scholarly journals Distribution Mapping and Typology of Slum Area Based on Spatial Autocorrelations in Padang City

2021 ◽  
Vol 1940 (1) ◽  
pp. 012080
Author(s):  
Risky Ramadhan ◽  
Azhari Syarief
Keyword(s):  
Slum Area ◽  
Distribution Mapping

A correlation of CL emissions from Penrith sandstone with elemental distributions obtained by simultaneous SEM-CL and EDS analysis

1995 ◽  
Vol 53 ◽  
pp. 392-393
Author(s):  
Paul J. Wright
Keyword(s):  
Optical Microscope ◽  
Electron Gun ◽  
High Electron ◽  
Collection System ◽  
Electron Hole ◽  
Depositional Processes ◽  
Eds Analysis ◽  
Distribution Mapping ◽  
Backscattered Electron ◽  
Electron Imaging

Most industrial and academic geologists are familiar with the beautiful red and orange cathodoluminescence colours produced by carbonate minerals in an optical microscope with a cold cathode electron gun attached. The cement stratigraphies interpreted from colour photographs have been widely used to determine the post depositional processes which have modified sedimentary rock textures.However to study quartzose materials high electron densities and kV's are necessary to stimulate sufficient emission. A scanning electron microscope with an optical collection system and monochromator provides an adequate tool and gives the advantage of providing secondary and backscattered electron imaging as well as elemental analysis and distribution mapping via standard EDS/WDS facilities.It has been known that the incorporation of many elements modify the characteristics of the CL emissions from geological materials. They do this by taking up positions between the valence and conduction band thus providing sites to assist in the recombination of electron hole pairs.

scholarly journals Assessing the adequacy of bias corrected IMERG satellite precipitation estimates using extended mixture distribution mapping method over Yangtze River basin

2018 ◽  
Vol 246 ◽  
pp. 01096
Author(s):  
Qiumei Ma ◽  
Lihua Xiong ◽  
Chong-Yu Xu ◽  
Shenglian Guo
Keyword(s):  
River Basin ◽  
Yangtze River ◽  
Extreme Values ◽  
Yangtze River Basin ◽  
Mixture Distribution ◽  
Mapping Method ◽  
Generalized Pareto ◽  
Precipitation Estimates ◽  
Distribution Mapping ◽  
Emd Method

Satellite precipitation estimates (SPE) product with high spatiotemporal resolution is a potential alternative to traditional ground-based gauge precipitation. However, SPE is frequently biased due to its indirect measurement, and thus bias correction is necessary before applying to a specific region. An improved distribution mapping method, i.e., Extended Mixture Distribution (EMD) of censored Gamma and generalized Pareto distributions, was established. The advantage of EMD method is that it describes both moderate and extreme values well and carries on the traditional censored, shifted Gamma distribution to combine the precipitation occurrence/non-occurrence events together. Then the EMD method was applied to the Integrated Multi-satellitE Retrievals for GPM product (IMERG) as statistical post-processing over Yangtze River basin. The Version-2 Gridded dataset of daily Surface Precipitation from China Meteorological Administration (GSP-CMA) was taken as reference. The adequacy of bias corrected IMERG precipitation was assessed and the results showed that (1) the Root Mean Squared Error and Relative Bias between bias-corrected IMERG precipitation and reference are significantly reduced relative to the raw IMERG estimates; (2) the performance of extreme values of IMERG in Yangtze River basin is enhanced since both the under- and over-estimation of the raw IMERG are compromised, due to the generalized Pareto distribution introduced in EMD which is enable to describe the extreme value distribution. This highlights the improved distribution mapping method, EMD is flexible and robust to bias correct the IMERG precipitation to obtain higher accuracy of SPE despite the coarse resolution of reference.

scholarly journals Machine Learning-Based Prediction of Selected Parameters of Commercial Biomass Pellets Using Line Scan Near Infrared-Hyperspectral Image

Processes ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 316
Author(s):  
Lakkana Pitak ◽  
Kittipong Laloon ◽  
Seree Wongpichet ◽  
Panmanas Sirisomboon ◽  
Jetsada Posom
Keyword(s):  
Near Infrared ◽  
Hyperspectral Image ◽  
Thermal Conversion ◽  
High Energy ◽  
Volatile Matter ◽  
Successive Projections Algorithm ◽  
Color Distribution ◽  
Standard Normal Variate ◽  
Distribution Mapping ◽  
Standard Normal

Biomass pellets are required as a source of energy because of their abundant and high energy. The rapid measurement of pellets is used to control the biomass quality during the production process. The objective of this work was to use near infrared (NIR) hyperspectral images for predicting the properties, i.e., fuel ratio (FR), volatile matter (VM), fixed carbon (FC), and ash content (A), of commercial biomass pellets. Models were developed using either full spectra or different spatial wavelengths, i.e., interval successive projections algorithm (iSPA) and interval genetic algorithm (iGA), wavelengths and different spectral preprocessing techniques. Their performances were then compared. The optimal model for predicting FR could be created with second derivative (D2) spectra with iSPA-100 wavelengths, while VM, FC, and A could be predicted using standard normal variate (SNV) spectra with iSPA-100 wavelengths. The models for predicting FR, VM, FC, and A provided R2 values of 0.75, 0.81, 0.82, and 0.87, respectively. Finally, the prediction of the biomass pellets’ properties under color distribution mapping was able to track pellet quality to control and monitor quality during the operation of the thermal conversion process and can be intuitively used for applications with screening.

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