Search Results - ((canopy algorithm) OR (_ algorithm))

Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm by Al-Jumaili A.H.A., Muniyandi R.C., Hasan M.K., Singh M.J., Paw J.K.S., Al-Jumaily A.

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Detecting canopy openings in logged-over forests: a multi-classifier analysis of PlanetScope imagery by Mawlidan, Nurmala, Ismail, Mohd Hasmadi, Gandaseca, Seca, ., Rahmawaty, Yaakub, Nur Faziera

“…Both SVM and OBIA surpassed the accuracy threshold, with SVM being the most effective in detecting and extracting canopy openings in dense forests. Results demonstrated the potential of PlanetSope imagery and advanced classification algorithms to detect canopy openings in logged-over forests. …”
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Photogrammetric unmanned aerial vehicle for digital terrain model estimation under oil palm tree canopy area / Suzanah Abdullah by Abdullah, Suzanah

“…It was found that WS algorithm recorded the lower RMSE value of 2.824m at 40m flying height, IWS algorithm obtained a lower RMSE value of 2.879m at 80m flying height, OBIA and SG algorithms obtained a lower RMSE value of 2.246m and 2.182m respectively at 100m flying height. …”
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Extracting crown morphology with a low-cost mobile LiDAR scanning system in the natural environment by Wang, Kai, Zhou, Jun, Zhang, Wenhai, Zhang, Baohua

“…The algorithm defined in this study was evaluated with manual measurements as reference, and the morphological parameters of the canopy obtained using the LOAM and LeGO-LOAM algorithms as the basic framework were compared. …”
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Individual-tree segmentation and extraction based on LiDAR point cloud data by Liu, Xiaofeng, Abdullah, Muhamad Taufik, Mustaffa, Mas Rina, Nasharuddin, Nurul Amelina

“…Utilizing LiDAR point cloud data and ground-measured data from 30 plots, we examined the sensitivity of individual tree segmentation to key parameters by varying the grid values of the point cloud distance discriminant clustering algorithm and adjusting the canopy height resolution (CHR) of the watershed algorithm. …”
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Semi-automatic oil palm tree counting from pleiades satellite imagery and airborne LiDAR / Nurul Syafiqah Khalid by Khalid, Nurul Syafiqah

“…This study aimed to develop the automatic oil palm tree counting using remote sensed data and two different algorithms at Felda Pasoh. There are three objectives, firstly, to produce tree height estimation by using the Canopy Height Model (CHM). …”
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Evaluation of tree growth characteristics of harum manis mango from multitemporal UAV image in plantation farm by Muhammad Yusuf, Akmal Alif

“…The contribution of this study is to produce Canopy Height Mapping (CHM) from difference multitemporal UAV data and characterization of mango tree develop using OBIA algorithm to monitoring development Harum Manis Tree. …”
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Synthetic Minority Over-Sampling Technique (SMOTE) and Logistic Model Tree (LMT)-adaptive boosting algorithms for classifying imbalanced datasets of nutrient and chlorophyll sufficiency levels of oil palm (Elaeis guineensis) using spectroradiometers and unmanned aerial vehicles by Amirruddin, Amiratul Diyana, Muharam, Farrah Melissa, Ismail, Mohd Hasmadi, Tan, Ngai Paing, Ismail, Mohd Firdaus

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Geotagged application for durian trees using aerial imagery and vegetation indices algorithm by Mohidem, Nur Adibah, Jeyakumaran, Vikneswaran, M. I., Ab Rahman, Che Ya, Nik Norasma, Rosle, Rhushalshafira, Fazlil Ilahi, Wan Fazilah, Hock, O. C., Mat Su, Ahmad Suhaizi, Tan, Ngai Paing, Ramlee, Shairul Izan

“…The objectives of this study are to geotag the durian trees and to compare several Vegetation Indices (VIs) algorithms (VisibleBand Difference Vegetation Index (VDVI), Visible Atmospherically Resistant Index (VARI), Normalized Green-Red Difference Index (NGRDI), Red-Green Ratio Index (RGRI), Modified Green-Red Vegetation Index (MGRVI), Excess Green Index (ExG), Color Index of Vegetation (CIVE), and Vegetativen (VEG)). …”
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Estimating tree height based on tree crown from UAV imagery / Suzanah Abdullah ... [et al.] by Abdullah, Suzanah, Tahar, Khairul Nizam, Abdul Rashid, Mohd Fadzil, Osoman, Muhammad Ariffin

