Hyperspectral Estimation Of Apple Tree Canopy Nitrogen,Chlorophyll And LAI Status

Hyperspectral remote sensing technology has the advantages of high spectral resolution, band continuity, and large amount of spectral information. It is able to estimate the physiological and ecological changes and nutritional status of the plants. Therefore, it has a unique advantage to the development of precision agriculture. Based on extraction and analysis of apple tree canopy spectral information, the purpose of this paper is to achieve the real-time, non-destructive monitoring of apple growth and nutritional status.In this study, Mengyin County was selected as the study area. Using a combination of quantitative methods of the ASD FieldSpec3spectroradiometer detection and laboratory experiments, based on the measuring of apple canopy spectral reflectance and leaf area index, collecting the Apple leaf samples at the same time and analyzing the apple leaf chlorophyll and nitrogen contents, the paper established of Nitrogen and growing indicators suitable spectral parameters and corresponding estimation model. The main conclusions were as follows:(1) Hyperspectral characteristics of the that spring shoots stopping growth period of apple canopy were initially found outThe hyperspectral curve of apple canopy was similar to the typical vegetation. In the400～700nm visible region, canopy spectral reflectance was mainly affected by the impact of chlorophyll. There was a reflection valley in blue and red regions and a reflection peak in green region. In the700～750nm, the spectral curve raised steeply. In the760～1300nm near-infrared region, due to the influence of canopy and leaf cell structure, spectral curve appeared "the infrared high level" within the existence of reflection valleys. In1560～2300nm, there were two peaks, mainly due to the impact of apple leaf water content and water content of the atmosphere. Depending on the moisture content of the atmosphere, the spectral curve dropped near1980nm. This spectral information provided a base for the further use of canopy reflectance spectrum monitoring apple tree growth conditions and nitrogen status.(2) Estimation model based on the nitrogen content of the apple canopy spectral characteristicsUse canopy spectral analysis technique to select sensitive bands related to the nitrogen content. Build various spectral parameters based on the sensitive spectral bands. Analyze the quantitative relationship of apple canopy nitrogen status and canopy reflectance spectral characteristics. Establish the nitrogen content of the sensitive spectral parameters and prediction equations. The apple canopy sensitive band in spring shoots stopped growth period mainly exists in the near-infrared platform and the visible region, where the red edge region was the most significant. The results showed that the optimal N content estimation models were N=2.070+1.448NDSI (1700,965) with vegetation index NDSI (1700,965) as the independent variable, N=1.96+2131.487R"717with R"717as the independent variable and N=1.999+1712.751R"717+1057.679R"976with R"171, R"976as the independent variable.(3) Proven the apple canopy LAI and hyper spectral parametersAccording to the correlation of apple canopy spectral characteristics and LAI, select the sensitive band of LAI. Use the linear regression analysis method to establish apple LAI estimation model. The results showed that, with the improvement of LAI, apple canopy spectral reflectance showed an increasing trend. The result showed that original spectrum753nm and the first derivation of732nm,564nm combination estimation models predict the best results. Judging from the built models, the original spectrum and the first derivative spectra estimate Apple LAI more accurately.(4)Relationship between the apple canopy chlorophyll content and hyper spectral parameters were found outChoose8vegetation indexes and construct sensitive band area within the two-band combination. Based on correlation analysis, modeling and accuracy test, determine the sensitive band region of apple canopy chlorophyll content was400to1350nm. By analyzing the relationship of vegetation indexes and the canopy chlorophyll content, determine the CCI index as independent variables estimation model is the best estimate model, which laid the foundation for the non-destructive testing of apple canopy chlorophyll content.The study founded out the apple canopy spectral characteristics in spring shoots growth period, discovered the hyperspectral mechanism and estimation model of apple canopy N content, chlorophyll content and leaf area index. It provides a fast and nondestructive method of estimating nutrient in apple tree, and offers a theoretical basis for the growth monitoring, nutrition diagnosis and yield estimation of apple tree using satellite remote sensing in the future.