Extraction And Spatio-temporal Analysis Of Winter Wheat Phenology Based On Time Window And EVI Amplitude Index

The phenological phenomenon of vegetation is the most intuitive and sensitive comprehensive indicator of the seasonal and interannual changes of environmental conditions.It is an important material to study the relationship between vegetation and climate and environmental changes.Its dynamic changes reflect how climate change affects the growth and development of crops.It is an indicator of the effects of climate change on the agricultural ecosystem..Crop phenological information plays a vital role in crop yield estimation and management.Monitoring seasonal changes in vegetation activities in large areas and Crop Phenology are of great significance for many applications,such as the estimation of net primary productivity,determining the boundary conditions for crop yield modeling,providing decision support for water supply.Hold.Phenology as an important input parameter in the crop growth model has an important influence on the accuracy of the simulation results.Winter wheat,as the most important grain in China,is a timely and accurate mapping of winter wheat,which is of great significance for food security and environmental sustainability.The advance or delay of winter wheat's key phenology is the direct response of winter wheat to climate change and production management measures.It is very necessary to grasp the information of winter wheat phenology to realize the monitoring of winter wheat growth.It is also one of the requirements of precision agriculture.Taking the main winter wheat production areas of the North China Plain as the research area,using the MODIS 250 meters daily EVI data,and the cultivated land vector data in the study area,the winter wheat planting area based on the time window and EVI amplitude index is carried out in view of the difficulty in identifying the planting area of winter wheat and the low extraction precision of the phenological parameters.And the acquisition of key phenological parameters.First,the paper selected the image data of the main winter wheat growth period(September-June),filled the missing data,constructed the time series data and smoothed it with Savitzky-Golay(S-G)filtering,and then proposed the winter wheat extraction based on the time window and EVI amplitude index,which utlized the typical characteristics of the winter wheat growth period in the EVI curve.The method was to solve the winter wheat and its partial phenological parameters,and then combined with the planting area of winter wheat,the location based method for the sowing time of winter wheat was put forward,and the sowing time was solved.Finally,the time and space of the sowing time,maturity and growth period of winter wheat in the main winter wheat planting areas were carried out.Change analysis.The main contents and conclusions of the thesis are as follows:(1)A method of extracting winter wheat and phenological parameters based on time window and EVI amplitude index.Compared with the 8 day/16 days data,the daily data brought more noise to the time series,but after smoothing the data through the S-G filter,the data was successfully extracted and the key phenological parameters of the winter wheat were solved,and the high accuracy was obtained.By obtaining the key points on the vegetation growth curve of the winter wheat time series,the EVI amplitude parameter was constructed,and the "double hump" characteristic in the growth curve was amplified by the EVI amplitude parameter,and the winter wheat was distinguished from other crop types by the restriction of time and other information.By analyzing the precision of the planting area of winter wheat,the relative precision of the area extraction of winter wheat can be up to 85.67%.Compared with the meteorological station observation data,the accuracy of the seedling period,the heading stage and the maturity period is high compared with the reference data,and 79%of the phenological parameters are extracted.The accuracy is within 4 days,which proves the validity of the method proposed in this paper.(2)The method of solving sowing time based on position information.The linear fitting of the seedling and sowing dates in the provinces/municipalities directly from the provinces/municipalities directly under the central government is calculated,and then the time for the seeding period of the seedling period is obtained.The experimental results show that the seeding time of this method is very high,and the accuracy of 81.5%is within 4.The experimental results show that the method of solving the winter wheat sowing time with location information can overcome the shortcomings of the traditional method of solving the sowing time based on "distance",and it has a high adaptability in the large scope of the study area.(3)Spatial and temporal variation of winter wheat phenology.The sowing time of winter wheat is inversely proportional to the relative latitude,and the sowing time gradually decreases with the increase of latitude,and with the increase of the year,the time of sowing time has a tendency to postpone,and the maturity date of winter wheat becomes late with the increase of latitude,and as the time goes on,the mature date has a backward trend.The length of growth period showed an increasing trend with latitude increasing,but the length of growth cycle remained unchanged throughout the whole research period.Phenological changes in winter wheat phenology have obvious spatial and temporal characteristics in 10 years.