Land cover classification using Google Earth Engine and random forest classifier—The role of image composition

TN Phan, V Kuch, LW Lehnert - Remote Sensing, 2020 - mdpi.com
Land cover information plays a vital role in many aspects of life, from scientific and economic
to political. Accurate information about land cover affects the accuracy of all subsequent …

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 …

The arctic amplification and its impact: A synthesis through satellite observations

I Esau, LH Pettersson, M Cancet, B Chapron… - Remote Sensing, 2023 - mdpi.com
Arctic climate change has already resulted in amplified and accelerated regional warming,
or the Arctic amplification. Satellite observations have captured this climate phenomenon in …

Trends in satellite Earth observation for permafrost related analyses—A review

M Philipp, A Dietz, S Buchelt, C Kuenzer - Remote Sensing, 2021 - mdpi.com
Climate change and associated Arctic amplification cause a degradation of permafrost
which in turn has major implications for the environment. The potential turnover of frozen …

Land use/land cover changes and their driving factors in the Northeastern Tibetan Plateau based on Geographical Detectors and Google Earth Engine: A case study …

C Liu, W Li, G Zhu, H Zhou, H Yan, P Xue - Remote Sensing, 2020 - mdpi.com
As an important production base for livestock and a unique ecological zone in China, the
northeast Tibetan Plateau has experienced dramatic land use/land cover (LULC) changes …

Pixel-vs. Object-based landsat 8 data classification in google earth engine using random forest: The case study of maiella national park

A Tassi, D Gigante, G Modica, L Di Martino, M Vizzari - Remote sensing, 2021 - mdpi.com
With the general objective of producing a 2018–2020 Land Use/Land Cover (LULC) map of
the Maiella National Park (central Italy), useful for a future long-term LULC change analysis …

Continuous monitoring of lake dynamics on the Mongolian Plateau using all available Landsat imagery and Google Earth Engine

Y Zhou, J Dong, X Xiao, R Liu, Z Zou, G Zhao… - Science of the Total …, 2019 - Elsevier
Lakes are important water resources on the Mongolian Plateau (MP) for human's livelihood
and production as well as maintaining ecosystem services. Previous studies, based on the …

The role of blue green infrastructure in the urban thermal environment across seasons and local climate zones in East Africa

X Li, LC Stringer, M Dallimer - Sustainable Cities and Society, 2022 - Elsevier
Rapid urbanisation and climate change are two major trends in Africa in need of further
investigation. In this paper, the urban thermal environment and vegetation abundance in …

Land cover changes and their driving mechanisms in Central Asia from 2001 to 2017 supported by Google Earth Engine

Y Hu, Y Hu - Remote Sensing, 2019 - mdpi.com
Limited research has been published on land changes and their driving mechanisms in
Central Asia, but this area is an important ecologically sensitive area. Supported by Google …

Monitoring urban expansion and loss of agriculture on the north coast of west java province, Indonesia, using Google Earth engine and intensity analysis

L Gandharum, DM Hartono, A Karsidi… - The Scientific World …, 2022 - Wiley Online Library
Uncontrolled urban expansion resulting from urbanization has a disastrous impact on
agricultural land. This situation is being experienced by the densely populated and fertile …