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Mapping Paddy Rice Fields by Combining Multi-Temporal Vegetation Index and Synthetic Aperture Radar Remote Sensing Data Using Google Earth Engine Machine Learning Platform

机译：采用谷歌地球发动机机床学习平台组合多时间植被指数和合成孔径雷达遥感数据映射水稻田

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Nengcheng Chen; Lixiaona Yu; Xiang Zhang; Yonglin Shen; Linglin Zeng; Qiong Hu; Dev Niyogi;
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1. Mapping paddy rice fields by applying machine learning algorithms to multi-temporal Sentinel-1A and Landsat data [J] . Onojeghuo Alex O., Blackburn George A., Wang Qunming, International journal of remote sensing . 2018,第3a4期

机译：通过将机器学习算法应用于多时相Sentinel-1A和Landsat数据来绘制水稻田
2. REMOTELY SENSED INDICATORS OF HABITAT HETEROGENEITY - USE OF SYNTHETIC APERTURE RADAR IN MAPPING VEGETATION STRUCTURE AND BIRD HABITAT [J] . Imhoff ML., Milne A., Morgan G., Remote Sensing of Environment: An Interdisciplinary Journal . 1997,第3期

机译：栖息地非均质性的遥感指标-综合孔径雷达在映射植被结构和鸟类栖息地中的应用。
3. Exploring Google Earth Engine Platform for Big Data Processing: Classification of Multi-Temporal Satellite Imagery for Crop Mapping [J] . Shelestov Andrii, Lavreniuk Mykola, Kussul Nataliia, Frontiers in Digital Humanities . 2017,第4期

机译：探索Google Earth Engine平台进行大数据处理：用于作物制图的多时相卫星图像分类
4. An Effective Use of Synthetic Aperture Radar Imaging Technique Over Optical Remote Sensing and Real Aperture Radar for Mapping of Earth Surface Features [C] . Gourab Adhikari, Sourav Halder, Sripatna Banerjee, Conference on Innovations in Energy Management and Renewable Resources . 2021

机译：用于在光学遥感和实际孔径雷达上进行合成孔径雷达成像技术的有效利用，用于地球表面特征的映射
5. Relationships between tropical forest structure and remotely sensed synthetic aperture radar data. [D] . Valeriano, Dalton de Morisson. 1996

机译：热带森林结构与遥感合成孔径雷达数据之间的关系。
6. Mapping paddy rice planting area in northeastern Asia with Landsat 8 images phenology-based algorithm and Google Earth Engine [O] . Jinwei Dong, Xiangming Xiao, Michael A. Menarguez, -1

机译：使用Landsat 8影像基于物候学的算法和Google Earth Engine绘制东北亚水稻种植区的图
7. Development of a global 30-m impervious surface map using multi-source and multi-temporal remote sensing datasets with the Google Earth Engine platform [O] . Xiao Zhang, Liangyun Liu, Changshan Wu, 2020

机译：使用Google地球发动机平台的多源和多时间遥感数据集开发全球30米不透水表面图

Mapping Paddy Rice Fields by Combining Multi-Temporal Vegetation Index and Synthetic Aperture Radar Remote Sensing Data Using Google Earth Engine Machine Learning Platform

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