Comment on Remote sensing data processing by multivariate regression analysis method for iron mineral resource potential mapping: A case study in Sarvian area, central Iran

2017 ◽  
Author(s):  
Sunday Adeniyi
Keyword(s):  
Remote Sensing ◽  
Mineral Resource ◽  
Multivariate Regression ◽  
Remote Sensing Data ◽  
Multivariate Regression Analysis ◽  
Analysis Method ◽  
Resource Potential ◽  
Iron Mineral ◽  
Potential Mapping

scholarly journals Remote sensing data processing by multivariate regression analysis method for iron mineral resource potential mapping: A case study in Sarvian area, central Iran

2017 ◽  
Author(s):  
Edris Mansouri ◽  
Faranak Feizi ◽  
Alireza Jafari Rad ◽  
Mehran Arian
Keyword(s):  
Regression Analysis ◽  
Multivariate Regression ◽  
Linear Equations ◽  
Satellite Image ◽  
Remote Sensing Data ◽  
Multivariate Regression Analysis ◽  
P Value ◽  
New Mineral ◽  
Iron Mineral ◽  
Model Versus

Abstract. This paper used multivariate regression to create a mathematical model (with reasonable accuracy) for iron skarn exploration in the region of the interest and generalizing multivariate regression in Mineral Prospectivity Mapping (MPM) field. The main target of this manuscript is to exert multivariate regression analysis (as a MPM method) to iron outcrops mapping from northeast part of the study area to discover new iron deposits in other parts. Two types of multivariate regression models as two linear equations were employed to discover new mineral deposits. The Aster satellite image bands (14 bands) sets as Unique Independent Variables (UIVs) and iron outcrops map as dependent variables were used for MPM. According to the results of p-value, R2 and R2adj, the second regression model (which was a multiples and exponents of UIVs) was the fitted model versus other models. Also the accuracy of the model was confirmed by iron outcrops map and geological observations. Based on field observation iron mineralization occurs as contact of limestone and intrusive rocks (skarn type). Iron minerals consist dominantly of magnetite, hematite and goethite.

scholarly journals The Evaluation of GPM Precipitation Remote Sensing Data with Observed Data (Case Study: Mid-West of Iran)

2019 ◽  
Vol 11 (2) ◽  
pp. 115-124
Author(s):  
hamid reza sadeghi ◽  
jafar masoompour ◽  
Morteza miri
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Data ◽  
Sensing Data

scholarly journals Coral Reef Ecosystem Monitoring Using Remote Sensing Data: Case Study in Owi Island, Biak, Papua

2016 ◽  
Vol 33 ◽  
pp. 600-606 ◽  
Author(s):  
Dominggus Samuel H.L.M.K. Awak ◽  
Jonson Lumban Gaol ◽  
Beginer Subhan ◽  
Hawis H. Madduppa ◽  
Dondy Arafat
Keyword(s):  
Remote Sensing ◽  
Coral Reef ◽  
Remote Sensing Data ◽  
Coral Reef Ecosystem ◽  
Ecosystem Monitoring ◽  
Sensing Data ◽  
Reef Ecosystem
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