Random forest in remote sensing: A review of applications and future directions
A random forest (RF) classifier is an ensemble classifier that produces multiple decision
trees, using a randomly selected subset of training samples and variables. This classifier …
trees, using a randomly selected subset of training samples and variables. This classifier …
Review of studies on tree species classification from remotely sensed data
Spatially explicit information on tree species composition of managed and natural forests,
plantations and urban vegetation provides valuable information for nature conservationists …
plantations and urban vegetation provides valuable information for nature conservationists …
Individual tree segmentation and tree species classification in subtropical broadleaf forests using UAV-based LiDAR, hyperspectral, and ultrahigh-resolution RGB data
Accurate classification of individual tree species is essential for inventorying, managing, and
protecting forest resources. Individual tree species classification in subtropical forests …
protecting forest resources. Individual tree species classification in subtropical forests …
Comparison of random forest, k-nearest neighbor, and support vector machine classifiers for land cover classification using Sentinel-2 imagery
P Thanh Noi, M Kappas - Sensors, 2017 - mdpi.com
In previous classification studies, three non-parametric classifiers, Random Forest (RF), k-
Nearest Neighbor (kNN), and Support Vector Machine (SVM), were reported as the foremost …
Nearest Neighbor (kNN), and Support Vector Machine (SVM), were reported as the foremost …
Comparison of support vector machine, random forest and neural network classifiers for tree species classification on airborne hyperspectral APEX images
E Raczko, B Zagajewski - European Journal of Remote Sensing, 2017 - Taylor & Francis
Knowledge of tree species composition in a forest is an important topic in forest
management. Accurate tree species maps allow for much more detailed and in-depth …
management. Accurate tree species maps allow for much more detailed and in-depth …
Tree species classification with random forest using very high spatial resolution 8-band WorldView-2 satellite data
Tree species diversity is a key parameter to describe forest ecosystems. It is, for example,
important for issues such as wildlife habitat modeling and close-to-nature forest …
important for issues such as wildlife habitat modeling and close-to-nature forest …
Classification of Zambian grasslands using random forest feature importance selection during the optimal phenological period
Y Zhao, W Zhu, P Wei, P Fang, X Zhang, N Yan… - Ecological …, 2022 - Elsevier
It is important to conduct grassland resource surveys for the scientific management of
grassland resources. Currently, remote sensing technology is widely used to classify land …
grassland resources. Currently, remote sensing technology is widely used to classify land …
Hyperspectral classification of plants: A review of waveband selection generalisability
Hyperspectral sensing, measuring reflectance over visible to shortwave infrared
wavelengths, has enabled the classification and map** of vegetation at a range of …
wavelengths, has enabled the classification and map** of vegetation at a range of …
Map** urban tree species using integrated airborne hyperspectral and LiDAR remote sensing data
Map** tree species within urban areas is essential for sustainable urban planning as well
as to improve our understanding of the role of urban vegetation as an ecological service …
as to improve our understanding of the role of urban vegetation as an ecological service …
[책][B] Fundamentals of satellite remote sensing: An environmental approach
E Chuvieco - 2020 - taylorfrancis.com
Fundamentals of Satellite Remote Sensing: An Environmental Approach, Third Edition, is a
definitive guide to remote sensing systems that focuses on satellite-based remote sensing …
definitive guide to remote sensing systems that focuses on satellite-based remote sensing …