Tracking the impact of typhoons on maize growth and recovery using Sentinel-1 and Sentinel-2 data: A case study of Northeast China
文献类型：期刊论文
| 作者 | Mu, Yongling1; Chen, Shengbo1; Cao, Yijing1,3; Zhu, Bingxue1,2; Li, Anzhen1; Cui, Liang1; Dai, Rui1; Zeng, Qinghong1 |
| 刊名 | AGRICULTURAL AND FOREST METEOROLOGY
 |
| 出版日期 | 2024-12-15 |
| 卷号 | 359页码:20 |
| 关键词 | Typhoon disaster Crop damage Sentinel-1 Sentinel-2 Damage severity Maize recovery Remote sensing |
| ISSN号 | 0168-1923 |
| DOI | 10.1016/j.agrformet.2024.110266 |
| 产权排序 | 2 |
| 英文摘要 | The increasing frequency of typhoon events, attributed to global climate change, has significantly affected agricultural production, predominantly resulting in substantial negative consequences. Accurate and timely assessment of crop damage is crucial for understanding economic implications, devising effective agricultural strategies, and enhancing resilience amid mounting climate uncertainties. This study investigates the utility of Sentinel-1 Synthetic Aperture Radar (SAR) and Sentinel-2 MultiSpectral Instrument (MSI) data in tracking maize damage severity following typhoon events. By employing continuous field sampling techniques and conducting visual interpretation of high-resolution remote sensing imagery, sample sets representing a spectrum of maize damage severity were systematically established. The application of time series analysis on Sentinel data enables a comprehensive exploration of spectral and polarization responses, providing insights into the correlation with maize damage severity. Segmentation of the maize damage timeline into pre-disaster, disaster, and recovery periods, coupled with optimization of relevant feature parameters, was undertaken to bolster monitoring precision. Leveraging the Google Earth Engine (GEE) cloud platform, a Random Forest algorithm was used to develop a model for monitoring maize damage severity across different post-typhoon periods, yielding maps delineating the distribution and magnitude of maize damage in Northeast China. Results indicate that integrating spectral indices from the pre-disaster phase with backscatter variations of polarization bands during various posttyphoon periods enhances maize damage assessment. Maize damage severity is notably elevated during the disaster period, achieving an overall accuracy of 87.22 %. While mitigated during the recovery phase, localized exacerbation occurs in severely affected regions, yielding an overall accuracy of 88.54 %. Analysis incorporating terrain and meteorological data reveals that post-typhoon maize disasters predominantly occur in low-lying and flat areas, with meteorological factors, particularly maximum wind speed and daily cumulative precipitation, exerting significant influence on damage severity. This study underscores the critical role of SAR and optical data fusion in elucidating typhoon-induced crop damage dynamics, thereby providing essential insights for proactive mitigation strategies against future agricultural losses. |
| WOS关键词 | RADARSAT-2 ; MOISTURE ; INDEXES ; CROPS |
| 资助项目 | National Key Research and Development Program of China[2020YFA0714103] ; Jilin Province Science and Technology Devel-opment Plan[20210201138GX] |
| WOS研究方向 | Agriculture ; Forestry ; Meteorology & Atmospheric Sciences |
| 语种 | 英语 |
| WOS记录号 | WOS:001338745700001 |
| 出版者 | ELSEVIER |
| 资助机构 | National Key Research and Development Program of China ; Jilin Province Science and Technology Devel-opment Plan |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/209690]  |
| 专题 | 陆地水循环及地表过程院重点实验室_外文论文 |
| 通讯作者 | Chen, Shengbo |
| 作者单位 | 1.Jilin Univ, Coll Geoexplorat Sci & Technol, Changchun 130026, Peoples R China 2.Chinese Acad Sci, Northeast Inst Geog & Agroecol, Changchun 130102, Peoples R China 3.Chinese Acad Sci, Key Lab Water Cycle & Related Land Surface Proc, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China |
| 推荐引用方式 GB/T 7714 | Mu, Yongling,Chen, Shengbo,Cao, Yijing,et al. Tracking the impact of typhoons on maize growth and recovery using Sentinel-1 and Sentinel-2 data: A case study of Northeast China[J]. AGRICULTURAL AND FOREST METEOROLOGY,2024,359:20. |
| APA | Mu, Yongling.,Chen, Shengbo.,Cao, Yijing.,Zhu, Bingxue.,Li, Anzhen.,...&Zeng, Qinghong.(2024).Tracking the impact of typhoons on maize growth and recovery using Sentinel-1 and Sentinel-2 data: A case study of Northeast China.AGRICULTURAL AND FOREST METEOROLOGY,359,20. |
| MLA | Mu, Yongling,et al."Tracking the impact of typhoons on maize growth and recovery using Sentinel-1 and Sentinel-2 data: A case study of Northeast China".AGRICULTURAL AND FOREST METEOROLOGY 359(2024):20. |
入库方式： OAI收割
来源：地理科学与资源研究所
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