Random Forest Classification Scenarios for Benthic Habitat Mapping using Planetscope Image

Wicaksono, Pramaditya and Lazuardi, Wahyu (2019) Random Forest Classification Scenarios for Benthic Habitat Mapping using Planetscope Image. In: 39th IEEE International Geoscience and Remote Sensing Symposium, IGARSS.

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Abstract

We presented the use of Random Forest (RF) classification to map benthic habitat in two small islands using different parameter scenario, which are the number of trees, the function to determine the number of randomly selected features, and the function to determine the impurity in a node. The results indicated that RF is a consistent performer with accuracy difference of 1.3 and 5.8 for the two Islands. Furthermore, different scenarios also producing similar benthic habitat spatial distribution and misclassification pattern. © 2019 IEEE.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Cited by: 20
Uncontrolled Keywords: Decision trees; Ecosystems; Geology; Image classification; Random forests; Remote sensing; Accuracy assessment; Benthic habitats; Misclassifications; Number of trees; PlanetScope; Random forest classification; Small island; Mapping
Subjects: G Geography. Anthropology. Recreation > G Geography (General)
Divisions: Faculty of Geography > Departemen Sains Informasi Geografi
Depositing User: Sri JUNANDI
Date Deposited: 29 Jul 2026 02:59
Last Modified: 29 Jul 2026 02:59
URI: https://ir.lib.ugm.ac.id/id/eprint/26918

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