Journal ArticleDOI
Oil palm mapping over Peninsular Malaysia using Google Earth Engine and machine learning algorithms
Nur Shafira Nisa Shaharum,Helmi Zulhaidi Mohd Shafri,Wan Azlina Wan Ab Karim Ghani,Sheila Samsatli,Mohammed Mustafa Abdulrahman Al-Habshi,Badronnisa Yusuf +5 more
Reads0
Chats0
TLDR
The efficiency of GEE as a cloud-based free platform to perform bioresource distributions mapping such as oil palm over a large area in Peninsular Malaysia is shown.About:
This article is published in Remote Sensing Applications: Society and Environment.The article was published on 2020-01-01. It has received 43 citations till now.read more
Citations
More filters
Journal ArticleDOI
A Comprehensive Review of Crop Yield Prediction Using Machine Learning Approaches With Special Emphasis on Palm Oil Yield Prediction
TL;DR: In this paper, a review on the use of machine learning algorithms to predict crop yield with special emphasis on palm oil yield prediction is presented, along with a brief discussion on the overview of widely used features and prediction algorithms.
Journal ArticleDOI
Machine learning information fusion in Earth observation: A comprehensive review of methods, applications and data sources
Sancho Salcedo-Sanz,Pedram Ghamisi,Maria Piles,Martin Werner,Lucas Cuadra,Álvaro Moreno-Martínez,Emma Izquierdo-Verdiguier,Jordi Muñoz-Marí,Amirhosein Mosavi,Gustau Camps-Valls +9 more
TL;DR: A thorough review of the latest work on information fusion for Earth observation, with a practical intention, not only focusing on describing the most relevant previous works in the field, but also the most important Earth observation applications where ML information fusion has obtained significant results.
Journal ArticleDOI
High-resolution global map of smallholder and industrial closed-canopy oil palm plantations
Adrià Descals,Serge A. Wich,Erik Meijaard,Erik Meijaard,David L. A. Gaveau,Stephen Peedell,Zoltan Szantoi +6 more
TL;DR: In this paper, the authors presented a map of closed-canopy oil palm plantations by typology (industrial versus small-holder plantations) at the global scale and with unprecedented detail (10m resolution) for the year 2019.
Journal ArticleDOI
A review of industry 4.0 revolution potential in a sustainable and renewable palm oil industry: HAZOP approach
Chun Hsion Lim,Steven Lim,Bing Shen How,Wendy Pei Qin Ng,Sue Lin Ngan,Wei Dong Leong,Hon Loong Lam +6 more
TL;DR: In this paper, a Hazard and Operability Analysis (HAZOP) approach is adopted to ensure a detailed evaluation of the existing problems, and to identify potential implementation of Industry 4.0 technologies in the palm oil industry.
Journal ArticleDOI
Machine Learning Information Fusion in Earth Observation: A Comprehensive Review of Methods, Applications and Data Sources
Sancho Salcedo-Sanz,Pedram Ghamisi,Maria Piles,Martin Werner,Lucas Cuadra,Álvaro Moreno-Martínez,Emma Izquierdo-Verdiguier,Jordi Muñoz-Marí,Amirhosein Mosavi,Gustau Camps-Valls +9 more
TL;DR: In this article, the most important information fusion data-driven algorithms based on Machine Learning (ML) techniques for problems in Earth observation are reviewed. And a thorough review of the latest work on information fusion for Earth observation, with a practical intention, not only focusing on describing the most relevant previous works in the field, but also some important Earth observation applications where ML information fusion has obtained significant results.
References
More filters
Journal ArticleDOI
Google Earth Engine: Planetary-scale geospatial analysis for everyone
TL;DR: Google Earth Engine is a cloud-based platform for planetary-scale geospatial analysis that brings Google's massive computational capabilities to bear on a variety of high-impact societal issues including deforestation, drought, disaster, disease, food security, water management, climate monitoring and environmental protection.
Journal ArticleDOI
Random forest in remote sensing: A review of applications and future directions
Mariana Belgiu,Lucian Drăguţ +1 more
TL;DR: This review has revealed that RF classifier can successfully handle high data dimensionality and multicolinearity, being both fast and insensitive to overfitting.
Journal ArticleDOI
Summary of Current Radiometric Calibration Coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI Sensors
TL;DR: In this paper, a summary of the current equations and rescaling factors for converting calibrated Digital Numbers (DNs) to absolute units of at-sensor spectral radiance, Top-Of- Atmosphere (TOA) reflectance, and atsensor brightness temperature is provided.
Journal ArticleDOI
Random forest classifier for remote sensing classification
TL;DR: It is suggested that the random forest classifier performs equally well to SVMs in terms of classification accuracy and training time and the number of user‐defined parameters required byrandom forest classifiers is less than the number required for SVMs and easier to define.
Journal ArticleDOI
Landsat-8: Science and Product Vision for Terrestrial Global Change Research
David P. Roy,Michael A. Wulder,Thomas R. Loveland,Curtis E. Woodcock,Richard G. Allen,Martha C. Anderson,Dennis L. Helder,James R. Irons,Daniel M. Johnson,Robert E. Kennedy,Ted Scambos,Crystal B. Schaaf,John R. Schott,Yongwei Sheng,Eric Vermote,Alan Belward,Robert Bindschadler,Warren B. Cohen,Feng Gao,James D. Hipple,Patrick Hostert,Justin L. Huntington,Christopher O. Justice,Ayse Kilic,V. Kovalskyy,Zhongping Lee,Leo Lymburner,Jeffrey G. Masek,Joel McCorkel,Yanmin Shuai,Ricardo Trezza,James E. Vogelmann,Randolph H. Wynne,Zhe Zhu +33 more
TL;DR: Landsat 8, a NASA and USGS collaboration, acquires global moderate-resolution measurements of the Earth's terrestrial and polar regions in the visible, near-infrared, short wave, and thermal infrared as mentioned in this paper.