Application and Method for Rice Flooding Disaster Growth Diagnosis Analysis Based on HJ-CCD Data

来源 :The Sixth Asian Conference on Precision Agriculture (第六届亚洲精准 | 被引量 : 0次 | 上传用户:homejang
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  It has great significance to study quick monitoring of rice flood disaster and applying timely remedial measures in the disaster area.LAI is a very important physiological parameter in crop growth characterization index, which can objectively reflect the crop growing information.Remote sensing technology has the characteristics of rapid, nondestructive to obtain object information in large scale.It has many advantages compared with traditional manual method, but existing methods of flood monitoring using remote sensing technology rarely consider the damage and the post disaster growth of rice.The HJ-CCD data have advantages of high temporal resolution and high spatial resolution remote sensing image can be used for the crop growing information of the critical stage of rice.This paper is monitored the growth situation after rice flood disaster in Anhui province use 5 screens HJ-CCD data as the data source when were got 13th July, 18th July,26th ,19th August, 26th August, 2009, respectively).The semi empirical function model which is Beer-Lambert laws was constructed for this inversion Lai.And LAI were acquired in each stage after flood disaster, the trend of growth diagnosis dynamic change was analyzed, assessed by rice flood disaster evaluation indicator.At the same time, the 43 field investigate data was used to verify the model.The results show that LAI can be well evaluated the degree of rice flood disaster based on HJ-CCD data, and it is effective for monitoring and diagnosing rice flood disaster.The results can provide a theoretical basis for rice flood disaster research, post disaster rehabilitation and recovery.It can also provide a theoretical basis for the implementation of targeted remedial measures at the same time.
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