Effective delineation of rare metal-bearing granites from remote sensing data using machine learning methods: A case study from the Umm Naggat Area, Central …
MA Abdelkader, Y Watanabe, A Shebl… - Ore Geology …, 2022 - Elsevier
Albitized granite (ABG) is considered as one of the most significant hosts of rare metals
(RMs). Consequently, adequate recognition of ABG through proper lithological …
(RMs). Consequently, adequate recognition of ABG through proper lithological …
Detecting Lithium (Li) mineralizations from space: Current research and future perspectives
Optical and thermal remote sensing data have been an important tool in geological
exploration for certain deposit types. However, the present economic and technological …
exploration for certain deposit types. However, the present economic and technological …
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 …
[HTML][HTML] Geological mapping using remote sensing data: A comparison of five machine learning algorithms, their response to variations in the spatial distribution of …
MJ Cracknell, AM Reading - Computers & Geosciences, 2014 - Elsevier
Abstract Machine learning algorithms (MLAs) are a powerful group of data-driven inference
tools that offer an automated means of recognizing patterns in high-dimensional data …
tools that offer an automated means of recognizing patterns in high-dimensional data …
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 kernel functions analysis for support vector machines for land cover classification
T Kavzoglu, I Colkesen - International Journal of Applied Earth Observation …, 2009 - Elsevier
Information about the Earth's surface is required in many wide-scale applications. Land
cover/use classification using remotely sensed images is one of the most common …
cover/use classification using remotely sensed images is one of the most common …
Performance evaluation of MLE, RF and SVM classification algorithms for watershed scale land use/land cover mapping using sentinel 2 bands
VK Rana, TMV Suryanarayana - Remote Sensing Applications: Society …, 2020 - Elsevier
The land use and land cover map plays a significant role in agricultural, water resources
planning, management, and monitoring programs at regional and national levels and is an …
planning, management, and monitoring programs at regional and national levels and is an …
[HTML][HTML] Predicting outcome and recovery after stroke with lesions extracted from MRI images
Here, we present and validate a method that lets us predict the severity of cognitive
impairments after stroke, and the likely course of recovery over time. Our approach employs …
impairments after stroke, and the likely course of recovery over time. Our approach employs …
Mapping maximum urban air temperature on hot summer days
Air temperature is an essential component in microclimate and environmental health
research, but difficult to map in urban environments because of strong temperature …
research, but difficult to map in urban environments because of strong temperature …
Semi-automatization of support vector machines to map lithium (Li) bearing pegmatites
Machine learning (ML) algorithms have shown great performance in geological remote
sensing applications. The study area of this work was the Fregeneda–Almendra region …
sensing applications. The study area of this work was the Fregeneda–Almendra region …