Zhihao,Xu, Bin,Gao, Maofang,Fang, Shifeng. 2007

[18]Derivation of Land Surface Temperature for Landsat-8 TIRS Using a Split Window Algorithm. Rozenstein, Offer,Karnieli, Arnon,Qin, Zhihao,Derimian, Yevgeny. 2014

[19]Forecasting of Powdery Mildew disease with multi-sources of remote sensing information. Zhang, Jingcheng,Yuan, Lin,Nie, Chenwei,Wei, Liguang,Yang, Guijun,Zhang, Jingcheng,Yang, Guijun,Zhang, Jingcheng,Yang, Guijun,Zhang, Jingcheng,Yuan, Lin. 2014

[20]Comparison of split window algorithms for land surface temperature retrieval from NOAA-AVHRR data. Qin, ZH,Xu, B,Zhang, WC,Li, WJ,Chen, ZX,Zhang, HO. 2004

作者其他论文 更多>>

微信小程序