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 …
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 …
[HTML][HTML] Optical remotely sensed time series data for land cover classification: A review
Accurate land cover information is required for science, monitoring, and reporting. Land
cover changes naturally over time, as well as a result of anthropogenic activities. Monitoring …
cover changes naturally over time, as well as a result of anthropogenic activities. Monitoring …
Unmanned aerial vehicle for remote sensing applications—A review
H Yao, R Qin, X Chen - Remote Sensing, 2019 - mdpi.com
The unmanned aerial vehicle (UAV) sensors and platforms nowadays are being used in
almost every application (eg, agriculture, forestry, and mining) that needs observed …
almost every application (eg, agriculture, forestry, and mining) that needs observed …
[BOOK][B] Classification methods for remotely sensed data
P Mather, B Tso - 2016 - taylorfrancis.com
Since the publishing of the first edition of Classification Methods for Remotely Sensed Data
in 2001, the field of pattern recognition has expanded in many new directions that make use …
in 2001, the field of pattern recognition has expanded in many new directions that make use …
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 …
Land cover 2.0
Interest in knowing more about the Earth's land cover and how it has changed over time
motivated the mission and sensor design of early terrestrial remote sensing systems. Rapid …
motivated the mission and sensor design of early terrestrial remote sensing systems. Rapid …
Understanding spatio-temporal patterns of land use/land cover change under urbanization in Wuhan, China, 2000–2019
Exploring land use structure and dynamics is critical for urban planning and management.
This study attempts to understand the Wuhan development mode since the beginning of the …
This study attempts to understand the Wuhan development mode since the beginning of the …
Remote sensing and machine learning for crop water stress determination in various crops: a critical review
The remote sensing (RS) technique is less cost-and labour-intensive than ground-based
surveys for diverse applications in agriculture. Machine learning (ML), a branch of artificial …
surveys for diverse applications in agriculture. Machine learning (ML), a branch of artificial …
Effects of land use and land cover change on ecosystem services in the Koshi River Basin, Eastern Nepal
The provision of ecosystem services is directly related to the type of land use and land cover
and management practices in a given area. Changes in land use and land cover can alter …
and management practices in a given area. Changes in land use and land cover can alter …