Groundwater qanat potential mapping using frequency ratio and Shannon’s entropy models in the Moghan watershed, Iran

By Seyed Amir Naghibi, Hamid Reza Pourghasemi, Zohre Sadat Pourtaghi, Ashkan Rezaei. Earth Science Informatics, 2015

319 citations recorded by the source corpus.

Subfields: Ecology, Evolution, Behavior and Systematics, Environmental Engineering, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/d7749aab7ee2c85d84ac1d79893f0ee8402f80f5

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecology, Evolution, Behavior and Systematics

1. Hamid Reza Pourghasemi
2. Seyed Amir Naghibi
3. Vijay P. Singh

In Environmental Engineering

1. Hamid Reza Pourghasemi
2. Khabat Khosravi
3. Binh Thai Pham
4. Seyed Amir Naghibi
5. Wei Chen
6. Haoyuan Hong
7. Mostafa Moradi Dashtpagerdi
8. Barnali Dixon

In Global and Planetary Change

1. Khabat Khosravi
2. Binh Thai Pham
3. D. Tien Bui
4. Himan Shahabi
5. Ataollah Shirzadi
6. Hamid Reza Pourghasemi
7. Wei Chen
8. Haoyuan Hong

Citations in the corpus

• GIS-based groundwater potential mapping using boosted regression tree, classification and regression tree, and random forest machine learning models in Iran (2015, methodology): “…profile curvature, distance to rivers, distance to faults, lithology, land use, drainage density, and fault density (also known as predictor factors) (Ozdemir 2011a, b; Oh et al., 2011; Manap et al. 2012; Davoodi Moghaddam et al. 2015; Pourtaghi and Pourghasemi, 2014; Naghibi et al. 2015).”
• Mapping Groundwater Potential Using a Novel Hybrid Intelligence Approach (2018, methodology): “2007), including frequency ratio (FR) (Naghibi et al. 2015), multi-criteria decision analysis (Chenini et al.”
• Application of analytical hierarchy process, frequency ratio, and certainty factor models for groundwater potential mapping using GIS (2015, background): “2014), logistic regression (Ozdemir 2011b; Pourtaghi and Pourghasemi 2014), Shannon’s entropy (Naghibi et al. 2014), weights-of-evidence (Corsini et al.”
• A comparative assessment between linear and quadratic discriminant analyses (LDA-QDA) with frequency ratio and weights-of-evidence models for forest fire susceptibility mapping in China (2017, methodology): “In this study, receiver operating characteristics (ROC) curve was implemented for evaluation of the FFMs produced by LDA, QDA, FR, and WofE models and to compare their results (Oh et al. 2011; Naghibi et al. 2015, 2016; Naghibi and Pourghasemi 2015; Tien Bui et al. 2016).”
• Spatial prediction of groundwater spring potential mapping based on an adaptive neuro-fuzzy inference system and metaheuristic optimization (2018, background): “…(Pourtaghi and Pourghasemi, 2014), logistic regression (Ozdemir, 2011a; Pourtaghi and Pourghasemi, 2014), evidential belief function (Nampak et al., 2014; Pourghasemi and Beheshtirad, 2015), and Shannon’s entropy (Naghibi et al., 2015), have been considered for groundwater potential mapping.”