Cropland abandonment mapping at sub-pixel scales using crop phenological information and MODIS time-series images
文献类型：期刊论文
| 作者 | Zhao, Xuan; Wu, Taixia; Wang, Shudong1,2; Liu, Kai3; Yang, Jingyu |
| 刊名 | COMPUTERS AND ELECTRONICS IN AGRICULTURE
 |
| 出版日期 | 2023-05-01 |
| 卷号 | 208页码:107763 |
| 关键词 | Cropland abandonment Phenology Sub-pixel MODIS time series Change detection |
| DOI | 10.1016/j.compag.2023.107763 |
| 文献子类 | Article |
| 英文摘要 | Cropland abandonment is a common land-use change with mixed impacts on the environment and rural eco-nomic development. Prevalent small family farms and excessive land fragmentation result in cropland aban-donment processes that are often gradual and spatially dispersed. These difficulties limit the ability to apply previous remote sensing mapping methods of cropland abandonment to areas with complex underlying surfaces, where mixed pixels and spectral aliasing problems arise. To meet the demands of broad-scale and high-accuracy abandoned cropland mapping, we developed the PCRRSBS -CV model by combining the phenology-based cropland retirement remote sensing (PCRRS) model with the coefficient of variation (CV) and tilled soil frac-tion (BS). This method combines information regarding crop phenology with Moderate Resolution Imaging Spectroradiometer (MODIS) time-series images. The PCRRS model was used to estimate changes in spectral metrics parameters during the process of cropland abandonment. Additionally, the dead fuel index and normalized difference vegetation index (NDVI) were employed to estimate the BS in mixed pixels (according to crop type). We predicted that use of the BS as the weighting coefficient for the PCRRS model would reduce interference from the mixed pixel problem, while spatial heterogeneity could be reduced by dividing the research area into regional units. Use of the CV of the NDVI time series with phenological information highlights the volatility of crop growth periods and helps to eliminate disturbances associated with woodlands and grasslands. Finally, we demonstrated this method in the Loess Plateau of China and a portion of central Europe; we verified its accuracy using high-resolution images from Google Earth. Our algorithm demonstrated overall accuracy of 82.2 % and can extract cropland abandonment information as little as 20 % of a pixel. The overall root mean square error (RMSE) was controlled below 15 %. In summary, the high accuracy achieved by this method enables the monitoring of cropland abandonment dynamics on a large scale. |
| WOS关键词 | FARMLAND ABANDONMENT ; INNER-MONGOLIA ; LANDSAT ; EUROPE ; VEGETATION ; COVER ; IDENTIFICATION ; RECULTIVATION ; STEPPE ; FOREST |
| WOS研究方向 | Agriculture ; Computer Science |
| WOS记录号 | WOS:000967080600001 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/200803]  |
| 专题 | 陆地水循环及地表过程院重点实验室_外文论文 |
| 作者单位 | 1.Hohai Univ, Sch Earth Sci & Engn, Nanjing 210098, Jiangsu, Peoples R China 2.Chinese Acad Sci, Aerosp Informat Res Inst, Beijing 100094, Peoples R China 3.Nanjing Univ Informat Sci & Technol, Collaborat Innovat Ctr Forecast & Evaluat Meteorol, Nanjing, Peoples R China 4.Chinese Acad Sci, Inst Geog Sci & Nat Resources, Key Lab Water Cycle & Related Land Surface Proc, Beijing 100101, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhao, Xuan,Wu, Taixia,Wang, Shudong,et al. Cropland abandonment mapping at sub-pixel scales using crop phenological information and MODIS time-series images[J]. COMPUTERS AND ELECTRONICS IN AGRICULTURE,2023,208:107763. |
| APA | Zhao, Xuan,Wu, Taixia,Wang, Shudong,Liu, Kai,&Yang, Jingyu.(2023).Cropland abandonment mapping at sub-pixel scales using crop phenological information and MODIS time-series images.COMPUTERS AND ELECTRONICS IN AGRICULTURE,208,107763. |
| MLA | Zhao, Xuan,et al."Cropland abandonment mapping at sub-pixel scales using crop phenological information and MODIS time-series images".COMPUTERS AND ELECTRONICS IN AGRICULTURE 208(2023):107763. |
入库方式： OAI收割
来源：地理科学与资源研究所
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