基于多源遥感数据的伊通县2007 - 2017年玉米产量估算

Yibo Wang, Xue Wang, Kun Tan, Yu Chen, Kailei Xu
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引用次数: 0

摘要

随着遥感技术的发展,利用多空间和多光谱分辨率遥感影像对农作物生长监测和产量估算具有重要意义。遥感光能利用模型以其数据采集简单、参数少、时间序列分析能力强等优点得到了广泛的应用。本研究分别利用卡耐基-艾姆斯-斯坦福方法(Carnegie-Ames-Stanford approach, CASA)模型计算的净初级生产力(NPP)和土壤有机质含量进行了产量估算。利用CASA模型对研究区2007 - 2017年玉米NPP进行估算,并探讨其时空变化特征。然后,在分析土壤有机质含量与NPP关系的基础上,建立了土壤有机质含量的反演模型。并对其时空变化特征进行了探讨。利用改进的产量估算模型对伊通县2007 - 2017年春玉米产量进行了估算。获得了研究区玉米收获指数和单位面积玉米单产。最后,结合上述数据对伊通县玉米的生长发育信息进行了综合评价。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Estimation of Maize Yield in Yitong County based on Multi-source Remote Sensing Data from 2007 to 2017
With the development of remote sensing technology, the utilizations of multi-spatial and multispectral resolution remote images have proved to be very important in monitoring the growth and estimating the yield of agricultural crops. The light energy utilization models using remote sensing have got the wide application because of its simple data acquisition, less parameters and capabilities for time series analysis. In this research, the yield estimation has been carried out using the net primary productivity (NPP) and the contents of soil organic matter which are obtained by Carnegie-Ames-Stanford approach (CASA) model and our proposed approach respectively. More specifically, NPP of maize in the study area from 2007 to 2017 was estimated using CASA model, and the characters of spatio-temporal variation were explored. After that, the retrieval model of the soil organic matter content was established based on the relationship analyzation between the soil organic content and NPP. The characters of spatio-temporal variation also have been explored. Then the yield of spring maize in Yitong County from 2007 to 2017 was estimated using an improved yield estimation model. Moreover, the maize harvest index and the yield of maize per unit area in the study area were obtained. Finally, the growth and development information of maize in Yitong County were comprehensively evaluated combining with these mentioned data.
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