Implementation of machine-learning classification in remote sensing: An applied review
Machine learning offers the potential for effective and efficient classification of remotely
sensed imagery. The strengths of machine learning include the capacity to handle data of …
sensed imagery. The strengths of machine learning include the capacity to handle data of …
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 …
Comparison of random forest and support vector machine classifiers for regional land cover mapping using coarse resolution FY-3C images
T Adugna, W Xu, J Fan - Remote Sensing, 2022 - mdpi.com
The type of algorithm employed to classify remote sensing imageries plays a great role in
affecting the accuracy. In recent decades, machine learning (ML) has received great …
affecting the accuracy. In recent decades, machine learning (ML) has received great …
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 …
Remote sensing technologies for enhancing forest inventories: A review
Forest inventory and management requirements are changing rapidly in the context of an
increasingly complex set of economic, environmental, and social policy objectives …
increasingly complex set of economic, environmental, and social policy objectives …
Assessing the robustness of Random Forests to map land cover with high resolution satellite image time series over large areas
New remote sensing sensors will acquire High spectral, spatial and temporal Resolution
Satellite Image Time Series (HR-SITS). These new data are of great interest to map land …
Satellite Image Time Series (HR-SITS). These new data are of great interest to map land …
Mapping temperate forest tree species using dense Sentinel-2 time series
Precise information on tree species composition is critical for forest management and
conservation, but mapping tree species with satellite data over large areas is still a …
conservation, but mapping tree species with satellite data over large areas is still a …
Forest stand species mapping using the Sentinel-2 time series
Accurate information regarding forest tree species composition is useful for a wide range of
applications, both for forest management and scientific research. Remote sensing is an …
applications, both for forest management and scientific research. Remote sensing is an …
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 …
A review of practical ai for remote sensing in earth sciences
Integrating Artificial Intelligence (AI) techniques with remote sensing holds great potential for
revolutionizing data analysis and applications in many domains of Earth sciences. This …
revolutionizing data analysis and applications in many domains of Earth sciences. This …