Google earth engine cloud computing platform for remote sensing big data applications: A comprehensive review

M Amani, A Ghorbanian, SA Ahmadi… - IEEE Journal of …, 2020 - ieeexplore.ieee.org
Remote sensing (RS) systems have been collecting massive volumes of datasets for
decades, managing and analyzing of which are not practical using common software …

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 …

[HTML][HTML] Identifying the land use land cover (LULC) changes using remote sensing and GIS approach: A case study at Bhaluka in Mymensingh, Bangladesh

MMH Seyam, MR Haque, MM Rahman - Case Studies in Chemical and …, 2023 - Elsevier
LULC is vital to investigate land use patterns and helping forecast future sustainable land
management. The study area is a freshly emerging and quickly industrialized area in …

Progress and trends in the application of Google Earth and Google Earth Engine

Q Zhao, L Yu, X Li, D Peng, Y Zhang, P Gong - Remote Sensing, 2021 - mdpi.com
Earth system science has changed rapidly due to global environmental changes and the
advent of Earth observation technology. Therefore, new tools are required to monitor …

[HTML][HTML] An improved approach for monitoring urban built-up areas by combining NPP-VIIRS nighttime light, NDVI, NDWI, and NDBI

Y Zheng, L Tang, H Wang - Journal of Cleaner Production, 2021 - Elsevier
Timely and accurate extraction of urban built-up areas is crucial to addressing
environmental problems related to fast changes in urban land cover, which is fundamental …

An overview of platforms for big earth observation data management and analysis

VCF Gomes, GR Queiroz, KR Ferreira - Remote Sensing, 2020 - mdpi.com
In recent years, Earth observation (EO) satellites have generated big amounts of geospatial
data that are freely available for society and researchers. This scenario brings challenges for …

Operational flood mapping using multi-temporal Sentinel-1 SAR images: A case study from Bangladesh

K Uddin, MA Matin, FJ Meyer - Remote Sensing, 2019 - mdpi.com
Bangladesh is one of the most flood-affected countries in the world. In the last few decades,
flood frequency, intensity, duration, and devastation have increased in Bangladesh …

Analysis of land use and land cover using machine learning algorithms on google earth engine for Munneru River Basin, India

KN Loukika, VR Keesara, V Sridhar - Sustainability, 2021 - mdpi.com
The growing human population accelerates alterations in land use and land cover (LULC)
over time, putting tremendous strain on natural resources. Monitoring and assessing LULC …

[HTML][HTML] Google Earth Engine, open-access satellite data, and machine learning in support of large-area probabilistic wetland mapping

JN Hird, ER DeLancey, GJ McDermid, J Kariyeva - Remote sensing, 2017 - mdpi.com
Modern advances in cloud computing and machine-leaning algorithms are shifting the
manner in which Earth-observation (EO) data are used for environmental monitoring …

Computer vision and image processing: a paper review

V Wiley, T Lucas - International Journal of Artificial Intelligence Research, 2018 - ijair.id
Computer vision has been studied from many persective. It expands from raw data recording
into techniques and ideas combining digital image processing, pattern recognition, machine …