[HTML][HTML] Google Earth Engine and artificial intelligence (AI): a comprehensive review

L Yang, J Driscol, S Sarigai, Q Wu, H Chen, CD Lippitt - Remote Sensing, 2022‏ - mdpi.com
Remote sensing (RS) plays an important role gathering data in many critical domains (eg,
global climate change, risk assessment and vulnerability reduction of natural hazards …

Support vector machine versus random forest for remote sensing image classification: A meta-analysis and systematic review

M Sheykhmousa, M Mahdianpari… - IEEE Journal of …, 2020‏ - ieeexplore.ieee.org
Several machine-learning algorithms have been proposed for remote sensing image
classification during the past two decades. Among these machine learning algorithms …

Google Earth Engine for geo-big data applications: A meta-analysis and systematic review

H Tamiminia, B Salehi, M Mahdianpari… - ISPRS journal of …, 2020‏ - Elsevier
Abstract Google Earth Engine (GEE) is a cloud-based geospatial processing platform for
large-scale environmental monitoring and analysis. The free-to-use GEE platform provides …

[HTML][HTML] Google Earth Engine: a global analysis and future trends

A Velastegui-Montoya, N Montalván-Burbano… - Remote Sensing, 2023‏ - mdpi.com
The continuous increase in the volume of geospatial data has led to the creation of storage
tools and the cloud to process data. Google Earth Engine (GEE) is a cloud-based platform …

[HTML][HTML] 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 …

Wetland map** in East Asia by two-stage object-based Random Forest and hierarchical decision tree algorithms on Sentinel-1/2 images

M Wang, D Mao, Y Wang, X ** of soil organic carbon concentration with 3D machine learning and satellite observations
C Sothe, A Gonsamo, J Arabian, J Snider - Geoderma, 2022‏ - Elsevier
Canada has extensive forests and peatlands that play key roles in global carbon cycle.
Canadian soils and peatlands are assumed to store approximately 20% of the world's soil …

A large-scale change monitoring of wetlands using time series Landsat imagery on Google Earth Engine: a case study in Newfoundland

M Mahdianpari, H Jafarzadeh, JE Granger… - GIScience & Remote …, 2020‏ - Taylor & Francis
Wetlands across Canada have been, and continue to be, lost or altered under the influence
of both anthropogenic and natural activities. The ability to assess the rate of change to …