Spatio-temporal Analysis Of Wheat-meteorological-harvester Working Time And The Data Platform Development

Wheat is one of the main food crops in China.Different regions have different wheat growth period.Wheat harvesting production during different maturity periods are different,which makes the wheat production distribution spatio-temporally heterogeneous.In recent years,China’s wheat production and total power of agricultural machinery have shown a trend of increasing year by year.The difference in wheat maturity of different regions has led to the phenomenon of cross-regional operation of wheat harvesters.The increase in the number of cross-regional combine harvesters has led to an ever-expanding range of operations,which has led to premature or delayed inter-regional operations,resulting in economic losses.At present,the agricultural machinery intelligent management,operation,maintenance management and operation management information are relatively isolated,so there is a lack of comprehensive basis for operational intelligent decision-making and management.Different wheat planting areas are affected by various factors such as spatial region,meteorological environment,crop production and mechanical operation capacity.The prediction of the number of harvesters in the region has certain complexity and uncertainty.This paper takes wheat as the research object,using spatial statistics,machine learning,data mining and other techniques to conduct a preliminary study on the spatiotemporal fluctuation of wheat production during 2002-2009 and the field working time of harvester during the harvest period.Based on wheat data,meteorological environment data and agricultural machinery work data,the main research contents and conclusions of the “wheat-meteorological-harvester” information visualization platform are as follows:1.A local Moran index spatial statistics based on semi-variogram was designed to quantitatively evaluate the spatial correlation of production in wheat producing areas.During the period of 2002-2009,China’s wheat was mainly distributed in the northern part of East China and Central South China.The production area mainly harvested winter wheat in May and June and harvested spring wheat in July and August.The global Moran index of wheat yield in the main producing areas is greater than 0,with significant spatial correlation.The wheat production in the main producing areas has the characteristics of increasing,spatial accumulation and stability year by year.2.A piecewise linear regression model based on decision tree was established to predict the number of days which agricultural machine can work in the wheat producing area during the harvest period.According to the optimal field working time prediction model,during the period of 2002-2009,the field working days in the wheat harvest period(22-24 weeks)of Henan,Shandong,Anhui,and Jiangsu provinces were range from 3.7 to 4.2 days.3.A “wheat-meteorological-harvester” multi-source data visualization platform was established for the storage,display,management and inquiry function of wheat,meteorology,harvester and other data.The platform can also show the predicted results of the harvester’s suitable field working time.