标题:
Hadoop平台下森林大气温度与地表温度关联研究Research on Relevance between Atmospheric Temperature and Surface Temperature inForests Based on Hadoop
作者:
杨博文, 汪子炎, 荀文婧, 刘晓峰, 朱正礼
关键字:
云计算, 大数据, 物联网, Hadoop, MapReduceCloud Computing, Big Data, Internet of Things, Hadoop, MapReduce
期刊名称:
《Hans Journal of Wireless Communications》, Vol.6 No.3, 2016-06-28
摘要:
本文基于南京紫金山地区森林关于大气温度、地表下5 cm处的土壤温度的大数据，对传统的数据分析方法作出改进，提出了用云计算对林业物联网数据进行分析的方法，运用Alphabet公司的Hadoop云计算平台的MapReduce大数据处理框架，研究大气温度和地表下5 cm处的土壤温度间的关系。本文利用Hadoop云计算平台下的MapReduce框架对林业物联网大数据进行数据处理，并利用MATLAB软件对两者进行分析研究，进而研究大气温度对地表温度的影响。地表温度在植物生长、气候学、生物化学研究中具有重要的意义，在农业气象中有重要的应用价值。
Base on the big data about the atmospheric temperature and surface temperature in the forest of Purple Mountain in Nanjing, the paper proposes a method to analyze the data of forestry Internet of things by the cloud computing. The paper uses Alphabet’s Hadoop cloud computing platform to analyze these data, and studies the relationship between atmospheric temperature and surface temperature. Framework of the MapReduce is used to carry out the data of the sensor data processing. Then, we use MATLAB to analyze the relationship between atmospheric temperature and surface temperature. Land surface temperature is considered of strategic importance in the field of plant growth, climatology, and biological research, and it also has important value in Agri-cultural Meteorology.