Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/483857
Title: | Forest fire detection system using landsat satellite images for effective disaster management |
Researcher: | Chanthiya P |
Guide(s): | Kalaivani V |
Keywords: | Forest fires LANDSAT images Disaster Management |
University: | Anna University |
Completed Date: | 2022 |
Abstract: | Forest fires are still the most common terrible danger in forests, and they are an uncontrollable natural occurrence that poses a significant threat to both wildlife and human who live there. According to reports, a total of four to six million wildfires have occurred every year in the last decade around the globe. Early detection of a prospective fire occurrence has the potential to lessen the cause or risk of the fire up to 95%. There are a variety of approaches that may be used to safeguard forest resources against fire. A satellite-based system can be used to identify fires, monitor them, and assess their impact. The benefit of employing a satellite-based system is its wide coverage of any location can cover an area. The majority of satellite-based systems are used to monitor forest fire incidents and analyze charred areas. There are a variety of satellite-based technologies that may be used to detect fires via remote sensing. newlineSeveral early detection algorithms have been introduced to detect the forest fires using LANDSAT images. The remote sensing-based fire detection system contains four basic steps. Initially the collected datasets are given for preprocessing. At this step the image co-registration, error correction and removal of cloud and cloud shadow are performed. Adaptive Median Filter is designed to handle the challenge of removing image noise while also reducing image distortion. newline |
Pagination: | xiv,130p. |
URI: | http://hdl.handle.net/10603/483857 |
Appears in Departments: | Faculty of Information and Communication Engineering |
Files in This Item:
File | Description | Size | Format | |
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01_title.pdf | Attached File | 27.32 kB | Adobe PDF | View/Open |
02_prelimpages.pdf | 2.42 MB | Adobe PDF | View/Open | |
03_contents.pdf | 15.54 kB | Adobe PDF | View/Open | |
04_abstracts.pdf | 7.63 kB | Adobe PDF | View/Open | |
05_chapter1.pdf | 310.41 kB | Adobe PDF | View/Open | |
06_chapter2.pdf | 188.67 kB | Adobe PDF | View/Open | |
07_chapter3.pdf | 931.55 kB | Adobe PDF | View/Open | |
08_chapter4.pdf | 844.51 kB | Adobe PDF | View/Open | |
09_chapter5.pdf | 794.36 kB | Adobe PDF | View/Open | |
10_chapter6.pdf | 34.83 kB | Adobe PDF | View/Open | |
11_annexures.pdf | 152.4 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 62.23 kB | Adobe PDF | View/Open |
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