Method for Spatializing Temperature Suitability Index Based on CLDAS
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Abstract:
In order to avoid the errors of the site observation data during the spatial interpolation and improve the accuracy of the spatialization on corn temperature suitability index, the CMA Land Data Assimilation System is used, which applies hourly temperature data. The daily temperature suitability index calculation model is set up in the space, which is based on the corn dynamic suitability calculation method of Inner Mongolia by using of GIS spatial analysis and Model Builder. The temperature suitability dynamic model requires inputting date that is used to calculate the spatial distribution of temperature indicators, such as optimum temperature, maximum temperature, and minimum temperature. Combining with the spatial distribution of the average daily temperature of CLDAS, the temperature suitability index is calculated on the space by using condition functions. Regular site suitability and model calculation results are compared from May to August 2015 as an example. The results show that the maximum absolute error is 0156, and the absolute error of about 90% results is less than 01 The maximum relative error is 369%, and the relative error of about 70% results is less than 8%. CLDAS data can reflect the influence of high temperature in May and low temperature in August, in which suitability index is 0 By using the Model Builder, the constructed calculation model of suitability index has higher practicability. Based on CLDAS temperature data, the temperature suitability index error is relatively small, and the precision of the spatialization can be used for further researches.
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Supported by:Beijing E-Tiller Technology Development Co., Ltd.
Supported by:Beijing E-Tiller Technology Development Co., Ltd.