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111.
多源信息的集成与融合及其在遥感制图中的优化利用 总被引:13,自引:3,他引:13
多源信息的集成和融合是地球信息科学领域的一大热点问题。它的意义和必要性与地球信息本身的特征、采集信息的手段特征及信息处理平台或系统的特点三方面紧密相联系。本文从不同传感器信息的集成和融合、遥感信息与非遥感地学信息的集成和融合、不同格式的 GIS数据的集成和复合三个方面研究了多源信息集成和融合的方法、前沿技术和应用领域,进而以黄土高原土壤侵蚀遥感调查和制图任务为例,介绍了多源信息集成和融合技术在该项目中的优化应用实例,包括技术流程分析、信息源分析、多源信息在土壤侵蚀遥感调查和制图中的融合方法、从遥感图像解译信息到 GIS数据库的转换技术等。 相似文献
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专题制图中,所收集到的数据经常是单因素的,而在专题地图上却往往需要把多个单因素专题数据进行综合分类来表示。本文中,采用Fuzzy-Grey局势决策(下简称F-G决策)来研究多因素专题数据的综合分类问题,把“数据的模糊性”引入到灰色局势决策之中,根据不同情况,讨论各局势上效果测度中模糊隶属度确定的建模方法,在合适的隶属函数的基础上,在计算机上对实例分类进行程序运行,获得满意的结果。研究表明应用该方法在专题制图中对多因素数据进行综合分类是一种有效的手段。 相似文献
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In this paper, a new model for a single reservoir operation optimization is proposed. The proposed model can design the optimal operation policy of a reservoir with explicit consideration of drought duration. The authors model this problem by formulating a single-stage loss function as a function of both the reservoir release and drought duration. Thereby the expected loss per period which is calculated based on the above extended single-stage loss function is minimized in infinite time horizon on the basis of Markov decision process (MDP) theory. The reliability indices are estimated as expected loss per period for specified extended loss functions. Finally, the features of the proposed model are illustrated through numerical analysis. 相似文献
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ABSTRACT In many places, magnitudes and frequencies of floods are expected to increase due to climate change. To understand these changes better, trend analyses of historical data are helpful. However, traditional trend analyses do not address issues related to shifts in the relative contributions of rainfall versus snowmelt floods, or in the frequency of a particular flood type. We present a novel approach for quantifying such trends in time series of floods using a fuzzy decision tree for event classification and applied it to maximal annual and seasonal floods in 27 alpine catchments for the period 1980–2014. Trends in flood types were studied with Sen’s slope and double mass curves. Our results reveal a decreasing number of rain-on-snow and an increasing number of short rainfall events in all catchments, with flash floods increasing in smaller catchments. Overall, the results demonstrate the value of incorporating a fuzzy flood-type classification into flood trend analyses. 相似文献
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ABSTRACT White mold of soybeans is one of the most important fungal diseases that affect soybean production in South Dakota. However, there is a lack of information on the spatial characteristics of the disease and relationship with soybean yield. This relationship can be explored with the Normalized Difference Vegetation Index (NDVI) derived from Landsat 8 and a fusion of Landsat 8 and the Moderate Resolution Imaging Spectroradiometer (MODIS) images. This study investigated the patterns of yield in two soybean fields infected with white mold between 2016 and 2017, and estimated yield loss caused by white mold. Results show evidence of clustering in the spatial distribution of yield (Moran’s I = 0.38; p < 0.05 in 2016 and Moran’s I = 0.45; p < 0.05 in 2017) that can be explained by the spatial distribution of white mold in the observed fields. Yield loss caused by white mold was estimated at 36% in 2016 and 56% in 2017 for the worse disease pixels, with the most accurate period for estimating this loss on 21 August and 8 September for 2016 field and 2017 field, respectively. This study shows the potential of free remotely sensed satellite data in estimating yield loss caused by white mold. 相似文献
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ABSTRACT Eighty percent of big data are associated with spatial information, and thus are Big Spatial Data (BSD). BSD provides new and great opportunities to rework problems in urban and environmental sustainability with advanced BSD analytics. To fully leverage the advantages of BSD, it is integrated with conventional data (e.g. remote sensing images) and improved methods are developed. This paper introduces four case studies: (1) Detection of polycentric urban structures; (2) Evaluation of urban vibrancy; (3) Estimation of population exposure to PM2.5; and (4) Urban land-use classification via deep learning. The results provide evidence that integrated methods can harness the advantages of both traditional data and BSD. Meanwhile, they can also improve the effectiveness of big data itself. Finally, this study makes three key recommendations for the development of BSD with regards to data fusion, data and predicting analytics, and theoretical modeling. 相似文献