Assessing the accuracy of GIS-based elementary multi criteria decision analysis as a spatial prediction tool – A case of predicting potential zones of sustainable groundwater resources

By K. Adiat, M. Nawawi, K. Abdullah. 2012

392 citations recorded by the source corpus.

Subfields: Environmental Engineering, Management, Monitoring, Policy and Law, Water Science and Technology

View Paper: https://www.semanticscholar.org/paper/368fa177b6de40f9020929ece41fff92a7904646

How researchers see this paper

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

In Environmental Engineering

1. Khabat Khosravi
2. Hamid Reza Pourghasemi
3. D. Tien Bui
4. Mahdi Panahi

In Management, Monitoring, Policy and Law

1. Khabat Khosravi
2. D. Tien Bui
3. Mahdi Panahi
4. Hamid Reza Pourghasemi
5. Omid Rahmati
6. Yousef Razandi
7. Najmeh Samani Neisani
8. Binh Thai Pham

Citations in the corpus

• Spatial prediction of groundwater spring potential mapping based on an adaptive neuro-fuzzy inference system and metaheuristic optimization (2018, background): “Lithology plays a key role in determining the groundwater potential due to different infiltration rates of formation (Adiat et al., 2012; Nampak et al., 2014).”
• Application of analytical hierarchy process, frequency ratio, and certainty factor models for groundwater potential mapping using GIS (2015, methodology): “According to Greenbaum (1989), Adiat et al. (2012), and Mogaji et al. (2014) the drainage density quantity is defined as the ratio of the sum of lengths of streams to the size of area of the grid under consideration.”