Extraction Of Winter Wheat Area In County Scale And The Main Growth Parameters Estimating At Jointing Stage

Foodsecurity is an industry to stabilize the masses and pacify the people.The current shortage of rural labor in China,the decrease of the amount of arable land,and the low comprehensive production efficiency of food crops have led to a lack of enthusiasm for farmers to grow grain.The decrease of sowing area and yield of the grain crops will definitely threaten national food security.Based on satellite remote sensing,3S technology can quickly,accurately and macroscopically acquire ground information,and realize the collection and analysis of agricultural information.What’s more,it has strong objectivity and low cost and is not limited by ground conditions,which is convenient to agricultural decision-making.Wenxi is a large wheat production county in Shanxi Province.It has important reference significance for the government to formulate food production policies about spatial layout and area extraction of winter wheat,and remote sensing monitoring of growth parameters.At present,there have been many researches on the identification of winter wheat planting areas and estimation of growth parameters using remote sensing technology at home and abroad,but few of these related to rain-fed and irrigated winter wheat.This study takes rain-cultivated and irrigated winter wheat as the research object,takes Wenxi County as the research area,takes Sentinel-2 satellite data as the remote sensing data source.Generated NDVI time-series curves on the basis of time series remote sensing images firstly,this study chose time windows,and calculated the thresholds of classification,next constructed a classification decision tree to extract winter wheat planting areas of rain-fed land and irrigated land and analyzed their spatial distribution information.On the basis of that,the study combined the data of field survey with Sentinel-2 satellite image data during the jointing stage to construct the remote sensing estimation models of main growth parameters such as LAI,SPAD and biomass.Precision verification and spatial inversion were carried out in the end of the research.The purpose of this study is to provide overall information and theoretical support for the decision of high yield and high quality of winter wheat and agronomic water and fertilizer treatment.The main findings are as follows:1)The decision tree classification method can fully extracted the planting area of winter wheat in rain-fed and irrigated land,which based on multitemporal Sentinel-2 remote sensing image data and phenological information of winter wheat.The best time-phase combination for identifying winter wheat planting area was 12.12,4.16,6.10.The winter wheat in Wenxi County was mainly distributed in the central and southern regions of the county,and the winter wheat planting area in the northwest and east was small and scattered,among which the rain-fed winter wheat was mainly distributed in the western,northern margins and eastern mountainous regions,and the irrigated winter wheat was mainly distributed in the central river valley basin area.2)The total planting area of winter wheat extracted in Wenxi County in this study is 36714.42 hm2,of which the extraction area of rain-fed winter wheat is 11622.82 hm2,and the extraction area of winter wheat in irrigated area is 25091.60 hm2.The quantitative extraction accuracy of winter wheat planting area is89.87%,and the spatial matching accuracy is 94 %.The quantitative extraction accuracy of winter wheat in rain-cultivated land is 85.34%,and the spatial matching accuracy is 92%;where in the irrigated land the value is 92.13%,and the spatial matching accuracy is 96%.The extraction accuracy in rain-fed land was lower than its in irrigated winter wheat land.3)The optimal anti-evolution amount of different growth parameters is different.The SPAD value estimated by the MERIS Terrestrial chlorophyll index has the highest accuracy.In the inversion of the LAI value of the leaf area index,NDVIre has the best inversion accuracy.The biomass has the highest fitting accuracy with CIre.The addition of the red edge band can improve the inversion accuracy of the model and alleviate the saturation effect of the vegetation index to a certain extent.4)It is feasible to use Sentinel-2 satellite spectral data to monitor the main growth parameters of winter wheat rainfed irrigated land.The distribution of winter wheat in the irrigated land was more concentrated than that in the rain-fed land,and the field management is moderate,and the model fits well;while the rain-fed land is scattered,the water and fertilizer conditions vary widely,and the model fits poorly.