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Timely and accurate estimation of rice planting area would greatly optimize our prediction of rice production, which provides invaluable information for government in formulating policies with regard to national food security. Previous studies have shown great potential of optical remote sensing as an effective way to map rice planting area. Commonly used classification techniques, which mainly focus...
The accurate prediction of crop yield is of great importance to regional production and food security. Many empirical models for crop production prediction are based on vegetation indices (VI) such as normalized vegetation index (NDVI) or simple ratio (SR) in specific growing period, with little attention paid to the sensitivity of different growing stages to yield prediction. This study investigates...
It is critical to estimate the biomass for assessing crop growth and predicting yield in crop. The hyperspectral techniques provide a powerful technique for monitoring crop biomass. The previous studies about using hyperspectral data to study crop mainly focused on models based on the full spectra or the manually selected spectra. The stability and prediction ability of full spectra models may be...
UAV based hyperspectral imaging is a promising approach to monitor crop growth status rapidly and non-destructively. This paper described a novel instrument to get hyperspectral information from lightweight unmanned aerial vehicles for crop monitoring. The objectives of this study were to assess the data quality of one hyperspectral frame camera and evaluate the ability in rice nitrogen status monitoring...
Unmanned Aerial Vehicles (UAV)-based remote sensing offers great possibilities to acquire in a fast and convenient way field data for precision agriculture applications. The UAV-based multispectral images with five wavebands (490, 550, 671, 700, 800 nm) were obtained at five growth stages from consecutive two years' wheat field experiments with different combinations in variety, N application rate...
The effect of canopy structure on the remote sensing of foliar nitrogen content has been debated in recent years, due to the uncertain mechanism of estimating foliar nitrogen content through canopy reflectance in the near-infrared region. Although this effect was investigated using the radiative transfer modeling of canopy structural influence, the complicated modeling implementation is still of limited...
The red edge position (REP) of a reflectance spectrum has been used as means to estimate the foliar chlorophyll content at leaf and canopy level. Most methods for extracting the REPs are based on the first derivative spectra and many studies have shown discontinuities in the REP data due to the existence of a double-peak feature in the first derivative spectra. This study proposes a new technique...
Recent studies have debated over the effect of canopy structure on the remote sensing of foliar nitrogen content. Although previous work reported on the radiative transfer modeling of canopy structural influence, the modeling implementation is still of limited use in the hyperspectral community. This study proposes to use a multi-scale tool, continuous wavelet analysis, to decompose the spectral responses...
The study on the agriculture model component information resources sharing mode is the basis for the retrieval and management of the agriculture model components in the distributed environment. This study proposed a new approach to use topic map matching and merging to generate the global model documents. First of all, it unified described the attributes, associations and file descriptive information...
The study on the crop growth model parallel algorithm is help to improve the computing efficiency of models in the low-cost PC cluster environment. According to the positive feedback characteristic of the crop development simulation model, this study used the partitioning and pipelining technology, and raised the two parallel algorithms, which are the single-node parallel job scheduling algorithm...
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