Low-Temperature and Frost Risk Division of Olive in FuJian Province Based on GIS

2011 International Conference on Computer Distributed Control and Intelligent Environmental Monitoring Pub Date : 2011-04-11 DOI:10.1109/CDCIEM.2011.389

Chen Jiajin, W. Jiayi, Mao Zhiguo, Lin Jing, Yang Kai, L. Lichun

{"title":"Low-Temperature and Frost Risk Division of Olive in FuJian Province Based on GIS","authors":"Chen Jiajin, W. Jiayi, Mao Zhiguo, Lin Jing, Yang Kai, L. Lichun","doi":"10.1109/CDCIEM.2011.389","DOIUrl":null,"url":null,"abstract":"According the low-temperature (Td) data of 60years from 1950/1951 to 2009-2010 in Fujian Province, geographic information, olive planting area, cut rates of yield and the farmer¡¯s net income, the low-temperature frost risk division of olive plant is done based on GIS technology, expert grading method, mathematical statistics and so on. The mainly indexes include the four factors of hazard, exposure, vulnerability and disaster prevention and reduction capability those combined results of the natural disaster risk, and the olive comprehensive risk assessment index is made of them to forming a division map of olive low-temperature and frost. The mainly results as follows: The risk factors of distribution are an uneven distribution. It is high low-temperature and frost risk region in County of Minqing, Shan hang, and YouXi, and the risk index reached 0.7418, 0.5818, 0.51, the olive can develop in those areas that are FuZhou south coast, PuTi an, QuanZhou and the most parts of ZhangZhou in Fujian Province.","PeriodicalId":6328,"journal":{"name":"2011 International Conference on Computer Distributed Control and Intelligent Environmental Monitoring","volume":"67 1","pages":"1585-1588"},"PeriodicalIF":0.0000,"publicationDate":"2011-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 International Conference on Computer Distributed Control and Intelligent Environmental Monitoring","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CDCIEM.2011.389","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 0

Abstract

According the low-temperature (Td) data of 60years from 1950/1951 to 2009-2010 in Fujian Province, geographic information, olive planting area, cut rates of yield and the farmer¡¯s net income, the low-temperature frost risk division of olive plant is done based on GIS technology, expert grading method, mathematical statistics and so on. The mainly indexes include the four factors of hazard, exposure, vulnerability and disaster prevention and reduction capability those combined results of the natural disaster risk, and the olive comprehensive risk assessment index is made of them to forming a division map of olive low-temperature and frost. The mainly results as follows: The risk factors of distribution are an uneven distribution. It is high low-temperature and frost risk region in County of Minqing, Shan hang, and YouXi, and the risk index reached 0.7418, 0.5818, 0.51, the olive can develop in those areas that are FuZhou south coast, PuTi an, QuanZhou and the most parts of ZhangZhou in Fujian Province.

查看原文本刊更多论文

基于GIS的福建省橄榄低温霜冻风险区划

根据福建省1950/1951年至2009-2010年60年的低温(Td)数据、地理信息、橄榄树种植面积、减产率和农民纯收入，采用GIS技术、专家分级法、数理统计等方法对橄榄树低温霜冻风险进行了划分。主要指标包括危险度、暴露度、易损性和防灾减灾能力这四个自然灾害风险综合结果，并以此构成橄榄综合风险评价指标，形成橄榄低温霜冻分区图。主要结果如下:风险因素分布不均匀。闽清县、山航县、油溪县为高低温霜冻风险区，风险指数分别为0.7418、0.5818、0.51，在福建省福州市南沿海、莆田县、泉州及漳州大部分地区均可生长。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

2011 International Conference on Computer Distributed Control and Intelligent Environmental Monitoring

自引率

0.00%

发文量