[HTML][HTML] What is going on within google earth engine? A systematic review and meta-analysis

P Pérez-Cutillas, A Pérez-Navarro… - … Society and environment, 2023 - Elsevier
Abstract Google Earth Engine (GEE) is a geospatial processing platform based on geo-
information applications in the 'cloud'. This platform provides free access to huge volumes of …

Land use and land cover mapping using Sentinel-2, Landsat-8 Satellite Images, and Google Earth Engine: A comparison of two composition methods

V Nasiri, A Deljouei, F Moradi, SMM Sadeghi, SA Borz - Remote Sensing, 2022 - mdpi.com
Accurate and real-time land use/land cover (LULC) maps are important to provide precise
information for dynamic monitoring, planning, and management of the Earth. With the advent …

[HTML][HTML] Mapping crop type in Northeast China during 2013–2021 using automatic sampling and tile-based image classification

F Xuan, Y Dong, J Li, X Li, W Su, X Huang… - International Journal of …, 2023 - Elsevier
Northeast China is one of the most major grain banks in China and has an overwhelming
influence on food security. To mitigate the challenges caused by increasing food demands …

Crop mapping using supervised machine learning and deep learning: a systematic literature review

M Alami Machichi, E mansouri, Y Imani… - … Journal of Remote …, 2023 - Taylor & Francis
The ever-increasing global population presents a looming threat to food production. To meet
growing food demands while minimizing negative impacts on water and soil, agricultural …

Applying machine learning classifiers to Sentinel-2 imagery for early identification of cotton fields to advance boll weevil eradication

C Yang, CPC Suh - Computers and Electronics in Agriculture, 2023 - Elsevier
Early identification of cotton fields is critical for boll weevil eradication programs to establish
field traps for monitoring weevil populations. However, most studies on crop type mapping …

Machine learning and food security: insights for agricultural spatial planning in the context of agriculture 4.0

VJPD Martinho, CAS Cunha, ML Pato, PJL Costa… - Applied Sciences, 2022 - mdpi.com
Climate change and global warming interconnected with the new contexts created by the
COVID-19 pandemic and the Russia-Ukraine conflict have brought serious challenges to …

Cropland Extraction in Southern China from Very High-Resolution Images Based on Deep Learning

D Xie, H Xu, X Xiong, M Liu, H Hu, M Xiong, L Liu - Remote Sensing, 2023 - mdpi.com
Accurate cropland information is crucial for the assessment of food security and the
formulation of effective agricultural policies. Extracting cropland from remote sensing …

Assessment of soil suitability using machine learning in arid and semi-arid regions

M Ismaili, S Krimissa, M Namous, A Htitiou… - Agronomy, 2023 - mdpi.com
Increasing agricultural production is a major concern that aims to increase income, reduce
hunger, and improve other measures of well-being. Recently, the prediction of soil-suitability …

Quantifying the impacts of the 2020 flood on Crop production and food security in the middle reaches of the Yangtze river, China

LC Wang, DV Hoang, YA Liou - Remote Sensing, 2022 - mdpi.com
This study uses satellite imagery and geospatial data to examine the impact of floods over
the main planting areas for double-cropping rice and grain crops in the middle reaches of …

The contribution of remote sensing and input feature selection for groundwater level prediction using LSTM neural networks in the Oum Er-Rbia Basin, Morocco

T Bouramtane, M Leblanc, I Kacimi, H Ouatiki… - Frontiers in …, 2023 - frontiersin.org
The planning and management of groundwater in the absence of in situ climate data is a
delicate task, particularly in arid regions where this resource is crucial for drinking water …