白雪娇,王鹏新,张树誉,李俐,王蕾,解毅.基于VTCI空间尺度上推方法的干旱影响评估[J].农业机械学报,2017,48(2):172-178.
BAI Xuejiao,WANG Pengxin,ZHANG Shuyu,LI Li,WANG Lei,XIE Yi.Drought Impact Assessment Based on Spatial Up-scaling Methods of Vegetation Temperature Condition Index[J].Transactions of the Chinese Society for Agricultural Machinery,2017,48(2):172-178.
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基于VTCI空间尺度上推方法的干旱影响评估   [下载全文]
Drought Impact Assessment Based on Spatial Up-scaling Methods of Vegetation Temperature Condition Index   [Download Pdf][in English]
投稿时间:2016-06-16  修订日期:2017-02-10
DOI:10.6041/j.issn.1000-1298.2017.02.023
中文关键词:  条件植被温度指数  空间尺度上推  干旱影响评估  精度评价
基金项目:国家自然科学基金项目(41371390)
作者单位
白雪娇 中国农业大学信息与电气工程学院 
王鹏新 中国农业大学信息与电气工程学院 
张树誉 陕西省气象局 
李俐 中国农业大学信息与电气工程学院 
王蕾 中国农业大学信息与电气工程学院 
解毅 中国农业大学信息与电气工程学院 
中文摘要:基于关中平原Aqua MODIS 条件植被温度指数(VTCI)的干旱监测结果,分别采用分布式和聚合式的主导类变异权重法(DCVW)、算术平均值变异权重法(AAVW)和中值变异权重法(MPVW)对市域单元内VTCI进行空间尺度上推,以获取冬小麦主要生育期聚合后的加权VTCI;以加权VTCI与冬小麦产量间的回归分析精度为参考,选择最为合适的空间尺度上推方法。结果表明:采用分布式获得的加权VTCI与冬小麦产量的回归分析结果整体优于聚合式获得的结果。在分布式的上推过程中,MPVW获得的加权VTCI与冬小麦产量间的回归分析精度较低,DCVW和AAVW的精度均较高,其中DCVW获得的加权VTCI与冬小麦产量间回归分析的决定系数R2达0.64,精度最高,说明采用分布式DCVW对市域单元内VTCI进行空间尺度上推得到的加权VTCI最为合理。
BAI Xuejiao  WANG Pengxin  ZHANG Shuyu  LI Li  WANG Lei  XIE Yi
College of Information and Electrical Engineering, China Agricultural University,College of Information and Electrical Engineering, China Agricultural University,Shaanxi Provincial Meteorological Bureau,College of Information and Electrical Engineering, China Agricultural University,College of Information and Electrical Engineering, China Agricultural University and College of Information and Electrical Engineering, China Agricultural University
Key Words:vegetation temperature condition index  spatial up-scaling  drought impact assessment  precision evaluation
Abstract:Up-scaling method for inferring spatial information from a pixel scale to a basic unit scale has significant effects on aggregating results and decision-making. Therefore, developing appropriate methods to accurately up-scale spatial data is the key to infer useful drought information. The time series of vegetation temperature condition index (VTCI) drought monitoring results in Guanzhong Plain from early March to late May in the years from 2008 to 2013 were spatially transformed from a pixel scale to a basic unit scale by using the dominant class variability-weighted method (DCVW), arithmetic average variability-weighted method (AAVW) and median pixel variability-weighted method (MPVW) in the distributed mode and aggregated mode to obtain the aggregated VTCIs. The weighted VTCIs of winter wheat in main growth period were calculated, and the regression analysis between the weighted VTCIs and winter wheat yields was applied as references to evaluate up-scaling methods. The results showed that the regression analysis results of the three methods in the distributed up-scaling mode were generally better than those in the aggregated up scaling mode. The regression analysis results in the distributed up-scaling mode also indicated that the computing accuracy was high by DCVW and AAVW and was low by MPVW. DCVW in the distributed up-scaling mode was the most accurate method with the highest determination coefficient and the lowest estimated standard error, which were 0.64 and 289.97kg/hm2, respectively. The estimation yields of winter wheat which obtained by DCVW were very close to the levels of statistics yearbook of Shaanxi Province, indicating that the estimation precision of DCVW mehtod was high, and the method was robust. Overall, the method of DCVW in distributed up-scaling mode was the most reasonable approach to up-scale VTCIs in Guanzhong Plain from a pixel scale to a basic unit scale.

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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