Mapping the spatiotemporal patterns of tillage practices across Chinese croplands with Google Earth Engine
文献类型：期刊论文
| 作者 | Wang, Yicheng; Tao, Fulu1; Chen, Yi; Yin, Lichang |
| 刊名 | COMPUTERS AND ELECTRONICS IN AGRICULTURE
 |
| 出版日期 | 2024 |
| 卷号 | 216页码:11 |
| ISSN号 | 0168-1699 |
| 关键词 | Agricultural management Crop mapping Conservation agriculture Croplands Tillage |
| DOI | 10.1016/j.compag.2023.108509 |
| 通讯作者 | Tao, Fulu(taofl@igsnrr.ac.cn) |
| 英文摘要 | Context: Tillage practices have major impacts on soil properties, grain yield, soil carbon sequestration, and greenhouse gas emissions. Conservation tillage is an agriculture practice aiming to minimize soil disturbance and protect soil structure. It is reported that more and more croplands are being converted from conventional tillage to conservation tillage in China. However, the information is lacking as to where and when conservation tillage practice is implemented at a regional and national scale.Objective: The objectives of this study are 1) to develop a new framework for classifying tillage practices with a random forest model and Google Earth Engine platform to overcome the limitations in mapping tillage practices across China; and 2) to map the spatiotemporal patterns of tillage practices across Chinese croplands from 2016 to 2020.Methods: We generated a 1 km grid dataset for tillage practices across Chinese croplands during 2016-2020 based on Sentinel-2 imagery. First, we generated two ground reference sample pools about tillage practices based on literature review and high-resolution maps. Then, we produced Sentinel-2 features during the tillage period by composting 18 bands related to the ratios of returned crop residues. Next, we trained an optimal random forest (RF) classifier by conducting a cross-validation. Finally, we applied the optimal RF classifier to composited features to produce tillage maps from 2016 to 2020.Results and Conclusions: The validation with ground reference samples shows that the classification results have an overall accuracy of 0.80. Comparisons at a provincial scale show the estimated proportion of conservation tillage is significantly correlated with statistic data with R2 being 0.88. Results show that conservation tillage practice is adopted in about 36% of Chinese croplands, mainly distributed in northeast China, northwest China, and the North China Plain. The proportion of conservation tillage ranged from 29% to 40% during 2016-2020 although with a large spatial heterogeneity.Significance: This study develops a sound framework to map tillage practices and provides more details about the spatiotemporal patterns of tillage practices, supporting regional planning of agricultural management and climate change mitigation. |
| WOS关键词 | CROP RESIDUE COVER ; NO-TILLAGE ; AREA ; INTENSITY ; EMISSIONS ; LANDSAT ; DATASET ; REGIME ; YIELD ; INDEX |
| 资助项目 | National Natural Science Foundation |
| WOS研究方向 | Agriculture ; Computer Science |
| 语种 | 英语 |
| 出版者 | ELSEVIER SCI LTD |
| WOS记录号 | WOS:001141503900001 |
| 资助机构 | National Natural Science Foundation |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/202471]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Tao, Fulu |
| 作者单位 | 1.Chinese Acad Sci, Key Lab Land Surface Pattern & Simulat, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China 2.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wang, Yicheng,Tao, Fulu,Chen, Yi,et al. Mapping the spatiotemporal patterns of tillage practices across Chinese croplands with Google Earth Engine[J]. COMPUTERS AND ELECTRONICS IN AGRICULTURE,2024,216:11. |
| APA | Wang, Yicheng,Tao, Fulu,Chen, Yi,&Yin, Lichang.(2024).Mapping the spatiotemporal patterns of tillage practices across Chinese croplands with Google Earth Engine.COMPUTERS AND ELECTRONICS IN AGRICULTURE,216,11. |
| MLA | Wang, Yicheng,et al."Mapping the spatiotemporal patterns of tillage practices across Chinese croplands with Google Earth Engine".COMPUTERS AND ELECTRONICS IN AGRICULTURE 216(2024):11. |
入库方式： OAI收割
来源：地理科学与资源研究所
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