Forest mapping in Peninsular Malaysia using Random Forest and Support Vector Machine Classifiers on Google Earth Engine
Forests play a crucial role in maintaining the balance of the global ecosystem by sustaining the interactions between living and non-living entities. Changes in forest areas encompass both growth and loss, often driven by development activities. Assessing forest cover and its changes is also a pivot...
| Main Authors: | Farah Nuralissa Muhammad, Lam, Kuok Choy |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Penerbit Universiti Kebangsaan Malaysia
2023
|
| Online Access: | http://journalarticle.ukm.my/22708/ http://journalarticle.ukm.my/22708/1/648502198981PB.pdf |
Similar Items
Comparison Of Google Earth Engine- Based Machine Learning Classifiers For Mapping Aquaculture Ponds In Sungai Udang, Penang
by: Rajandran, Arvinth
Published: (2023)
by: Rajandran, Arvinth
Published: (2023)
Multi-temporal, multi-sensor land use/land cover mapping: Google Earth Engine and Random Forest for the classification of the Scottish flow country
by: Sutherland, Neil
Published: (2021)
by: Sutherland, Neil
Published: (2021)
Oil palm mapping over Peninsular Malaysia using Google Earth Engine and machine learning algorithms
by: Shaharum, Nur Shafira Nisa, et al.
Published: (2020)
by: Shaharum, Nur Shafira Nisa, et al.
Published: (2020)
Churn Forecast Portal using Random Forest Classifier
by: Arpan, Chakraborty, et al.
Published: (2024)
by: Arpan, Chakraborty, et al.
Published: (2024)
Teaching Sustainability with Overlay Mapping and Google Earth
by: Stocker, Laura, et al.
Published: (2009)
by: Stocker, Laura, et al.
Published: (2009)
Classifying forest species using hyperspectral data in Balah Forest Reserve, Kelantan, Peninsular Malaysia
by: Mat Zain, Ruhasmizan, et al.
Published: (2013)
by: Mat Zain, Ruhasmizan, et al.
Published: (2013)
Forest classification and mapping for resource management at the Gunung Stong Forest Reserve, Peninsular Malaysia
by: Mat Zain, Ruhasmizan
Published: (2012)
by: Mat Zain, Ruhasmizan
Published: (2012)
Google the earth: what's next?
by: Mansor, Shattri
Published: (2010)
by: Mansor, Shattri
Published: (2010)
Support directional shifting vector: A direction based machine learning classifier
by: Kowsher, Md., et al.
Published: (2021)
by: Kowsher, Md., et al.
Published: (2021)
The application of support vector machine in classifying potential archers using bio-mechanical indicators
by: Zahari, Taha, et al.
Published: (2018)
by: Zahari, Taha, et al.
Published: (2018)
Electrical substations mapping for possible communication technologies using QGIS and Google Earth Pro
by: Izzati Thaqifah Zulkifli,, et al.
Published: (2024)
by: Izzati Thaqifah Zulkifli,, et al.
Published: (2024)
XAIRF-WFP: a novel XAI-based random forest classifier for advanced email spam detection
by: Bouke, Mohamed Aly, et al.
Published: (2024)
by: Bouke, Mohamed Aly, et al.
Published: (2024)
Leptospirosis modelling using hydrometeorological indices and random forest machine learning
by: Jayaramu, Veianthan, et al.
Published: (2023)
by: Jayaramu, Veianthan, et al.
Published: (2023)
Leptospirosis modelling using hydrometeorological indices and random forest machine learning for humid tropical north-east Peninsular Malaysia
by: Jayaramu, Veianthan
Published: (2022)
by: Jayaramu, Veianthan
Published: (2022)
An improved algorithm for iris classification by using support vector machine and binary random machine learning
by: Kamarulzalis, Ahmad Haadzal
Published: (2018)
by: Kamarulzalis, Ahmad Haadzal
Published: (2018)
Beyond boundaries: Sharing knowledge with Google Earth
by: Stocker, Laura
Published: (2012)
by: Stocker, Laura
Published: (2012)
Orchids in the Montane forests of Peninsular Malaysia
by: Go, Rusea, et al.
Published: (2015)
by: Go, Rusea, et al.
Published: (2015)
Cardiotocogram Data Classification using Random Forest based Machine Learning Algorithm
by: Molla, M. M. Imran, et al.
Published: (2020)
by: Molla, M. M. Imran, et al.
Published: (2020)
Hybrid sampling and random forest machine learning approach for software detect prediction
by: Md. Anwar, Hossen, et al.
Published: (2019)
by: Md. Anwar, Hossen, et al.
Published: (2019)
Twisted pair cable fault diagnosis via random forest machine learning
by: Ghazali, N. B., et al.
Published: (2022)
by: Ghazali, N. B., et al.
