北京市农林科学院机构知识库

Based on HJ-CCD image to monitoring degree of corn tasseling

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文献类型：外文期刊

作者： Wang, Huifang ¹ ; Wang, Jihua ¹ ; Gu, Xiaohe ¹ ; Guo, Wei ¹ ; Huang, Wenjiang ¹ ; Wang, Huifang ¹ ; Wang, Jihua ¹ ;

作者机构： 1.Beijing Res Ctr Informat Technol Agr, Beijing, Peoples R China

2.Zhejiang Univ, Inst Agr Remote Sensing & Informat Syst Applicat, Hangzhou, Peoples R China

关键词： Remote Sensing;MLR;Corn Tasseling;HJ Data

期刊名称：2012 FIRST INTERNATIONAL CONFERENCE ON AGRO-GEOINFORMATICS (AGRO-GEOINFORMATICS)

ISSN： 2334-3168

年卷期： 2012 年

页码：

收录情况： SCI

摘要： Heading stage is the key stage of corn in whole growth phase, degree of corn tasseling directly related to the yield and quality in heading stage. Remote sensing data in the reflective optical domain function as a unique cost-effective source for providing spatially and temporally distributed information on key biophysical and biochemical parameters of vegetation. Based on remote sensing data to acquire the degree of the corn tasseling imformation and make field management measures in critical growing stage of corn which is an important application subject in precision agriculture, especially crop phenology monitoring application requirements of precision agriculture is increasingly urgent. The aim of this article was to establish the relationship between degree of the corn tassteling and vegetation index from satellite image. This study research object was corn in Gongzhuling and Nongan of Jinlin Province, A data mining approach based on HJ-CCD data to modeling the corn tasseling and mapping its spatial distribution in heading stage was presented. Firstly extracted the vegetation indices from HJ-CCD image data, and the response relationship were analyzed between degree of tasseling and vegetation indices. Secondly a MLR (multiple line regression) model was established, the vegetation indices (VIgreen) was significantly correctly to the corn degree of tasseling at the heading stage (R-2=0.544). Thirdly the monitoring model accuracy was verified. It acquired a high accuracy (R-2=0.502). In general, the result showed that puts forward based on HJ-CCD remote sensing data can monitoring the degree of corn tasseling and distribution, and The indigenous remote sensing data which owned the advantages as the higher revisit frequency and wide scene swath are able to satisfy monitoring and assessing corn tasseling. It will lay a theoretical basis on monitoring and identifying the degree of the tasseling. It makes utmost to achieve more per ear harvest of looks in the field of management in the key growth stage.

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