Towards interpreting multi-temporal deep learning models in crop mapping

DeepCropNet: a deep spatial-temporal learning framework for county-level corn yield estimation

(2020) Tao Lin et al.   Environmental Research Letters

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

Explaining the unsuitability of the kappa coefficient in the assessment and comparison of the accuracy of thematic maps obtained by image classification

(2020) Giles M. Foody   REMOTE SENSING OF ENVIRONMENT

Crop Mapping from Sentinel-1 Polarimetric Time-Series with a Deep Neural Network

(2020) Yang Qu et al.   Remote Sensing

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

An automated rice mapping method based on flooding signals in synthetic aperture radar time series

(2020) Pei Zhan et al.   REMOTE SENSING OF ENVIRONMENT

Long-short-term-memory-based crop classification using high-resolution optical images and multi-temporal SAR data

(2019) Ya’nan Zhou et al.   GIScience & Remote Sensing

Evaluation and Comparison of Random Forest and A-LSTM Networks for Large-scale Winter Wheat Identification

(2019) Tianle He et al.   Remote Sensing

A phenology-based spectral and temporal feature selection method for crop mapping from satellite time series

(2019) Qiong Hu et al.   International Journal of Applied Earth Observation and Geoinformation

Why deep-learning AIs are so easy to fool

(2019) Douglas Heaven   NATURE

Deep learning based winter wheat mapping using statistical data as ground references in Kansas and northern Texas, US

(2019) Liheng Zhong et al.   REMOTE SENSING OF ENVIRONMENT

A deep learning approach to conflating heterogeneous geospatial data for corn yield estimation: A case study of the US Corn Belt at the county level

(2019) Hao Jiang et al.   GLOBAL CHANGE BIOLOGY

A temporal group attention approach for multitemporal multisensor crop classification

(2019) Zhengtao Li et al.   INFRARED PHYSICS & TECHNOLOGY

Refined shape model fitting methods for detecting various types of phenological information on major U.S. crops

(2018) Toshihiro Sakamoto   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

Land cover mapping at very high resolution with rotation equivariant CNNs: Towards small yet accurate models

(2018) Diego Marcos et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

Urban land-use mapping using a deep convolutional neural network with high spatial resolution multispectral remote sensing imagery

(2018) Bo Huang et al.   REMOTE SENSING OF ENVIRONMENT

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

Multi-Temporal Land Cover Classification with Sequential Recurrent Encoders

(2018) Marc Rußwurm et al.   ISPRS International Journal of Geo-Information

Spatial-temporal patterns of features selected using random forests: a case study of corn and soybeans mapping in the US

(2018) Xiaoxuan Liu et al.   INTERNATIONAL JOURNAL OF REMOTE SENSING

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

Deep Recurrent Neural Network for Agricultural Classification using multitemporal SAR Sentinel-1 for Camargue, France

(2018) Emile Ndikumana et al.   Remote Sensing

Deep learning based multi-temporal crop classification

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

Deep Learning Classification of Land Cover and Crop Types Using Remote Sensing Data

(2017) Nataliia Kussul et al.   IEEE Geoscience and Remote Sensing Letters

MODIS phenology-derived, multi-year distribution of conterminous U.S. crop types

(2017) Richard Massey et al.   REMOTE SENSING OF ENVIRONMENT

PhenoRice: A method for automatic extraction of spatio-temporal information on rice crops using satellite data time series

(2017) Mirco Boschetti et al.   REMOTE SENSING OF ENVIRONMENT

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

Automated mapping of soybean and corn using phenology

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

Random forest in remote sensing: A review of applications and future directions

(2016) Mariana Belgiu 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

Assessing the robustness of Random Forests to map land cover with high resolution satellite image time series over large areas

(2016) Charlotte Pelletier et al.   REMOTE SENSING OF ENVIRONMENT

Rapid corn and soybean mapping in US Corn Belt and neighboring areas

(2016) Liheng Zhong et al.   Scientific Reports

A support vector machine to identify irrigated crop types using time-series Landsat NDVI data

(2015) Baojuan Zheng et al.   International Journal of Applied Earth Observation and Geoinformation

Deep learning

(2015) Yann LeCun et al.   NATURE

Land surface phenology along urban to rural gradients in the U.S. Great Plains

(2015) J.J. Walker et al.   REMOTE SENSING OF ENVIRONMENT

Mapping rice paddy extent and intensification in the Vietnamese Mekong River Delta with dense time stacks of Landsat data

(2015) Caitlin Kontgis et al.   REMOTE SENSING OF ENVIRONMENT

Assessment of an Operational System for Crop Type Map Production Using High Temporal and Spatial Resolution Satellite Optical Imagery

(2015) Jordi Inglada et al.   Remote Sensing

Characterizing changes in cropping patterns using sequential Landsat imagery: an adaptive threshold approach and application to Phoenix, Arizona

(2014) Chao Fan et al.   INTERNATIONAL JOURNAL OF REMOTE SENSING

Good practices for estimating area and assessing accuracy of land change

(2014) Pontus Olofsson et al.   REMOTE SENSING OF ENVIRONMENT

Temperatures and the growth and development of maize and rice: a review

(2013) Berta Sánchez et al.   GLOBAL CHANGE BIOLOGY

Impact of feature selection on the accuracy and spatial uncertainty of per-field crop classification using Support Vector Machines

(2013) F. Löw et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

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

Early-season crop area estimates for winter crops in NE Australia using MODIS satellite imagery

(2010) A.B. Potgieter et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

Estimating crop water stress with ETM+ NIR and SWIR data

(2008) Abduwasit Ghulam et al.   AGRICULTURAL AND FOREST METEOROLOGY