This research conducted to estimate fresh fruit bunch (FFB) of oil palm and their distribution using remote sensing technique. Cimulang oil palm plantation was choose as study area. First step, estimated the age of oil palm trees based on their canopy density as the result from Landsat 8 OLI analysis and classified into five class.
Understanding biomass waste potential is very important for further utilization. Remote sensing technique can be used to detect oil palm trees age based on the canopy density and to estimate the amount of EFB in further analysis.
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Objective of research : - estimate oil palm trees age based on canopy density using remote sensing technique - estimate fresh fruit bunch and empty fruit bunch production based on oil palm trees
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IOP Conference Series: Earth and Environmental Science PAPER OPEN ACCESS Estimating the age of oil palm trees using remote sensing technique To cite this article: A C Fitrianto et al 2025 IOP Conf. Ser.: Earth Environ.
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Oil palm plantations are the largest oil-producing plant and are included in the multipurpose plant category as a contributing economy and reducing the poverty. Oil palm age is one of the factors that support the growth and production process of oil palm. We used Landsat 8 Operational Land Imager (OLI) to estimate the oil palm age. The aims in this study are to analyse the relationship between
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Detecting nutrients deficiencies of oil palm trees using remotely sensed data To cite this article: Faradina Marzukhi et al 2016 IOP Conf. Ser.: Earth Environ. Sci. 37 012040 View the article online for updates and enhancements. Related content Estimating the age of oil palm trees using remote sensing technique A C Fitrianto, A Darmawan, K
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measures for estimating oil palm age. International Journal of Remote Sensing, 40(19), 7516-7537. To classify the age of the tree. SPOT 5 Set of textures were used (mean, variance, correlation and etc) Optimized window size and number of texture measurements for oil palm ages classification with accuracy of 84%
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textural measures for estimating oil palm age international journal of remote sensing evaluation of modis gross primary productivity and land cover products for the humid tropics using oil palm trees in peninsular malaysia and google earth imagery estimating and calculating carbon sequestration value of oil palm by using remote sensing
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Oil Palm (Elaeis guineensis Jacq.) has recorded a boom production the last decades and its main productive zone is inside the tropics that meet the best biophysical conditions. Investors as well as geospatial practitioners are increasingly interested on the best growing and harvesting conditions. So said, the aim of this paper is to select the best oil palm planting site through the best
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Age Of Oil Palm Trees. The relationship between tree height and age was significant which supports the polynomial regression function (PRF) model with a kernel size for under 10-12-year-old oil palm trees, while exponential regression function (ERF) is more fitted for older trees (i.e., 22 years old).
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In oil palm plantations, we prepared 55 fresh fruit bunches to identify their ripeness and forecast harvest time. Based on the field test performance, the inductive sensor system can determine the oil palm ripeness with an accuracy of 100 % and forecast the harvest time with RMSE of 13.45.
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The authors found a precipitation significant effect on the backscatter. Also scattering from large leaves of mature palm trees significantly changed the estimates [42]. This definitely needs more investigation. The measurement of changes in oil palm plantation expansion does not seem to be a major problem using multimodal SAR imagery [16].
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There is an urgent need to monitor the expansion of oil palm agriculture, particularly in the tropical biodiversity-hotspot regions where oil palm agriculture commonly takes place in habitats such as tropical peatlands in Malaysia and Indonesia (Wicke et al., 2011).Stakeholders (e.g. government agencies) require reliable, up-to-date and accurate remote sensing data to facilitate decision
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Herv茅 Nonw猫gnon Sayimi Aholoukp猫, Bernard Dubos, Philippe Deleporte, Albert Flori, Lucien Guillaume Amadji, Jean-Luc Chotte and Didier Blavet, Allometric equations for estimating oil palm stem biomass in the ecological context of Benin, West Africa, Trees, 10.1007/s00468-018-1742-8, 32, 6, (1669-1680), (2025).
Get Pricetextural measures for estimating oil palm age international journal of remote sensing evaluation of modis gross primary productivity and land cover products for the humid tropics using oil palm trees in peninsular malaysia and google earth imagery estimating and calculating carbon sequestration value of oil palm by using remote sensing
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There is an urgent need to monitor the expansion of oil palm agriculture, particularly in the tropical biodiversity-hotspot regions where oil palm agriculture commonly takes place in habitats such as tropical peatlands in Malaysia and Indonesia (Wicke et al., 2011).Stakeholders (e.g. government agencies) require reliable, up-to-date and accurate remote sensing data to facilitate decision
Get Price
In oil palm plantations, we prepared 55 fresh fruit bunches to identify their ripeness and forecast harvest time. Based on the field test performance, the inductive sensor system can determine the oil palm ripeness with an accuracy of 100 % and forecast the harvest time with RMSE of 13.45.
Get Price
The Journal of Applied Remote Sensing (JARS) is an online journal that optimizes the communication of concepts, information, and progress within the remote sensing community to improve the societal benefit for monitoring and management of natural disasters, weather forecasting, agricultural and urban land-use planning, environmental quality monitoring, ecological restoration, and numerous
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Jo茫o M.B. Carreiras, Joshua Jones, Richard M. Lucas and Yosio E. Shimabukuro, Mapping major land cover types and retrieving the age of secondary forests in the Brazilian by combining single-date optical and radar remote sensing data, Remote Sensing of Environment, 10.1016/j.rse.2017.03.016, 194, (16-32), (2017).
