Mapping of groundwater potential zones in the Musi basin using remote sensing data and GIS

By Sreedhar Ganapuram, G. T. V. Kumar, I. Krishna, Ercan Kahya, M. Demirel. Advances in Engineering Software, 2009

299 citations recorded by the source corpus.

Subfields: Environmental Engineering, Global and Planetary Change, Water Science and Technology

View Paper: https://www.semanticscholar.org/paper/94d8dac4e196e1bd40687345200bbca3b30b4f4a

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. Hamid Reza Pourghasemi
2. Seyed Amir Naghibi
3. Barnali Dixon
4. Khabat Khosravi

In Global and Planetary Change

1. Hamid Reza Pourghasemi
2. Seyed Amir Naghibi
3. Barnali Dixon
4. Binh Thai Pham
5. Khabat Khosravi
6. Indra Prakash
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): “Many studies used integrated geographic information system (GIS), remote sensing (RS), and geostatistics methods for groundwater mapping (Jaiswal et al. 2003; Solomon and Quiel 2006; Jha et al. 2007; Ganapuram et al. 2009; Saha et al. 2010; Chung and Rogers 2012; Bhat et al. 2015; Varouchakis 2015).”