Articles | Volume 13, issue 12
https://doi.org/10.5194/essd-13-5969-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-13-5969-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
23 Dec 2021
Data description paper |
| 23 Dec 2021
| 23 Dec 2021
NESEA-Rice10: high-resolution annual paddy rice maps for Northeast and Southeast Asia from 2017 to 2019
Jichong Han
Academy of Disaster Reduction and Emergency Management Ministry of
Emergency Management & Ministry of Education, School of National Safety
and Emergency Management, Beijing Normal University, Beijing 100875, China
Zhao Zhang
CORRESPONDING AUTHOR
Academy of Disaster Reduction and Emergency Management Ministry of
Emergency Management & Ministry of Education, School of National Safety
and Emergency Management, Beijing Normal University, Beijing 100875, China
Yuchuan Luo
Academy of Disaster Reduction and Emergency Management Ministry of
Emergency Management & Ministry of Education, School of National Safety
and Emergency Management, Beijing Normal University, Beijing 100875, China
Juan Cao
Academy of Disaster Reduction and Emergency Management Ministry of
Emergency Management & Ministry of Education, School of National Safety
and Emergency Management, Beijing Normal University, Beijing 100875, China
Liangliang Zhang
Academy of Disaster Reduction and Emergency Management Ministry of
Emergency Management & Ministry of Education, School of National Safety
and Emergency Management, Beijing Normal University, Beijing 100875, China
Fei Cheng
Academy of Disaster Reduction and Emergency Management Ministry of
Emergency Management & Ministry of Education, School of National Safety
and Emergency Management, Beijing Normal University, Beijing 100875, China
Huimin Zhuang
Academy of Disaster Reduction and Emergency Management Ministry of
Emergency Management & Ministry of Education, School of National Safety
and Emergency Management, Beijing Normal University, Beijing 100875, China
Jing Zhang
Academy of Disaster Reduction and Emergency Management Ministry of
Emergency Management & Ministry of Education, School of National Safety
and Emergency Management, Beijing Normal University, Beijing 100875, China
Fulu Tao
Key Laboratory of Land Surface Pattern and Simulation, Institute of
Geographical Sciences and Natural Resources Research, Chinese Academy of
Sciences, Beijing 100101, China
College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
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Cited
16 citations as recorded by crossref.
- Spatial domain transfer: Cross-regional paddy rice mapping with a few samples based on Sentinel-1 and Sentinel-2 data on GEE L. Sun et al. 10.1016/j.jag.2024.103762
- Large-scale and high-resolution paddy rice intensity mapping using downscaling and phenology-based algorithms on Google Earth Engine L. Meng et al. 10.1016/j.jag.2024.103725
- Annual paddy rice planting area and cropping intensity datasets and their dynamics in the Asian monsoon region from 2000 to 2020 J. Han et al. 10.1016/j.agsy.2022.103437
- Optimizing Rice Field Mapping in the Northern Region of China: An Asynchronous Flooding Signal and Object-Based Method L. Li et al. 10.1109/JSTARS.2024.3357141
- Phenology-assisted supervised paddy rice mapping with the Landsat imagery on Google Earth Engine: Experiments in Heilongjiang Province of China from 1990 to 2020 C. Zhang et al. 10.1016/j.compag.2023.108105
- Spatiotemporal expansion and methane emissions of rice-crayfish farming systems in Jianghan Plain, China H. Wei et al. 10.1016/j.agrformet.2024.109908
- Twenty-meter annual paddy rice area map for mainland Southeast Asia using Sentinel-1 synthetic-aperture-radar data C. Sun et al. 10.5194/essd-15-1501-2023
- Development of a 10-m resolution maize and soybean map over China: Matching satellite-based crop classification with sample-based area estimation H. Li et al. 10.1016/j.rse.2023.113623
- Monitoring Cropland Abandonment in Hilly Areas with Sentinel-1 and Sentinel-2 Timeseries S. He et al. 10.3390/rs14153806
- Automated near-real-time mapping and monitoring of rice growth extent and stages in Selangor Malaysia . Fatchurrachman et al. 10.1016/j.rsase.2023.100993
- Feature-based algorithm for large-scale rice phenology detection based on satellite images X. Zhao et al. 10.1016/j.agrformet.2022.109283
- Mapping Diverse Paddy Rice Cropping Patterns in South China Using Harmonized Landsat and Sentinel-2 Data J. Hu et al. 10.3390/rs15041034
- Bi-Objective Crop Mapping from Sentinel-2 Images Based on Multiple Deep Learning Networks W. Song et al. 10.3390/rs15133417
- High-resolution distribution maps of single-season rice in China from 2017 to 2022 R. Shen et al. 10.5194/essd-15-3203-2023
- High-Resolution Mapping of Paddy Rice Extent and Growth Stages across Peninsular Malaysia Using a Fusion of Sentinel-1 and 2 Time Series Data in Google Earth Engine . Fatchurrachman et al. 10.3390/rs14081875
- NESEA-Rice10: high-resolution annual paddy rice maps for Northeast and Southeast Asia from 2017 to 2019 J. Han et al. 10.5194/essd-13-5969-2021
14 citations as recorded by crossref.
