Support vector machine versus random forest for remote sensing image classification: A meta-analysis and systematic review
Several machine-learning algorithms have been proposed for remote sensing image
classification during the past two decades. Among these machine learning algorithms …
classification during the past two decades. Among these machine learning algorithms …
A review on early forest fire detection systems using optical remote sensing
The environmental challenges the world faces nowadays have never been greater or more
complex. Global areas covered by forests and urban woodlands are threatened by natural …
complex. Global areas covered by forests and urban woodlands are threatened by natural …
Support vector machines in remote sensing: A review
A wide range of methods for analysis of airborne-and satellite-derived imagery continues to
be proposed and assessed. In this paper, we review remote sensing implementations of …
be proposed and assessed. In this paper, we review remote sensing implementations of …
A survey of image classification methods and techniques for improving classification performance
Image classification is a complex process that may be affected by many factors. This paper
examines current practices, problems, and prospects of image classification. The emphasis …
examines current practices, problems, and prospects of image classification. The emphasis …
Object-oriented lulc classification in google earth engine combining snic, glcm, and machine learning algorithms
A Tassi, M Vizzari - Remote Sensing, 2020 - mdpi.com
Google Earth Engine (GEE) is a versatile cloud platform in which pixel-based (PB) and
object-oriented (OO) Land Use–Land Cover (LULC) classification approaches can be …
object-oriented (OO) Land Use–Land Cover (LULC) classification approaches can be …
[BOOK][B] Computer processing of remotely-sensed images
Computer Processing of Remotely-Sensed Images A thorough introduction to computer
processing of remotely-sensed images, processing methods, and applications Remote …
processing of remotely-sensed images, processing methods, and applications Remote …
Key issues in rigorous accuracy assessment of land cover products
Accuracy assessment and land cover map** have been inexorably linked throughout the
first 50 years of publication of Remote Sensing of Environment. The earliest developers of …
first 50 years of publication of Remote Sensing of Environment. The earliest developers of …
Comparison of random forest and support vector machine classifiers for regional land cover map** 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 …
[BOOK][B] Geography and geographers: Anglo-American human geography since 1945
R Johnston, JD Sidaway - 2015 - taylorfrancis.com
Geography and Geographers continues to be the most comprehensive and up-to-date
overview of human geography available. It provides a survey of the major debates, key …
overview of human geography available. It provides a survey of the major debates, key …
Support vector machines for classification in remote sensing
Support vector machines (SVM) represent a promising development in machine learning
research that is not widely used within the remote sensing community. This paper reports the …
research that is not widely used within the remote sensing community. This paper reports the …