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 …

An enhanced pixel-based phenological feature for accurate paddy rice map** with Sentinel-2 imagery in Google Earth Engine

R Ni, J Tian, X Li, D Yin, J Li, H Gong, J Zhang… - ISPRS Journal of …, 2021‏ - Elsevier
Accurate paddy rice map** with remote sensing at a regional scale plays critical roles in
agriculture and ecology. Previous studies mainly employed a single key phenological period …

Map** cropland extent of Southeast and Northeast Asia using multi-year time-series Landsat 30-m data using a random forest classifier on the Google Earth Engine …

AJ Oliphant, PS Thenkabail, P Teluguntla… - International Journal of …, 2019‏ - Elsevier
Cropland extent maps are useful components for assessing food security. Ideally, such
products are a useful addition to countrywide agricultural statistics since they are not …

[HTML][HTML] A robust index to extract paddy fields in cloudy regions from SAR time series

S Xu, X Zhu, J Chen, X Zhu, M Duan, B Qiu… - Remote Sensing of …, 2023‏ - Elsevier
Timely and accurate map** of paddy rice cultivation is needed for maintaining sustainable
rice production, ensuring food security, and monitoring water usage. Synthetic Aperture …

Rice crop detection using LSTM, Bi-LSTM, and machine learning models from Sentinel-1 time series

H Crisóstomo de Castro Filho… - Remote Sensing, 2020‏ - mdpi.com
The Synthetic Aperture Radar (SAR) time series allows describing the rice phenological
cycle by the backscattering time signature. Therefore, the advent of the Copernicus Sentinel …

Annual paddy rice planting area and crop** intensity datasets and their dynamics in the Asian monsoon region from 2000 to 2020

J Han, Z Zhang, Y Luo, J Cao, L Zhang, H Zhuang… - Agricultural …, 2022‏ - Elsevier
CONTEXT Timely information on the spatiotemporal trends in annual paddy rice planting
areas (PRA) and crop** intensity (CI) in Asia is important for food security warnings and …

Deep machine learning with Sentinel satellite data to map paddy rice production stages across West Java, Indonesia

KR Thorp, D Drajat - Remote Sensing of Environment, 2021‏ - Elsevier
Indonesia recently implemented a novel, technology-driven approach for conducting
agricultural production surveys, which involves monthly observations at many thousands of …

Map** paddy rice by the object-based random forest method using time series Sentinel-1/Sentinel-2 data

Y Cai, H Lin, M Zhang - Advances in Space Research, 2019‏ - Elsevier
Rice is one of the world's major staple foods, especially in China. In this study, we proposed
an object-based random forest (RF) method for paddy rice map** using time series …