“…In this study, the UAV technology is explored by applying several algorithms approach to determine tree crown and tree height of a single tree canopy. …”
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Geotagged Application for Durian Trees using Aerial Imagery and Vegetation Indices Algorithm by Mohidem, N. A., Jeya Kumaran, V., Ab Rahman, M. I., Che’Ya, N. N., Rosle, R., Fazlil Ilahi, W. F., Hock, O. C., Mat Su, A. S., Ping, T. N., Izan, S

A Hydrologic Model for Studying the Climate Change Impact on Evapotranspiration and Water Yield in a Humid Tropical Watershed by Nabi, Amjad

“…A procedure was presented and evaluated for subdividing a watershed into GRUs through the application of an unsupervised pattern recognition algorithm in conjunction with topographic data to Landsat Thematic Mapper (TM) data in a GIS environment. …”
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Performance of a photogrammetric digital elevation model in a tropical montane forest environment by Wong, Wilson, Vun Chiong, Satoshi Tsuyuki, Phua, Mui How, Keiko Ioki, Gen Takao

“…More detailed local accuracy evaluation was conducted at block level: 31 1-ha blocks and one 0.25-ha block located over different forest types and characterized by the mean canopy height (range=8.4-41.1 m) and standard deviation (range=2.0-9.8 m) of the ALS-canopy height model (ALS-CHM). …”
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Drought-events and potential impacts on land use/land cover dynamics based on AVHRR data of 1992-2003 for central Iran by Mokhtari, Ahmad

“…The model works based on the seasonal values of Normalized-Difference Vegetation Index (NDVJ) correlated to vegetation canopy cover. The algorithm was compared with the maximum likelihood supervised classification algorithm. …”
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Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification by Myaser, Jwan

“…The last phase involves developing a new fusion algorithm using SVM and Fuzzy K-Means Clustering (FKM) algorithms for Sentinel 2 data to enhance LCM accuracy. …”
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Area-based vs tree-centric approaches to mapping forest carbon in Southeast Asian forests from airborne laser scanning data by David A. Coomes, Michele Dalponte, Tommaso Jucker, Gregory P. Asner, Lindsay F. Banin, David F.R.P. Burslem, Simon L. Lewis, Reuben Nilus, Oliver L. Phillips, Phua, Mui How, Lan Qie

“…We compare the performance of (a) an area-based model developed by Asner and Mascaro (2014), and used primarily in the neotropics hitherto, with (b) a tree centric approach that uses a new algorithm (itcSegment) to locate trees within the ALS canopy height model, measures their heights and crown widths, and calculates biomass from these dimensions. …”
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Quantifying forest disturbance using LiDAR data and time series Landsat images / Syaza Rozali by Rozali, Syaza

“…Two fusion data are tested; 1) SpectralLandsat and 2) SpectralLandsat + HeightALS by Random Forest and Support Vector Machine classification algorithm. The result shows second fusion data having 1 meter Landsat resolution and Airborne LiDAR performed better classification using object-based segmentation and Random Forest classification, about 96% of the overall accuracy with 0.91 kappa index of aggreement. …”
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Evaluation of multiple In Situ and remote sensing system for early detection of Ganoderma boninense infected oil palm by Ahmadi, Seyedeh Parisa

“…This study concluded that remote sensing approach combined with data mining approaches such as ANN algorithms have great potential in monitoring vast plantation areas in a rapid and inexpensive manner.…”
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Implication of image processing algorithm in remote sensing and GIS applications by Pathan, Mubeena, Jusoff, Kamaruzaman, Mohd Sood, Alias, Razali, Yaakob, Qureshi, Barkatullah

“…This review presents evaluation and utilization of different algorithms such as Simple Recursive Algorithm, Backtracking Algorithm, Divide and Conquer Algorithm, Dynamic Algorithm, Branch and Bound Algorithm, Brute Force Algorithm and Randomized Algorithm. …”
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Comparison between Genetic Algorithm and Prey-Predator Algorithm. by Ong, Hong Choon

“…We also compared the performance of this algorithm with the genetic algorithm on selected test problems and we showed that the new algorithm performed better in our publication.…”
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