刘哲,刘玮,昝糈莉,封伟,李绍明,张晓东.基于多年环境特征的东北春玉米时空型种植区划研究[J].农业机械学报,2017,48(6):125-131.
LIU Zhe,LIU Wei,ZAN Xuli,FENG Wei,LI Shaoming,ZHANG Xiaodong.Temporal and Spatial Planting Regionalization Description of Spring Maize in Northeast China Based on Several Years Environmental Characteristics[J].Transactions of the Chinese Society for Agricultural Machinery,2017,48(6):125-131.
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基于多年环境特征的东北春玉米时空型种植区划研究   [下载全文]
Temporal and Spatial Planting Regionalization Description of Spring Maize in Northeast China Based on Several Years Environmental Characteristics   [Download Pdf][in English]
投稿时间:2016-10-14  
DOI:10.6041/j.issn.1000-1298.2017.06.016
中文关键词:  玉米种植环境  多环境测试  空间型区划  时空型区划  类别归属度
基金项目:国家自然科学基金青年项目(41301075)
作者单位
刘哲 中国农业大学信息与电气工程学院 
刘玮 中国农业大学信息与电气工程学院 
昝糈莉 中国农业大学信息与电气工程学院 
封伟 中国农业大学信息与电气工程学院 
李绍明 中国农业大学信息与电气工程学院 
张晓东 中国农业大学信息与电气工程学院 
中文摘要:玉米是我国主要粮食作物之一,现有的玉米种植环境区划受尺度过大的影响,分区环境特征不能满足品种精细测试要求,只用多年平均值描述环境空间特征,对于多环境测试中的环境不能充分地认知。为此,以地理网格为单元,以东北三省为研究区,利用东北三省21年的气象、DEM、坡度和县域春玉米种植面积等数据,以每年的环境特征为指标,构建多年环境特征数据库,通过属性聚类方法,从时空角度研究玉米种植环境精细区划方法,将东北三省的多年环境特征分成7类,使用类别归属度分析方法,实现东北三省玉米种植环境时空型区划。与多年环境特征均值的空间型区划对比结果表明,时空型区划结果更加精细,环境认知更加充分。
LIU Zhe  LIU Wei  ZAN Xuli  FENG Wei  LI Shaoming  ZHANG Xiaodong
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,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:maize planting environment  multiple environment test  spatial regionalization  spatial temporal regionalization  belonging degree for category
Abstract:Maize is one of the main food crops in China. Due to too much scales of maize environmental regionalization description, the partition environmental characteristics are not satisfied with the test requirements of the fine varieties, and only using several years average values to describe the spatial characteristics of the environment can not enough recognize the multiple environment test of the environment. The geographical grid was taken as the unit, and the three northeastern provinces as the study area. By using the 21 year meteorological data, DEM, slope and the planting area of spring maize in the three provinces of Northeast China, the every year environment characteristic was used as index to build a multi year environmental characteristic mean database and a several years environment characteristics database. From the temporal and spatial perspective, the attribute clustering method was used to research a maize environment fine division method. The result was that the environmental characteristics of the three provinces in Northeast China were divided into seven categories. The regionalization of maize planting environment in the three provinces of Northeast China was carried out by using the belonging degree analysis method for category, and compared with the spatial regionalization of the mean value of environmental characteristics for many years, the result of spatial temporal regionalization was more precise and the environmental cognition was more full.

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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