Published: (2022)
The employment of Support Vector Machine to classify high and low performance archers based on bio-physiological variables
by: Zahari, Taha, et al.
Published: (2018)
by: Zahari, Taha, et al.
Published: (2018)
Review on support vector machine (SVM) classifier for human emotion pattern recognition from EEG signals
by: Zulkifli, Noor Aishah Atiqah, et al.
Published: (2015)
by: Zulkifli, Noor Aishah Atiqah, et al.
Published: (2015)
Face Recognition System Using Complete Grabor Filter with Random Forest
by: Low, Jeng Lam
Published: (2013)
by: Low, Jeng Lam
Published: (2013)
Google upgrades mapping tools
Published: (2008)
Published: (2008)
Mapping Net Primary Productivity of Peninsular Malaysia Forest Using Satellite Data
by: Ibrahim, Ab. Latif, et al.
Published: (2005)
by: Ibrahim, Ab. Latif, et al.
Published: (2005)
A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem
by: Mohd Pozi, Muhammad Syafiq
Published: (2016)
by: Mohd Pozi, Muhammad Syafiq
Published: (2016)
A method of mapping forest fuel types in peat swamp forest
by: Mohd Razali, Sheriza, et al.
Published: (2012)
by: Mohd Razali, Sheriza, et al.
Published: (2012)
Flood inundation mapping in the Kelantan River Basin, Malaysia, using Sentinel-1 SAR and Google Earth Engine
by: Yi, Lin Tew, et al.
Published: (2024)
by: Yi, Lin Tew, et al.
Published: (2024)
Marine and human habitat mapping for the Coral Triangle Initiative region of Sabah using Landsat and Google Earth imagery
by: Hossain, Mohammad Shawkat, et al.
Published: (2016)
by: Hossain, Mohammad Shawkat, et al.
Published: (2016)
Forecasting of Realised Volatility with the Random Forests Algorithm
by: Luong, C., et al.
Published: (2018)
by: Luong, C., et al.
Published: (2018)
Unsupervised Process Fault Detection with Random Forests
by: Auret, L., et al.
Published: (2010)
by: Auret, L., et al.
Published: (2010)
Classification of cervical cancer using random forest
by: Bahirah, Mohd Bashah, et al.
Published: (2022)
by: Bahirah, Mohd Bashah, et al.
Published: (2022)
Classification Of Microarray Datasets Using
Random Forest
by: Ng, Ee Ling
Published: (2009)
by: Ng, Ee Ling
Published: (2009)
Landslide susceptibility mapping using support vector machine and GIS at the Golestan province, Iran
by: Pourghasemi, Hamid Reza, et al.
Published: (2013)
by: Pourghasemi, Hamid Reza, et al.
Published: (2013)
Conditioning factors determination for landslide susceptibility mapping using support vector machine learning
by: Kalantar, Bahareh, et al.
Published: (2019)
by: Kalantar, Bahareh, et al.
Published: (2019)
Improved feature extraction and lexicon reduction methods classified by support vector machine for Farsi handwritten word recognition system
by: Akbarpour, Shahin
Published: (2011)
by: Akbarpour, Shahin
Published: (2011)
Assessing leaf scale measurement for nitrogen content of oil palm: performance of discriminant analysis and support vector machine classifiers
by: Amirruddin, Amiratul Diyana, et al.
Published: (2017)
by: Amirruddin, Amiratul Diyana, et al.
Published: (2017)
Waqf based forest biobank: a forest protection mechanism for Peninsular Malaysia
by: Yaakob, Adzidah, et al.
Published: (2018)
by: Yaakob, Adzidah, et al.
Published: (2018)
Dynamics of classified forests in the urban district of Bobo-Dioulasso in Burkina Faso
by: Francoise, Valea, et al.
Published: (2024)
by: Francoise, Valea, et al.
Published: (2024)
Tropical forest and the Chewong in peninsular Malaysia
by: Sittimongkol, Saifon
Published: (2019)
by: Sittimongkol, Saifon
Published: (2019)
Similar Items
-
Comparison Of Google Earth Engine- Based Machine Learning Classifiers For Mapping Aquaculture Ponds In Sungai Udang, Penang
by: Rajandran, Arvinth
Published: (2023) -
Multi-temporal, multi-sensor land use/land cover mapping: Google Earth Engine and Random Forest for the classification of the Scottish flow country
by: Sutherland, Neil
Published: (2021) -
Oil palm mapping over Peninsular Malaysia using Google Earth Engine and machine learning algorithms
by: Shaharum, Nur Shafira Nisa, et al.
Published: (2020) -
Churn Forecast Portal using Random Forest Classifier
by: Arpan, Chakraborty, et al.
Published: (2024) -
Teaching Sustainability with Overlay Mapping and Google Earth
by: Stocker, Laura, et al.
Published: (2009)