Agriculture Big Data Analysis System Based on Korean Market Information

Abstract

As the world's population grows, how to maintain the food supply is becoming a bigger problem. Now and in the future, big data will play a major role in decision making in the agriculture industry. The challenge is how to obtain valuable information to help us make future decisions. Big data helps us to see history clearer, to obtain hidden values, and make the right decisions for the government and farmers. To contribute to solving this challenge, we developed the Agriculture Big Data Analysis System. The system consists of agricultural big data collection, big data analysis, and big data visualization. First, we collected structured data like price, climate, yield, etc., and unstructured data, such as news, blogs, TV programs, etc. Using the data that we collected, we implement prediction algorithms like ARIMA, Decision Tree, LDA, and LSTM to show the results in data visualizations.

Ecological Strategies for Rural Nature Conservation Environment Based on Big Data Information System

“…Raster/vector data structure, this structure form is usually the most used one spatial data structure model, this hybrid structure model has two benefits, the first is to make the spatial information and attribute information related to both vector data and raster data expressed accurately, it is necessary to establish a form of mathematical expression, i.e., spatial topological relationship and discrete; the other is he can be very fast processing data. So in this paper the structure used for the organization of the rural environment database in a grouped and hierarchical directory way is the raster/vector data structure [15,16].…”