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The rapid expansion of oil palm cultivation in the Neotropics has generated great debate around possible biodiversity impacts. Colombia, for example, is the largest producer of oil palm in the Americas, but the effects of oil palm cultivation on native fauna are poorly understood. Here, we compared how richness, abundance and composition of terrestrial mammal species differ between oil palm
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Monitoring biodiversity in the Anthropocene using remote sensing in species distribution models. Remote sensing of environment, 239, p. 111626. Co-producing a Research Agenda for Sustainable Palm Oil. Estimating population and livestock density of mobile pastoralists and sedentary settlements in the southeastern Lake Chad area.
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The rapid expansion of oil palm cultivation in the Neotropics has generated great debate around possible biodiversity impacts. Colombia, for example, is the largest producer of oil palm in the Americas, but the effects of oil palm cultivation on native fauna are poorly understood. Here, we compared how richness, abundance and composition of terrestrial mammal species differ between oil palm
Get Price
The Journal of Applied Remote Sensing (JARS) is an online journal that optimizes the communication of concepts, information, and progress within the remote sensing community to improve the societal benefit for monitoring and management of natural disasters, weather forecasting, agricultural and urban land-use planning, environmental quality monitoring, ecological restoration, and numerous
Get Price
Jo茫o M.B. Carreiras, Joshua Jones, Richard M. Lucas and Yosio E. Shimabukuro, Mapping major land cover types and retrieving the age of secondary forests in the Brazilian by combining single-date optical and radar remote sensing data, Remote Sensing of Environment, 10.1016/j.rse.2017.03.016, 194, (16-32), (2017).
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Monitoring biodiversity in the Anthropocene using remote sensing in species distribution models. Remote sensing of environment, 239, p. 111626. Co-producing a Research Agenda for Sustainable Palm Oil. Estimating population and livestock density of mobile pastoralists and sedentary settlements in the southeastern Lake Chad area.
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This has occurred despite recent research that has called the oftustification of poverty alleviation for oil palm development into question, particularly in remote areas with high forest cover, where oil palm development is associated with reductions in wellbeing indicators (Santika, Wilson, Budiharta, Law, et al., 2025).
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Monitoring biodiversity in the Anthropocene using remote sensing in species distribution models. Remote sensing of environment, 239, p. 111626. the case of multi-stakeholder platforms on oil palm in Myanmar (Unpublished). In: Leverage Points conference. trees and livelihoods, 27(2), pp. 86-102.
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Skewed contributions of individual trees to indirect nature experiences. (UAV) derived structure-from-motion photogrammetry point clouds for oil palm (Elaeis guineensis) canopy segmentation and height estimation. Waveform lidar over vegetation: an evaluation of inversion methods for estimating return energy. Remote Sensing of
Get Price隆opscience.iop.org. Home Search Collections Journals About Contact us My IOPscience. Measurement and monitoring needs, capabilities and potential for addressing reduced emissions from deforestation and forest degradation under REDD+. This content has been downloaded from IOPscience. Please scroll down to see the full text.
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This has occurred despite recent research that has called the oftustification of poverty alleviation for oil palm development into question, particularly in remote areas with high forest cover, where oil palm development is associated with reductions in wellbeing indicators (Santika, Wilson, Budiharta, Law, et al., 2025).
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Monitoring biodiversity in the Anthropocene using remote sensing in species distribution models. Remote sensing of environment, 239, p. 111626. the case of multi-stakeholder platforms on oil palm in Myanmar (Unpublished). In: Leverage Points conference. trees and livelihoods, 27(2), pp. 86-102.
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A similar approach has been used to predict the distribution of trees species across South America, using the leaf area index and the normalised difference vegetation index data (both derived from multispectral SRS; Box 1) in combination with canopy moisture and roughness metrics derived from radar data (Prateslark, Saatchi, & Agosti, 2008).
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Topics are addressed using no more technical jargon than necessary, and without presupposing any advanced knowledge of biology or the philosophy of science on the part of the reader. Discussion questions are also provided to encourage reader reflection.
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A Review of Image Denoising Algorithms, with a New One . Related Databases. Estimating the Noise Level Function with the Tree of Shapes and Non-parametric Statistics. Computer Analysis of Images and Patterns, 377-388. A remote sensing image enhancement method using mean filter and unsharp masking in non-subsampled contourlet transform
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Skewed contributions of individual trees to indirect nature experiences. (UAV) derived structure-from-motion photogrammetry point clouds for oil palm (Elaeis guineensis) canopy segmentation and height estimation. Waveform lidar over vegetation: an evaluation of inversion methods for estimating return energy. Remote Sensing of
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tropical deforestation, predictive models, orangutan, oil palm plantations, road construction, RED, Sumatra Taungya is an age-old forest plantation practice in many parts of the world. Land is cleared and initially planted with both food crops and tree seedlings
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