王鹏新,刘郊,李俐,张树誉,解毅.应用中值融合模型的条件植被温度指数降尺度转换研究[J].农业机械学报,2017,48(6):100-108.
WANG Pengxin,LIU Jiao,LI Li,ZHANG Shuyu,XIE Yi.Down scaling Transformation of Vegetation Temperature Condition Index Using Median Fusion Model[J].Transactions of the Chinese Society for Agricultural Machinery,2017,48(6):100-108.
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应用中值融合模型的条件植被温度指数降尺度转换研究   [下载全文]
Down scaling Transformation of Vegetation Temperature Condition Index Using Median Fusion Model   [Download Pdf][in English]
投稿时间:2016-10-11  
DOI:10.6041/j.issn.1000-1298.2017.06.013
中文关键词:  干旱遥感监测  MODIS数据  Landsat数据  降尺度  条件植被温度指数  中值融合模型
基金项目:国家自然科学基金项目(41371390)
作者单位
王鹏新 中国农业大学信息与电气工程学院 
刘郊 中国农业大学信息与电气工程学院 
李俐 中国农业大学信息与电气工程学院 
张树誉 陕西省气象局 
解毅 中国农业大学信息与电气工程学院 
中文摘要:为获得基于Landsat卫星遥感数据更为精确的定量化干旱监测结果,以陕西省关中平原为研究区域,基于Aqua MODIS数据反演的1km空间分辨率的条件植被温度指数(VTCI)的定量化干旱监测结果(MODIS-VTCI)和Landsat OLI/TIRS 数据反演的30m空间分辨率的VTCI相对干湿监测结果(Landsat-VTCI),应用降尺度的中值融合模型(MFM)将基于MODIS数据反演的VTCI降尺度至30m空间分辨率的VTCI定量化干旱监测,并对其结果进行验证。结果表明,应用降尺度的中值融合模型转换的VTCI定量化干旱监测结果(MFM-VTCI)与Landsat-VTCI的空间分布及纹理特征相似,两者间的相关系数和结构相似度均较大,均方根误差、差值影像及差值频数分布图所呈现的结果与定量化干旱监测结果和相对干湿监测结果间的系统误差相符,表明Landsat-VTCI与MFM-VTCI间的可比性较强。MFM-VTCI与累计降水间的相关性和MODIS-VTCI与累计降水间的相关性相近,均大于Landsat-VTCI与累计降水间的相关性,表明MFM-VTCI是定量化的干旱监测结果。
WANG Pengxin  LIU Jiao  LI Li  ZHANG Shuyu  XIE Yi
College of Information and Electrical Engineering, China Agricultural University,College of Information and Electrical Engineering, China Agricultural University,College of Information and Electrical Engineering, China Agricultural University,Shaanxi Provincial Meteorological Bureau and College of Information and Electrical Engineering, China Agricultural University
Key Words:drought monitoring by remote sensing  MODIS data  Landsat data  down scaling  vegetation temperature condition index  median fusion model
Abstract:Vegetation temperature condition index (VTCI) is proved to be a quantitative drought monitoring approach by using the high temporal resolution remotely sensed data. However, with low temporal resolution data, the monitoring results are relatively wet and dry. A new model called the median fusion model (MFM) was developed for spatially down scaling the coarse spatial quantitative VTCI (1km) derived from the moderate resolution imaging spectroradiometer (MODIS) data products and the relative VTCI (30m) derived from the Landsat OLI/TIRS products in the Guanzhong Plain, China to a scale of the quantitative drought monitoring results (30m) called MFM-VTCI, and their quantifications were proved. The results showed that the good agreements between the MFM-VTCIs and the Landsat-VTCIs were found in terms of correlation coefficient and structural similarity index (SSIM) values, and the two VTCIs had similar spatial distribution and texture features. The root mean square error (RMSE) and the differences between the MFM-VTCIs and the Landsat-VTCIs were consistent with the systematic error between the quantitative drought monitoring results and the relatively wet and dry monitoring results, indicating that it was comparable between the MFM-VTCIs and the Landsat-VTCIs. The correlation coefficients between the MFM-VTCIs and the cumulative precipitation were similar to those between the MODIS-VTCIs and the cumulative precipitation, which were larger than those between the Landsat-VTCIs and the cumulative precipitation, indicating that the down scaled MFM-VTCIs were quantitative drought monitoring results.

Transactions of the Chinese Society for Agriculture Machinery (CSAM), in charged of China Association for Science and Technology (CAST), sponsored by CSAM and Chinese Academy of Agricultural Mechanization Science(CAAMS), started publication in 1957. It is the earliest interdisciplinary journal in Chinese which combines agricultural and engineering. It always closely grasps the development direction of agriculture engineering disciplines and the published papers represent the highest academic level of agriculture engineering in China. Currently, nearly 8,000 papers have been already published. There are around 3,000 papers contributed to the journal each year, but only around 600 of them will be accepted. Transactions of CSAM focuses on a wide range of agricultural machinery, irrigation, electronics, robotics, agro-products engineering, biological energy, agricultural structures and environment and more. Subjects in Transactions of the CSAM have been embodied by many internationally well-known index systems, such as: EI Compendex, CA, CSA, etc.

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