Landslide susceptibility mapping using GIS-based statistical models and Remote sensing data in tropical environment

345 indexed citations

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This paper, published in 2015, received 345 indexed citations. Written by Himan Shahabi and Mazlan Hashim covering the research area of Global and Planetary Change and Management, Monitoring, Policy and Law. It is primarily cited by scholars working on Management, Monitoring, Policy and Law (272 citations), Global and Planetary Change (205 citations) and Atmospheric Science (76 citations). Published in Scientific Reports.

Countries where authors are citing Landslide susceptibility mapping using GIS-based statistical models and Remote sensing data in tropical environment

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This map shows the geographic impact of Landslide susceptibility mapping using GIS-based statistical models and Remote sensing data in tropical environment. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Landslide susceptibility mapping using GIS-based statistical models and Remote sensing data in tropical environment with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Landslide susceptibility mapping using GIS-based statistical models and Remote sensing data in tropical environment more than expected).

Fields of papers citing Landslide susceptibility mapping using GIS-based statistical models and Remote sensing data in tropical environment

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Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of Landslide susceptibility mapping using GIS-based statistical models and Remote sensing data in tropical environment. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Landslide susceptibility mapping using GIS-based statistical models and Remote sensing data in tropical environment.

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This paper is also available at doi.org/10.1038/srep09899.

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