检索结果-南通市图书馆

Spectral Model for Soybean Yield Estimate Using MODIS/EVI data

International Journal of Geosciences 2013年第9期4卷 1233-1241页

作者： Anibal Gusso Jorge Ricardo Ducati Mauricio Roberto Veronez damien Arvor luiz gonzaga da silveira jr. Environmental Engineering UNISINOSSao LeopoldoBrazil Remote Sensing Center and Astronomy Department UFRGSPorto AlegreBrazil Graduate Program in Geology UNISINOSSao LeopoldoBrazil Institut de Recherche Pour le Developpement(IRD) MontpellierFrance Graduate Program in Applied Computing UNISINOSSao LeopoldoBrazil

Attaining reliable and timely agricultural estimates is very important everywhere, and in Brazil, due to its characteristics, this is especially true. In this study, estimations of crop production were made based on the temporal profiles of the Enhanced Vegetation Index (EVI) obtained from Moderate Resolution Imaging Spectroradiometer (MODIS) images. The objective was to evaluate the coupled model (CM) performance of crop area and crop yield estimates based solely on MODIS/EVI as input data in Rio Grande do Sul State, which is characterized by high variability in seasonal soybean yields, due to different crop development conditions. The resulting production estimates from CM were compared to official agricultural statistics of Brazilian Institute of Geography and Statistics (IBGE) and the National Company of Food Supply (CONAB) at different levels from 2000/2001 to 2010/2011 crop years. Results obtained with CM indicate that its application is able to generate timely production estimates for soybean both at municipality and local levels. Validation estimates with CM at State level obtained R2 = 0.95. Combining all cropping years at municipality level, estimates were highly correlated to official statistics from IBGE, with R2 = 0.91 and RMSD = 10,840 tons. Spatially interpolated comparisons of yield maps obtained from the CM estimates and IBGE data also showed visual similarity in their spatial distribution. Local level comparisons were performed and presented R2 = 0.95. Implications of this work point out that time-series analysis of production estimates are able to provide anticipated spatial information prior to the soybean harvest.

关键词： Remote Sensing Coupled Model Soy Yield Forecast Satellite Images

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Monitoring Heat Waves and Their Impacts on Summer Crop Development in Southern Brazil

引用

Agricultural Sciences 2014年第4期5卷 353-364页

作者： Anibal Gusso Jorge Ricardo Ducati Mauricio Roberto Veronez Victor Sommer luiz gonzaga da silveira Junior Environmental Engineering Vale do Rio dos Sinos University(UNISINOS)Sao LeopoldoBrazil Center for Remote Sensing and Meteorological Research Federal University of Rio Grande do Sul(UFRGS)Porto AlegreBrazil VizLab-Advanced Visualization Laboratory Vale do Rio dos Sinos University(UNISINOS)Sao LeopoldoBrazil Astronomy Department Federal University of Rio Grande do Sul(UFRGS)Porto AlegreBrazil Graduate Program in Geology Vale do Rio dos Sinos University(UNISINOS)Sao LeopoldoBrazil Crop Breeding Foundation(Fundacao Pró-Sementes) Passo FundoBrazil Graduate Program in Applied Computing Vale do Rio dos Sinos University(UNISINOS)São LeopoldoBrazil

Periods in the soybean summer cycle that are sensitive to the occurrence of high temperatures were studied. An analysis was performed on the variability of soybean yields associated with crop canopy temperatures during key development periods. A land surface temperature (LST) data series from MODIS (Moderate Resolution Imaging Spectroradiometer) on the Aqua satellite was processed between 2003 and 2012 that covered the entire state of Rio Grande do Sul, in Brazil. Enhanced vegetation index (EVI) data from MODIS on the Terra satellite were used to monitor the LST during different phenological stages. Spatially interpolated maps of soybean yield distributions were generated using data obtained from Instituto Brasileiro de Geografia e Estatística (IBGE) at state and municipality levels. The results indicate that canopy-LST occurrence in mid-February, during the grain filling, is most correlated to yield reduction (R2 = 0.82 and RMSD = 14.4%). At the state level, the average yield is 2003 kg·ha-1 with a standard deviation of 308 kg·ha-1. The overall average of the canopy-LST is 305.0 K (31.8°C) with a standard deviation of 1.9 K. The slope of the downward linear relationship between canopy-LST and yield was -28.7%. These results indicate that monitoring heat wave events can provide important information for characterising agriculture vulnerability.

关键词： Land Surface Temperature Soybean Remote Sensing Canopy Vegetation Index MODIS data

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：