Prediction concentration of PM2.5 in Surabaya using ordinary Kriging method

2021 ◽  
Author(s):  
Derbi W. Fitri ◽  
Nurul Afifah ◽  
Siti M. D. Anggarani ◽  
Nur Chamidah
Keyword(s):  
Ordinary Kriging ◽  
Kriging Method

scholarly journals Spatial Interpolation on Rainfall Data over Peninsular Malaysia Using Ordinary Kriging

2013 ◽  
Vol 63 (2) ◽  
Author(s):  
Suhaila Jamaludin ◽  
Hanisah Suhaimi
Keyword(s):  
Spatial Analysis ◽  
Ordinary Kriging ◽  
Spatial Interpolation ◽  
Rainfall Intensity ◽  
Peninsular Malaysia ◽  
Rainfall Data ◽  
Kriging Method ◽  
Intensity Index ◽  
Dry Conditions ◽  
Two Indices

This study presents the spatial analysis of the rainfall data over Peninsular Malaysia. 70 rainfall stations were utilized in this study. Due to the limited number of rainfall stations, the Ordinary Kriging method which is one of the techniques in Spatial Interpolation was used to estimate the values of the rainfall data and to map their spatial distribution. This spatial analysis was analysed according to the two indices that describe the wet events and another two indices that characterize dry conditions. Large areas at the east experienced high rainfall intensity compared to the areas in the west, northwest and southwest. The small value that has been obtained in Aridity Intensity Index (AII) reflects that the high amount of rainfall in the eastern areas is not contributed by low-intensity events (less than 25th percentile). In terms of number of consecutive dry days, Northwestern areas in Peninsular Malaysia recorded the highest value. This finding explains the occurrence of a large number of floods and soil erosions in the eastern areas.

scholarly journals Review of the Kriging Technique Applications to Groundwater Quality

2021 ◽  
Vol 27 (12) ◽  
pp. 23-32
Author(s):  
Hayat Azawi ◽  
May Samir Saleh
Keyword(s):  
Groundwater Quality ◽  
Quality Indicator ◽  
Ordinary Kriging ◽  
Indicator Kriging ◽  
Disjunctive Kriging ◽  
Kriging Method ◽  
Lognormal Kriging ◽  
Groundwater Contaminants ◽  
Simple Kriging

Kriging, a geostatistical technique, has been used for many years to evaluate groundwater quality. The best estimation data for unsampled points were determined by using this method depending on measured variables for an area. The groundwater contaminants assessment worldwide was found through many kriging methods. The present paper shows a review of the most known methods of kriging that were used in estimating and mapping the groundwater quality. Indicator kriging, simple kriging, cokriging, ordinary kriging, disjunctive kriging and lognormal kriging are the most used techniques. In addition, the concept of the disjunctive kriging method was explained in this work to be easily understood.

Real-Time Automatic Seizure Detection Using Ordinary Kriging Method in an Edge-IoMT Computing Paradigm

2020 ◽  
Vol 1 (5) ◽  
Author(s):  
Ibrahim L. Olokodana ◽  
Saraju P. Mohanty ◽  
Elias Kougianos ◽  
Oluwaseyi O. Olokodana
Keyword(s):  
Real Time ◽  
Ordinary Kriging ◽  
Seizure Detection ◽  
Kriging Method ◽  
Computing Paradigm

Generation Of Temperature Climatic Chart Using The Ordinary Kriging Method And Correction Of Altitude

2013 ◽  
Author(s):  
Mateus Brunelli ◽  
Willingthon Pavan ◽  
Marcelo Trindade Rebonatto
Keyword(s):  
Ordinary Kriging ◽  
Kriging Method

scholarly journals Transport of broilers: load microclimate during Brazilian summer

2014 ◽  
Vol 34 (3) ◽  
pp. 405-412 ◽  
Author(s):  
José A. D. Barbosa Filho ◽  
Marília L. V. Queiroz ◽  
Daniel de F. Brasil ◽  
Frederico M. C. Vieira ◽  
Iran J. O. Silva
Keyword(s):  
Relative Humidity ◽  
Ordinary Kriging ◽  
Environmental Variables ◽  
Critical Period ◽  
Continuous Monitoring ◽  
Kriging Method ◽  
Comfort Index ◽  
Data Loggers

The objective of this study was to characterize the microclimatic profile of broiler transport trucks under commercial conditions, in the summer, by continuous monitoring of environmental variables (temperature and air relative humidity). Three loads were monitored from farm to slaughterhouse, considering factors such as distance and day periods (morning, afternoon, and night). To obtain the profile of the environmental variables during journey, data loggers, that determined the microclimate to which birds were submitted, were installed in the trucks; data loggers also allowed visualization of the Enthalpy Comfort Index (ECI) so that load regions could be classified according to heat comfort limits for 6-week old poultries. Temperature, relative humidity, and ECI in the truck were analyzed, using geostatistics, by the ordinary kriging method. The afternoon was the most critical period, and truck central and rear regions were most problematic for chickens, thus most susceptible to losses.

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