A decision tree based on spatial relationships for predicting hotspots in peatlands

Predicting hotspot occurrence as an indicator of forest and land fires is essential in developing an early warning system for fire prevention. This work applied a spatial decision tree algorithm on spatial data of forest fires. The algorithm is the improvement of the conventional decision tree algor...

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Main Authors: Sitanggang, Imas Sukaesih, Yaakob, Razali, Mustapha, Norwati, Nuruddin, Ahmad Ainuddin
Format: Article
Language:English
Published: Universitas Ahmad Dahlan and Institute of Advanced Engineering and Science 2014
Online Access:http://psasir.upm.edu.my/id/eprint/36155/1/A%20decision%20tree%20based%20on%20spatial%20relationships%20for%20predicting%20hotspots%20in%20peatlands.pdf
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author Sitanggang, Imas Sukaesih
Yaakob, Razali
Mustapha, Norwati
Nuruddin, Ahmad Ainuddin
author_facet Sitanggang, Imas Sukaesih
Yaakob, Razali
Mustapha, Norwati
Nuruddin, Ahmad Ainuddin
author_sort Sitanggang, Imas Sukaesih
collection UPM
description Predicting hotspot occurrence as an indicator of forest and land fires is essential in developing an early warning system for fire prevention. This work applied a spatial decision tree algorithm on spatial data of forest fires. The algorithm is the improvement of the conventional decision tree algorithm in which the distance and topological relationships are included to grow up spatial decision trees. Spatial data consist of a target layer and ten explanatory layers representing physical, weather, socio-economic and peatland characteristics in the study area Rokan Hilir District, Indonesia. Target objects are hotspots of 2008 and non-hotspot points. The result is a pruned spatial decision tree with 122 leaves and the accuracy of 71.66%. The spatial tree has produces higher accuracy than the non-spatial trees that were created using the ID3 and C4.5 algorithm. The ID3 decision tree has accuracy of 49.02% while the accuracy of C4.5 decision tree reaches 65.24%.
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spelling upm.eprints-361552016-01-26T02:56:10Z http://psasir.upm.edu.my/id/eprint/36155/ A decision tree based on spatial relationships for predicting hotspots in peatlands Sitanggang, Imas Sukaesih Yaakob, Razali Mustapha, Norwati Nuruddin, Ahmad Ainuddin Predicting hotspot occurrence as an indicator of forest and land fires is essential in developing an early warning system for fire prevention. This work applied a spatial decision tree algorithm on spatial data of forest fires. The algorithm is the improvement of the conventional decision tree algorithm in which the distance and topological relationships are included to grow up spatial decision trees. Spatial data consist of a target layer and ten explanatory layers representing physical, weather, socio-economic and peatland characteristics in the study area Rokan Hilir District, Indonesia. Target objects are hotspots of 2008 and non-hotspot points. The result is a pruned spatial decision tree with 122 leaves and the accuracy of 71.66%. The spatial tree has produces higher accuracy than the non-spatial trees that were created using the ID3 and C4.5 algorithm. The ID3 decision tree has accuracy of 49.02% while the accuracy of C4.5 decision tree reaches 65.24%. Universitas Ahmad Dahlan and Institute of Advanced Engineering and Science 2014-06 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/36155/1/A%20decision%20tree%20based%20on%20spatial%20relationships%20for%20predicting%20hotspots%20in%20peatlands.pdf Sitanggang, Imas Sukaesih and Yaakob, Razali and Mustapha, Norwati and Nuruddin, Ahmad Ainuddin (2014) A decision tree based on spatial relationships for predicting hotspots in peatlands. TELKOMNIKA, 12 (2). pp. 511-518. ISSN 1693-6930; ESSN: 2302-4046 http://journal.uad.ac.id/index.php/TELKOMNIKA/article/view/68
spellingShingle Sitanggang, Imas Sukaesih
Yaakob, Razali
Mustapha, Norwati
Nuruddin, Ahmad Ainuddin
A decision tree based on spatial relationships for predicting hotspots in peatlands
title A decision tree based on spatial relationships for predicting hotspots in peatlands
title_full A decision tree based on spatial relationships for predicting hotspots in peatlands
title_fullStr A decision tree based on spatial relationships for predicting hotspots in peatlands
title_full_unstemmed A decision tree based on spatial relationships for predicting hotspots in peatlands
title_short A decision tree based on spatial relationships for predicting hotspots in peatlands
title_sort decision tree based on spatial relationships for predicting hotspots in peatlands
url http://psasir.upm.edu.my/id/eprint/36155/1/A%20decision%20tree%20based%20on%20spatial%20relationships%20for%20predicting%20hotspots%20in%20peatlands.pdf
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