Transferable deep learning model based on the phenological matching principle for mapping crop extent

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

(2021) Nanshan You et al.   Scientific Data

Large-scale crop type and crop area mapping across Brazil using synthetic aperture radar and optical imagery

(2021) Olaniyi A. Ajadi et al.   International Journal of Applied Earth Observation and Geoinformation

Large-scale rice mapping under different years based on time-series Sentinel-1 images using deep semantic segmentation model

(2021) Pengliang Wei et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

Crop type mapping by using transfer learning

(2021) Artur Nowakowski et al.   International Journal of Applied Earth Observation and Geoinformation

Two shifts for crop mapping: Leveraging aggregate crop statistics to improve satellite-based maps in new regions

(2021) Dan M. Kluger et al.   REMOTE SENSING OF ENVIRONMENT

Examining earliest identifiable timing of crops using all available Sentinel 1/2 imagery and Google Earth Engine

(2020) Nanshan You et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

Detecting flowering phenology in oil seed rape parcels with Sentinel-1 and -2 time series

(2020) Raphaël d’Andrimont et al.   REMOTE SENSING OF ENVIRONMENT

ResUNet-a: A deep learning framework for semantic segmentation of remotely sensed data

(2020) Foivos I. Diakogiannis et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

Deep Learning Segmentation and Classification for Urban Village Using a Worldview Satellite Image Based on U-Net

(2020) Zhuokun Pan et al.   Remote Sensing

Exploring multiscale object-based convolutional neural network (multi-OCNN) for remote sensing image classification at high spatial resolution

(2020) Vitor S. Martins et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

A generalized approach based on convolutional neural networks for large area cropland mapping at very high resolution

(2020) Dujuan Zhang et al.   REMOTE SENSING OF ENVIRONMENT

DeepCropMapping: A multi-temporal deep learning approach with improved spatial generalizability for dynamic corn and soybean mapping

(2020) Jinfan Xu et al.   REMOTE SENSING OF ENVIRONMENT

Transfer Learning for Crop classification with Cropland Data Layer data (CDL) as training samples

(2020) Pengyu Hao et al.   SCIENCE OF THE TOTAL ENVIRONMENT

Simulating Soybean–Rice Rotation and Irrigation Strategies in Arkansas, USA Using APEX

(2020) Sam R. Carroll et al.   Sustainability

From local to global: A transfer learning-based approach for mapping poplar plantations at national scale using Sentinel-2

(2020) Yousra Hamrouni et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

WHU-Hi: UAV-borne hyperspectral with high spatial resolution (H2) benchmark datasets and classifier for precise crop identification based on deep convolutional neural network with CRF

(2020) Yanfei Zhong et al.   REMOTE SENSING OF ENVIRONMENT

Mapping crops within the growing season across the United States

(2020) Venkata Shashank Konduri et al.   REMOTE SENSING OF ENVIRONMENT

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

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

Deep learning based cloud detection for medium and high resolution remote sensing images of different sensors

(2019) Zhiwei Li et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

Environmental fate and impact assessment of thiobencarb application in California rice fields using RICEWQ

(2019) Ruoyu Wang et al.   SCIENCE OF THE TOTAL ENVIRONMENT

Smallholder maize area and yield mapping at national scales with Google Earth Engine

(2019) Zhenong Jin et al.   REMOTE SENSING OF ENVIRONMENT

Multi-sensor cloud and cloud shadow segmentation with a convolutional neural network

(2019) Marc Wieland et al.   REMOTE SENSING OF ENVIRONMENT

Crop Mapping Based on Historical Samples and New Training Samples Generation in Heilongjiang Province, China

(2019) Lin Zhang et al.   Sustainability

Machine-learned prediction of annual crop planting in the U.S. Corn Belt based on historical crop planting maps

(2019) Chen Zhang et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Using the Landsat archive to map crop cover history across the United States

(2019) David M. Johnson   REMOTE SENSING OF ENVIRONMENT

MultiResUNet : Rethinking the U-Net architecture for multimodal biomedical image segmentation

(2019) Nabil Ibtehaz et al.   NEURAL NETWORKS

Cloud detection algorithm for multi-modal satellite imagery using convolutional neural-networks (CNN)

(2019) Michal Segal-Rozenhaimer et al.   REMOTE SENSING OF ENVIRONMENT

The critical period for yield and quality determination in canola ( Brassica napus L.)

(2018) John A. Kirkegaard et al.   FIELD CROPS RESEARCH

A light and faster regional convolutional neural network for object detection in optical remote sensing images

(2018) Peng Ding et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

A high-performance and in-season classification system of field-level crop types using time-series Landsat data and a machine learning approach

(2018) Yaping Cai et al.   REMOTE SENSING OF ENVIRONMENT

A 30-m landsat-derived cropland extent product of Australia and China using random forest machine learning algorithm on Google Earth Engine cloud computing platform

(2018) Pardhasaradhi Teluguntla et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

Early-season crop mapping using improved artificial immune network (IAIN) and Sentinel data

(2018) Pengyu Hao et al.   PeerJ

Deep learning based multi-temporal crop classification

(2018) Liheng Zhong et al.   REMOTE SENSING OF ENVIRONMENT

Satellite detection of rising maize yield heterogeneity in the U.S. Midwest

(2017) David B Lobell et al.   Environmental Research Letters

Landsat-based classification in the cloud: An opportunity for a paradigm shift in land cover monitoring

(2017) G. Azzari et al.   REMOTE SENSING OF ENVIRONMENT

National-scale soybean mapping and area estimation in the United States using medium resolution satellite imagery and field survey

(2017) Xiao-Peng Song et al.   REMOTE SENSING OF ENVIRONMENT

Google Earth Engine: Planetary-scale geospatial analysis for everyone

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

Deep Learning in Remote Sensing: A Comprehensive Review and List of Resources

(2017) Xiao Xiang Zhu et al.   IEEE Geoscience and Remote Sensing Magazine

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

Deep learning

(2015) Yann LeCun et al.   NATURE

Tracking the dynamics of paddy rice planting area in 1986–2010 through time series Landsat images and phenology-based algorithms

(2015) Jinwei Dong et al.   REMOTE SENSING OF ENVIRONMENT

Life cycle greenhouse gas emissions in California rice production

(2014) Sonja Brodt et al.   FIELD CROPS RESEARCH

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

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

Efficient corn and soybean mapping with temporal extendability: A multi-year experiment using Landsat imagery

(2013) Liheng Zhong 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