Modern breeding technologies are capable of producing hundreds of new varieties daily, so fast, simple and effective methods for screening valuable candidate plant materials are urgently needed. Final yield is a significant agricultural trait in rice breeding. In the screening and evaluation of the rice varieties, measuring and evaluating rice yield is essential. Conventional means of measuring rice yield mainly depend on manual determination, which is tedious, labor-intensive, subjective and error-prone, especially when large-scale plants were to be investigated. This paper presented an in vivo, automatic and high-throughput method to estimate the yield of individual pot-grown rice plant using multi-angle RGB imaging and image analysis. In this work, we demonstrated a new idea of estimating rice yield from projected panicle area, projected area of leaf and stem and fractal dimension. 5-fold cross validation showed that the predictive error was 7.45%. The constructed model achieved promising results on rice plants grown both in-door and out-door. The presented work has the potential of accelerating yield estimation and would be a promising impetus for plant phenomics.

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Computer and Computing Technologies in Agriculture VIII

In order to shorten the revisit period, and improve the efficiency of imaging, currently, all the in orbit high resolution remote sensing satellites adopt side-view imaging technology. When satellites imaging with a side perspective, it would inevitably cause the degradation of image quality, like spatial resolution reduction, image deformation incensement, and the reduction of positioning accuracy. In addition, with the increase of the side perspective, the error of DEM data will be amplified in the process of ortho-rectification, which, thus, will bring bigger error for image mapping accuracy. To address this problem, embarked from the impact of side view and DEM precision on image point error, this paper used Quick bird image data of the same area but different side perspectives, and simulate the impacts of different DEM elevation error on different side view image. At last we put forward a method to determine the maximum side perspective with map precision constraints, and set up a conversion relationship among satellite side view, DEM error and image point error. Finally, the paper combines the errors of 1:50000 DEM, ASTERGDEM and the requirement of ortho-image drawing, discusses and gives the values of maximum side perspective in the mountains and plains.

/pdf/a-method-to-determine-the-maximum-side-perspective-of-4vmijvp1x1.pdf

A Method to Determine the Maximum Side Perspective of Satellite with the Constraints of Mapping Accuracy

This paper introduces some technique of Quickbird,that includes Layer Stack,Resolution Merge,Radiometric Enhancement,Nature Color's Transformation and so on.It primary expounds the method of Quickbird's Orthocorrection,precision analysis,application to updating technique of relief map and spatial data.

Shi Yuhua

Papers

Research of Quickbird Image on Orthocorrection and Updating of Relief Map