Maize Information Inversion And Yield Estimation A Plain Along The Yellow River In Inner Mongolia Based On MODIS And UAV

In order to obtain agricultural information along the Yellow Plain of Inner Mongolia and improve the efficiency and accuracy of agricultural remote sensing technology,this paper took the Yellow Plain of Inner Mongolia as the research area,and analyzed the planting structure by using MODIS remote sensing images of large regional and large scale.On this basis,multi-spectral unmanned aerial vehicle was used to extract agricultural information and estimate the yield of the corn with the largest planting area in the research area in small regions and at small scales.The main research contents and conclusions are as follows:(1)The MODIS-EVI time series curve was used to explore the distribution of six major crops in the study area.The user accuracy of wheat,corn,sunflower,zucchini,tomato,alfalfa and other crops is 79.59%,80%,83.67%,78.18%,75.93%,82.22%,68.75%,and the mapping accuracy is 78%,80%,82%,86%,82%,74%,66%.The overall classification accuracy of crops reached 78.29%,the Kappa coefficient was0.747,and the relative error between the corn with the largest planting area and the actual statistics was 6.31%.It is proved that EVI time series classification method has strong applicability to identify crops in large area and large scale.(2)Using threshold segmentation and change monitoring technology,vegetation coverage and different growth periods were extracted.The results showed that the vegetation coverage of maize test plots on August 27,September 7,September 20 and November 1 were 76.30%,66.61%,29.17%and 5.08%,respectively.The decrease area of NDVI in maize trial plots from August 27 to September 8,from September 8to September 20,and from September 20 to November 1 accounted for 74.64%,81.62%and 73.83%of the total area of maize trial plots,respectively.Combined with the vegetation coverage and different growth stages,the period from September 8 to September 20 was the period of the fastest decay of maize form.(3)According to the reflectance of the five bands,the two bands with the highest correlation with the chlorophyll content of corn leaves were selected to establish the equation.The determination coefficient R~2was 0.78 for the extraction of the chlorophyll content of corn leaves,which proved that the method of establishing the regression equation with the two bands with the highest correlation could achieve the extraction of the chlorophyll content of corn.Then,the leaf chlorophyll content was used to indirectly extract the total nitrogen content of corn,and the determination coefficient R~2was 0.71,indicating that when the nutrient content of crops was difficult to extract,the regression relationship between nutrient elements and information that could be easily extracted could be established to realize the indirect extraction of nutrient elements.Finally,two bands with the highest correlation with LAI were selected and transformed into vegetation index as the dependent variable to extract LAI through mathematical processing.The determination coefficient R~2was0.82,which proved that vegetation index was more accurate than single band to detect vegetation growth.(4)Compare the physiological information,single phase vegetation index NDVI,long phase accuracy of yield estimation model,found that when the single phase vegetation index and physiological information compared to yield estimation model accuracy has improved significantly,long phase of uav remote sensing yield estimation and is superior to the single phase,and the most scientific,but too much when combined to increase the complexity of the model.In this paper,NDVI 3 time phase production estimation model is the most reasonable.