- Spatial domain transfer: Cross-regional paddy rice mapping with a few samples based on Sentinel-1 and Sentinel-2 data on GEE L. Sun et al. 10.1016/j.jag.2024.103762
- Large-scale and high-resolution paddy rice intensity mapping using downscaling and phenology-based algorithms on Google Earth Engine L. Meng et al. 10.1016/j.jag.2024.103725
- Annual paddy rice planting area and cropping intensity datasets and their dynamics in the Asian monsoon region from 2000 to 2020 J. Han et al. 10.1016/j.agsy.2022.103437
- Optimizing Rice Field Mapping in the Northern Region of China: An Asynchronous Flooding Signal and Object-Based Method L. Li et al. 10.1109/JSTARS.2024.3357141
- Phenology-assisted supervised paddy rice mapping with the Landsat imagery on Google Earth Engine: Experiments in Heilongjiang Province of China from 1990 to 2020 C. Zhang et al. 10.1016/j.compag.2023.108105
- Spatiotemporal expansion and methane emissions of rice-crayfish farming systems in Jianghan Plain, China H. Wei et al. 10.1016/j.agrformet.2024.109908
- Twenty-meter annual paddy rice area map for mainland Southeast Asia using Sentinel-1 synthetic-aperture-radar data C. Sun et al. 10.5194/essd-15-1501-2023
- Development of a 10-m resolution maize and soybean map over China: Matching satellite-based crop classification with sample-based area estimation H. Li et al. 10.1016/j.rse.2023.113623
- Monitoring Cropland Abandonment in Hilly Areas with Sentinel-1 and Sentinel-2 Timeseries S. He et al. 10.3390/rs14153806
- Automated near-real-time mapping and monitoring of rice growth extent and stages in Selangor Malaysia . Fatchurrachman et al. 10.1016/j.rsase.2023.100993
- Feature-based algorithm for large-scale rice phenology detection based on satellite images X. Zhao et al. 10.1016/j.agrformet.2022.109283
- Mapping Diverse Paddy Rice Cropping Patterns in South China Using Harmonized Landsat and Sentinel-2 Data J. Hu et al. 10.3390/rs15041034
- Bi-Objective Crop Mapping from Sentinel-2 Images Based on Multiple Deep Learning Networks W. Song et al. 10.3390/rs15133417
- High-resolution distribution maps of single-season rice in China from 2017 to 2022 R. Shen et al. 10.5194/essd-15-3203-2023
2 citations as recorded by crossref.
- High-Resolution Mapping of Paddy Rice Extent and Growth Stages across Peninsular Malaysia Using a Fusion of Sentinel-1 and 2 Time Series Data in Google Earth Engine . Fatchurrachman et al. 10.3390/rs14081875
- NESEA-Rice10: high-resolution annual paddy rice maps for Northeast and Southeast Asia from 2017 to 2019 J. Han et al. 10.5194/essd-13-5969-2021
Latest update: 18 Apr 2024
Short summary
The accurate planting area and spatial distribution information is the basis for ensuring food security at continental scales. We constructed a paddy rice map database in Southeast and Northeast Asia for 3 years (2017–2019) at a 10 m spatial resolution. There are fewer mixed pixels in our paddy rice map. The large-scale and high-resolution maps of paddy rice are useful for water resource management and yield monitoring.
The accurate planting area and spatial distribution information is the basis for ensuring food...
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