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 …
[HTML][HTML] Basic tenets of classification algorithms K-nearest-neighbor, support vector machine, random forest and neural network: A review
In this paper, sixty-eight research articles published between 2000 and 2017 as well as
textbooks which employed four classification algorithms: K-Nearest-Neighbor (KNN) …
textbooks which employed four classification algorithms: K-Nearest-Neighbor (KNN) …
Hyperspectral image classification with convolutional neural network and active learning
Deep neural network has been extensively applied to hyperspectral image (HSI)
classification recently. However, its success is greatly attributed to numerous labeled …
classification recently. However, its success is greatly attributed to numerous labeled …
Review of machine learning approaches for biomass and soil moisture retrievals from remote sensing data
The enormous increase of remote sensing data from airborne and space-borne platforms, as
well as ground measurements has directed the attention of scientists towards new and …
well as ground measurements has directed the attention of scientists towards new and …
Geographic object-based image analysis (GEOBIA): Emerging trends and future opportunities
Over the last two decades (since ca. 2000), Geographic Object-Based Image Analysis
(GEOBIA) has emerged as a new paradigm to analyzing high-spatial resolution remote …
(GEOBIA) has emerged as a new paradigm to analyzing high-spatial resolution remote …
Hyperspectral image classification with Markov random fields and a convolutional neural network
This paper presents a new supervised classification algorithm for remotely sensed
hyperspectral image (HSI) which integrates spectral and spatial information in a unified …
hyperspectral image (HSI) which integrates spectral and spatial information in a unified …
Future scenarios based on a CA-Markov land use and land cover simulation model for a tropical humid basin in the Cerrado/Atlantic forest ecotone of Brazil
Recently, the advancement of agriculture in Brazil has caused very serious problems, such
as deforestation and an increase in the amount of pesticides and suspended sediment that …
as deforestation and an increase in the amount of pesticides and suspended sediment that …
Improving accuracy estimation of Forest Aboveground Biomass based on incorporation of ALOS-2 PALSAR-2 and Sentinel-2A imagery and machine learning: A case …
The main objective of this research is to investigate the potential combination of Sentinel-2A
and ALOS-2 PALSAR-2 (Advanced Land Observing Satellite-2 Phased Array type L-band …
and ALOS-2 PALSAR-2 (Advanced Land Observing Satellite-2 Phased Array type L-band …
Land-use/cover classification in a heterogeneous coastal landscape using RapidEye imagery: evaluating the performance of random forest and support vector …
Mapping of patterns and spatial distribution of land-use/cover (LULC) has long been based
on remotely sensed data. In the recent past, efforts to improve the reliability of LULC maps …
on remotely sensed data. In the recent past, efforts to improve the reliability of LULC maps …
A new synergistic approach for monitoring wetlands using Sentinels-1 and 2 data with object-based machine learning algorithms
A Whyte, KP Ferentinos, GP Petropoulos - Environmental Modelling & …, 2018 - Elsevier
In this work the synergistic use of Sentinel-1 and 2 combined with the System for Automated
Geoscientific Analyses (SAGA) Wetness Index in the content of land use/cover (LULC) …
Geoscientific Analyses (SAGA) Wetness Index in the content of land use/cover (LULC) …