scholarly journals Geospatial blending to improve spatial mapping of precipitation with high spatial resolution by merging satellite-based and ground-based data

2016 ◽  
Vol 30 (16) ◽  
pp. 2789-2803 ◽  
Author(s):  
Baik Jongjin ◽  
Park Jongmin ◽  
Ryu Dongryeol ◽  
Choi Minha
Keyword(s):  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Spatial Mapping

scholarly journals A Method of Spatial Mapping and Reclassification for High-Spatial-Resolution Remote Sensing Image Classification

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Guizhou Wang ◽  
Jianbo Liu ◽  
Guojin He
Keyword(s):  
Remote Sensing ◽  
Image Classification ◽  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Multispectral Image ◽  
Classification Method ◽  
Support Vector ◽  
Spatial Mapping ◽  
Remote Sensing Images ◽  
Mapping Mechanism

This paper presents a new classification method for high-spatial-resolution remote sensing images based on a strategic mechanism of spatial mapping and reclassification. The proposed method includes four steps. First, the multispectral image is classified by a traditional pixel-based classification method (support vector machine). Second, the panchromatic image is subdivided by watershed segmentation. Third, the pixel-based multispectral image classification result is mapped to the panchromatic segmentation result based on a spatial mapping mechanism and the area dominant principle. During the mapping process, an area proportion threshold is set, and the regional property is defined as unclassified if the maximum area proportion does not surpass the threshold. Finally, unclassified regions are reclassified based on spectral information using the minimum distance to mean algorithm. Experimental results show that the classification method for high-spatial-resolution remote sensing images based on the spatial mapping mechanism and reclassification strategy can make use of both panchromatic and multispectral information, integrate the pixel- and object-based classification methods, and improve classification accuracy.

High spatial resolution AEM observations of yttrium segregation in chromia scales grown on Co-45%Cr

1986 ◽  
Vol 44 ◽  
pp. 518-519
Author(s):  
K. Przybylski ◽  
A. J. Garratt-Reed ◽  
G. J. Yurek
Keyword(s):  
Spatial Resolution ◽  
Outer Surface ◽  
Maximum Concentration ◽  
High Spatial Resolution ◽  
Reactive Elements ◽  
Chromia Scales

The addition of so-called “reactive” elements such as yttrium to alloys is known to enhance the protective nature of Cr2O3 or Al2O3 scales. However, the mechanism by which this enhancement is achieved remains unclear. An A.E.M. study has been performed of scales grown at 1000°C for 25 hr. in pure O2 on Co-45%Cr implanted at 70 keV with 2x1016 atoms/cm2 of yttrium. In the unoxidized alloys it was calculated that the maximum concentration of Y was 13.9 wt% at a depth of about 17 nm. SIMS results showed that in the scale the yttrium remained near the outer surface.

Integration of Core-Edge Spectroscopy Methods for the Study of Polymers

1996 ◽  
Vol 54 ◽  
pp. 154-155
Author(s):  
E. G. Rightor
Keyword(s):  
Excited State ◽  
Polymer Blends ◽  
Gas Phase ◽  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Electronic States ◽  
Core Electron ◽  
Bulk Solids ◽  
Development Application

Core edge spectroscopy methods are versatile tools for investigating a wide variety of materials. They can be used to probe the electronic states of materials in bulk solids, on surfaces, or in the gas phase. This family of methods involves promoting an inner shell (core) electron to an excited state and recording either the primary excitation or secondary decay of the excited state. The techniques are complimentary and have different strengths and limitations for studying challenging aspects of materials. The need to identify components in polymers or polymer blends at high spatial resolution has driven development, application, and integration of results from several of these methods.

Color Hologram Generation Using High Spatial Resolution Camera

2013 ◽  
Vol 67 (3) ◽  
pp. J108-J115
Author(s):  
Kosuke Nomura ◽  
Ryutaro Oi ◽  
Takanori Senoh ◽  
Taiichiro Kurita ◽  
Takayuki Hamamoto
Keyword(s):  
Spatial Resolution ◽  
High Spatial Resolution
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