Analyzing the Impact of Forest Cover at River Bank on Flood Spread by using Predictive Analytics and Satellite Imagery
| Autor: | Muhammad Fahad Umer, Muhammad Khalid, Rafi Ullah, Tariq Mahmood, Muhammad Aneeq Yusuf |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
010504 meteorology & atmospheric sciences
General Computer Science Flood myth Computer science 0207 environmental engineering 02 engineering and technology Predictive analytics 01 natural sciences Forest cover Human settlement Satellite imagery Physical geography 020701 environmental engineering Bank 0105 earth and related environmental sciences |
| Zdroj: | International Journal of Advanced Computer Science and Applications. 10 |
| ISSN: | 2156-5570 2158-107X |
| Popis: | Floods have been a recurring problem for a number of countries around the world including Pakistan. It is believed that densely populated forests at river banks can prevent floods from spreading towards settlements and farmlands. The role of forest in flood spread has been an area of research for a while but the role of predictive modeling in this area is yet to be investigated in detail. In this study, we have used predictive analytics and satellite imagery to develop an environmental model that can predict the flood spread by considering forest cover at river bank and month of the year as parameters. We have used the satellite images of an area situated in the northern region of Pakistan i.e. Dera Ghazi Khan from the USGS’s Land Sat program. These images comprised of a section of the Indus River and its adjoining areas. We want to analyze the forest bank at various section of the Indus River. We developed and trained our predictive model by using the satellite imagery data and tested it on a separate dataset to determine error percentage. The model showed significant promise and predicted the flood spread with an average accuracy of above 80%. |
| Databáze: | OpenAIRE |
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