Výsledky vyhledávání - "forest classification"

Akademický článek

Semi-automated mangrove mapping at National-Scale using Sentinel-2, Sentinel-1, and SRTM data with Google Earth Engine: A case study in Thailand

Autor: Surachet Pinkeaw, Pawita Boonrat, Werapong Koedsin, Alfredo Huete

Publikováno v: Egyptian Journal of Remote Sensing and Space Sciences, Vol 27, Iss 3, Pp 555-564 (2024)

Mangroves are a crucial part of the coastal ecosystem; thus, precise and up-to-date monitoring is essential to guide regional policies and inform conservation strategies. This study investigates the capabilities of semi-automated remote sensing appro

Externí odkaz: https://doaj.org/article/722e44ec534e413bb29c61534126af6e

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Akademický článek

Machine Learning model interpretability using SHAP values: Application to Igneous Rock Classification task

Autor: Antonella S. Antonini, Juan Tanzola, Lucía Asiain, Gabriela R. Ferracutti, Silvia M. Castro, Ernesto A. Bjerg, María Luján Ganuza

Publikováno v: Applied Computing and Geosciences, Vol 23, Iss , Pp 100178- (2024)

El Fierro intrusive body is one of the bodies that compose the La Jovita–Las Aguilas mafic–ultramafic belt, located in the Sierra Grande de San Luis, Argentina. The units of this belt carry a base metal sulfide (BMS) mineralization and platinum g

Externí odkaz: https://doaj.org/article/ecc7fc197246437db2f21351a1dbf5b9

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Akademický článek

Improved random forest classification model combined with C5.0 algorithm for vegetation feature analysis in non-agricultural environments

Autor: Tianyu Wang

Publikováno v: Scientific Reports, Vol 14, Iss 1, Pp 1-13 (2024)

Abstract In response to the challenges posed by the high computational complexity and suboptimal classification performance of traditional random forest algorithms when dealing with high-dimensional and noisy non-agricultural vegetation satellite dat

Externí odkaz: https://doaj.org/article/c8398ba2ab294a0c90ee2b5a38fcf4a1

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Akademický článek

Distribution Characteristics of Benggang in the Middle and Upper Reaches of the Han River

Autor: Liu Na, Zhang Heng, Deng Canlu, Wu Jialong, Xiong Yuankang

Publikováno v: Redai dili, Vol 44, Iss 3, Pp 415-428 (2024)

Benggang (a fragmented erosion landform) have emerged as crucial factors restraining regional economic development, social stability, and ecological conservation due to their suddenness, explosiveness, and unpredictability. Monitoring the dynamic cha

Externí odkaz: https://doaj.org/article/3731d528608749dca6b9121180be7e98

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Akademický článek

Prediction of declarative memory profile in panic disorder patients: a machine learning-based approach

Autor: Felipe Dalvi-Garcia, Laiana Azevedo Quagliato, Donald J. Bearden, Antonio Egidio Nardi

Publikováno v: Brazilian Journal of Psychiatry, Vol 45, Iss 6, Pp 482-490 (2024)

Objective: To develop a classification framework based on random forest (RF) modeling to outline the declarative memory profile of patients with panic disorder (PD) compared to a healthy control sample. Methods: We developed RF models to classify the

Externí odkaz: https://doaj.org/article/f955a657ea86450abe65407e30c6a80c

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Akademický článek

Investigation of classification of support vector machine on the estimation of the deciduous broad-leaved forests area in the north of Iran

Autor: Mohammadreza Tabesh, Seyed Armin Hashemi, Sahar Tabibian, Mohsen Abbasipour, Maghsood Hosseini

Publikováno v: Temas Agrarios, Vol 29, Iss 1, Pp 40-52 (2024)

During the last decades, Caspian forests have been attacked by human interference. Easy access, abundance and diversity of valuable forest products have led to the increase in population density, the creation of new residential areas and the activity

Externí odkaz: https://doaj.org/article/66d7e28aecae487aa3ec18d99d174347

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Akademický článek

Edge Computing Assisted Internet of Things in Sports Management System

Autor: Baolei Zhang, Juan Yang, Yan Peng, Chong Liu

Publikováno v: Tehnički Vjesnik, Vol 31, Iss 4, Pp 1297-1303 (2024)

In recent years, the movement analysis is commonly used to track the risk of injury and strengthen the efficiency of athlete performance. However, most of these devices are costly, found mainly in experimental settings, which analyze a few samples of

Externí odkaz: https://doaj.org/article/3eddcbff0e9740c78bbf408877c9427d

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Akademický článek

Detecting Forest Fires in Southwest China From Remote Sensing Nighttime Lights Using the Random Forest Classification Model

Autor: Yuehan Yu, Lili Liu, Zhijian Chang, Yuanqing Li, Kaifang Shi

Publikováno v: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 10759-10769 (2024)

Forest fires are one of the most common natural disasters and public crisis events, presenting a serious threat to the ecosystem and human security. The traditional forest fire monitoring is time-consuming and inaccurate, but nighttime light remote s

Externí odkaz: https://doaj.org/article/5aa9df8f4a254bf0b186bd7b913336db

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Akademický článek

Random forest and support vector machine classifiers for coastal wetland characterization using the combination of features derived from optical data and synthetic aperture radar dataset

Autor: Sandra Maria Cherian, Rajitha K

Publikováno v: Journal of Water and Climate Change, Vol 15, Iss 1, Pp 29-49 (2024)

Mapping mangrove forests is crucial for their conservation, but it is challenging due to their complex characteristics. Many studies have explored machine learning techniques that use Synthetic Aperture Radar (SAR) and optical data to improve wetland

Externí odkaz: https://doaj.org/article/9630518315c640c7bd8b5d8344817b9f

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