A large-scale, long time-series (1984‒2020) of soybean mapping with phenological features: Heilongjiang Province as a test case

The 10-m crop type maps in Northeast China during 2017–2019

(2021) Nanshan You et al.   Scientific Data

Annual 30-m land use/land cover maps of China for 1980–2015 from the integration of AVHRR, MODIS and Landsat data using the BFAST algorithm

(2020) Yidi Xu et al.   Science China-Earth Sciences

Mapping croplands of Europe, Middle East, Russia, and Central Asia using Landsat, Random Forest, and Google Earth Engine

(2020) Aparna R. Phalke et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

Remote sensing phenological monitoring framework to characterize corn and soybean physiological growing stages

(2020) Chunyuan Diao   REMOTE SENSING OF ENVIRONMENT

Mapping twenty years of corn and soybean across the US Midwest using the Landsat archive

(2020) Sherrie Wang et al.   Scientific Data

Crop type mapping without field-level labels: Random forest transfer and unsupervised clustering techniques

(2019) Sherrie Wang et al.   REMOTE SENSING OF ENVIRONMENT

Assessing the pasturelands and livestock dynamics in Brazil, from 1985 to 2017: A novel approach based on high spatial resolution imagery and Google Earth Engine cloud computing

(2019) Leandro Parente et al.   REMOTE SENSING OF ENVIRONMENT

Robust Landsat-based crop time series modelling

(2018) D.P. Roy et al.   REMOTE SENSING OF ENVIRONMENT

High-resolution multi-temporal mapping of global urban land using Landsat images based on the Google Earth Engine Platform

(2018) Xiaoping Liu et al.   REMOTE SENSING OF ENVIRONMENT

Estimating Sub-Pixel Soybean Fraction from Time-Series MODIS Data Using an Optimized Geographically Weighted Regression Model

(2018) Qiong Hu et al.   Remote Sensing

Near real-time agriculture monitoring at national scale at parcel resolution: Performance assessment of the Sen2-Agri automated system in various cropping systems around the world

(2018) Pierre Defourny et al.   REMOTE SENSING OF ENVIRONMENT

Automated cropland mapping of continental Africa using Google Earth Engine cloud computing

(2017) Jun Xiong et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

Google Earth Engine: Planetary-scale geospatial analysis for everyone

(2017) Noel Gorelick et al.   REMOTE SENSING OF ENVIRONMENT

Characterizing spatiotemporal dynamics in phenology of urban ecosystems based on Landsat data

(2017) Xuecao Li et al.   SCIENCE OF THE TOTAL ENVIRONMENT

Automated mapping of soybean and corn using phenology

(2016) Liheng Zhong et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

Mapping paddy rice planting area in northeastern Asia with Landsat 8 images, phenology-based algorithm and Google Earth Engine

(2016) Jinwei Dong et al.   REMOTE SENSING OF ENVIRONMENT

Using a global reference sample set and a cropland map for area estimation in China

(2016) Le Yu et al.   Science China-Earth Sciences

A Hidden Markov Models Approach for Crop Classification: Linking Crop Phenology to Time Series of Multi-Sensor Remote Sensing Data

(2015) Sofia Siachalou et al.   Remote Sensing

A New Automatic Stratification Method for U.S. Agricultural Area Sampling Frame Construction Based on the Cropland Data Layer

(2014) Claire Boryan et al.   IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

Landsat-8: Science and product vision for terrestrial global change research

(2014) D.P. Roy et al.   REMOTE SENSING OF ENVIRONMENT

Improving 30 m global land-cover map FROM-GLC with time series MODIS and auxiliary data sets: a segmentation-based approach

(2013) Le Yu et al.   INTERNATIONAL JOURNAL OF REMOTE SENSING

Improved Land Cover Mapping using Random Forests Combined with Landsat Thematic Mapper Imagery and Ancillary Geographic Data

(2013) Xiaodong Na et al.   PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING

Detecting interannual variation in deciduous broadleaf forest phenology using Landsat TM/ETM+ data

(2013) Eli K. Melaas et al.   REMOTE SENSING OF ENVIRONMENT

High-Resolution Global Maps of 21st-Century Forest Cover Change

(2013) M. C. Hansen et al.   SCIENCE

A phenology-based approach to map crop types in the San Joaquin Valley, California

(2011) Liheng Zhong et al.   INTERNATIONAL JOURNAL OF REMOTE SENSING

Comparison of different vegetation indices for the remote assessment of green leaf area index of crops

(2011) Andrés Viña et al.   REMOTE SENSING OF ENVIRONMENT

Monitoring US agriculture: the US Department of Agriculture, National Agricultural Statistics Service, Cropland Data Layer Program

(2011) Claire Boryan et al.   Geocarto International

Land Surface Water Index (LSWI) response to rainfall and NDVI using the MODIS Vegetation Index product

(2010) K. Chandrasekar et al.   INTERNATIONAL JOURNAL OF REMOTE SENSING

Farming the planet: 2. Geographic distribution of crop areas, yields, physiological types, and net primary production in the year 2000

(2008) Chad Monfreda et al.   GLOBAL BIOGEOCHEMICAL CYCLES

Evaluation of Random Forest and Adaboost tree-based ensemble classification and spectral band selection for ecotope mapping using airborne hyperspectral imagery

(2008) Jonathan Cheung-Wai Chan et al.   REMOTE SENSING OF ENVIRONMENT