Design And Implementation Of Forestry Informatization System Based On Cloud Platform

This thesis studies the forestry information system based on the cloud platform,and introduces the forestry informatization system as an example to the Xunhan Ula ecological station cloud platform,which has certain value and research value.The system design is mainly completed for a large number of scattered data storage management and processing visualization.Through the combination with the cloud platform,to play the advantages of large data to improve the utilization of forestry information to promote forestry development.This thesis designs a series of internal working systems for the daily work of the users by analyzing the users of Saihanwula ecological station and the actual data form.In order to allow users to centrally manage the scattered data.And through a large number of data visual display,so that users at any time on the macro changes in the data have a general understanding of the user to facilitate the user according to the trend of changes in forestry data to draw conclusions.Through the excel table to read the download information query and other functions,but also to meet the user's basic needs for data storage retrieval.HBase as the underlying database,the use of its distributed storage features to facilitate the storage of large amounts of data,and located on the Hadoop platform can use the platform for a large number of data processing speed advantage to meet the user's data processing and analysis needs.Excel tables are available in a variety of data formats and can be customized for different table data formats.Therefore,the system can be more convenient to complement the function to enhance.The forestry information system is still in the exploratory stage,the system in the face of complex network environment and data information complexity has yet to be tested.And the analysis of forestry data in the system has yet to be further communicated with forestry industry experts in order to arrive at more intuitive conclusions through large data analysis.Helping non-professional users to understand the impact of changes in forest information on trees is more straightforward.