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 …
decades, managing and analyzing of which are not practical using common software …
Google Earth Engine and artificial intelligence (AI): a comprehensive review
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 …
global climate change, risk assessment and vulnerability reduction of natural hazards …
Improved Gaussian mixture model to map the flooded crops of VV and VH polarization data
Accurate and timely monitoring of flooded crop areas is crucial for disaster rescue and loss
assessment. However, most flooded crop monitoring methods based on synthetic aperture …
assessment. However, most flooded crop monitoring methods based on synthetic aperture …
[HTML][HTML] Mapping of crop types and crop sequences with combined time series of Sentinel-1, Sentinel-2 and Landsat 8 data for Germany
L Blickensdörfer, M Schwieder, D Pflugmacher… - Remote sensing of …, 2022 - Elsevier
Monitoring agricultural systems becomes increasingly important in the context of global
challenges like climate change, biodiversity loss, population growth, and the rising demand …
challenges like climate change, biodiversity loss, population growth, and the rising demand …
WHU-Hi: UAV-borne hyperspectral with high spatial resolution (H2) benchmark datasets and classifier for precise crop identification based on deep convolutional …
Unmanned aerial vehicle (UAV)-borne hyperspectral systems can acquire hyperspectral
imagery with a high spatial resolution (which we refer to here as H 2 imagery). As a result of …
imagery with a high spatial resolution (which we refer to here as H 2 imagery). As a result of …
Transfer learning in environmental remote sensing
Abstract Machine learning (ML) has proven to be a powerful tool for utilizing the rapidly
increasing amounts of remote sensing data for environmental monitoring. Yet ML models …
increasing amounts of remote sensing data for environmental monitoring. Yet ML models …
The 10-m crop type maps in Northeast China during 2017–2019
Northeast China is the leading grain production region in China where one-fifth of the
national grain is produced; however, consistent and reliable crop maps are still unavailable …
national grain is produced; however, consistent and reliable crop maps are still unavailable …
Phenology-assisted supervised paddy rice mapping with the Landsat imagery on Google Earth Engine: Experiments in Heilongjiang Province of China from 1990 to …
Accurate spatial distribution maps of paddy rice played crucial roles in food security and
market stability. Decades-spanning Landsat images were useful for long-term paddy rice …
market stability. Decades-spanning Landsat images were useful for long-term paddy rice …
[HTML][HTML] From parcel to continental scale–A first European crop type map based on Sentinel-1 and LUCAS Copernicus in-situ observations
R d'Andrimont, A Verhegghen, G Lemoine… - Remote sensing of …, 2021 - Elsevier
Detailed parcel-level crop type mapping for the whole European Union (EU) is necessary for
the evaluation of agricultural policies. The Copernicus program, and Sentinel-1 (S1) in …
the evaluation of agricultural policies. The Copernicus program, and Sentinel-1 (S1) in …
Mapping cropping intensity in China using time series Landsat and Sentinel-2 images and Google Earth Engine
Cropping intensity has undergone dramatic changes worldwide due to the effects of climate
changes and human management activities. Cropping intensity is an important factor …
changes and human management activities. Cropping intensity is an important factor …