Yubin Lan

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  • Chenghai Yang, John K Westbrook, Charles P, C Suh, Daniel E Martin, W Clint Hoffmann +4 others
  • 2014
This paper describes the design and evaluation of an airborne multispectral imaging system based on two identical consumer-grade cameras for agricultural remote sensing. The cameras are equipped with a full-frame complementary metal oxide semiconductor (CMOS) sensor with 5616 × 3744 pixels. One camera captures normal color images, while the other is(More)
The brown rice plant hopper (BRPH), Nilaparvata lugens (Stal), is one of the most important insect pests affecting rice and causes serious damage to the yield and quality of rice plants in Asia. This study used bionic electronic nose technology to sample BRPH volatiles, which vary in age and amount. Principal component analysis (PCA), linear discrimination(More)
Water productivity (WP) is a key element of agricultural water management in agricultural irrigated regions. The objectives of this study were: (i) to estimate biomass of winter wheat using spectral indices; (ii) integrate the estimation of biomass data with the AquaCrop model using a lookup table for higher accuracy biomass simulation; (iii) show(More)
Leaf area index (LAI) and biomass are frequently used target variables for agricultural and ecological remote sensing applications. Ground measurements of winter wheat LAI and biomass were made from March to May 2014 in the Yangling district, Shaanxi, Northwest China. The corresponding remotely sensed data were obtained from the earth-observation satellites(More)
Principal Component Analysis (PCA) is one of the main methods used for electronic nose pattern recognition. However, poor classification performance is common in classification and recognition when using regular PCA. This paper aims to improve the classification performance of regular PCA based on the existing Wilks Λ-statistic (i.e., combined PCA with the(More)
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