Detecting irrigation extent, frequency, and timing in a heterogeneous arid agricultural region using MODIS time series, Landsat imagery, and ancillary data
文献类型：期刊论文
| 作者 | Chen, Yaoliang1,2,3; Lu, Dengsheng2,4; Luo, Lifeng2,5; Pokhrel, Yadu6; Deb, Kalyanmoy7; Huang, Jingfeng3; Ran, Youhua8 |
| 刊名 | REMOTE SENSING OF ENVIRONMENT
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| 出版日期 | 2018 |
| 卷号 | 204页码:197-211 |
| 关键词 | Irrigation frequency Irrigation timing MODIS time-series data Greenness index Arid agricultural region |
| ISSN号 | 0034-4257 |
| DOI | 10.1016/j.rse.2017.10.030 |
| 通讯作者 | Huang, Jingfeng(hjf@zju.edu.cn) |
| 英文摘要 | Mapping irrigated area, frequency, timing, and amount is important for sustainable management of water resources in semi-arid and arid regions. Various studies exist on the mapping of irrigation using remote sensing and census statistics, but they mainly focus on the mapping of irrigation extent without taking frequency and timing into account. In this study, we proposed a new approach to extract irrigation attributes including irrigation extent, frequency and timing using multi-source data moderate resolution imaging spectroradiometer (MODIS), Landsat, and ancillary data. A time-series dataset with 30-m spatial resolution was generated by fusing 480-m time-series MODIS and Landsat imagery. We used the greenness index (the ratio of NIR and green spectral bands) to detect irrigation events during the first half of the growing season. Rainfall events were assumed as water supplement events along with irrigation events. The number of water supplement stages were then recorded cumulatively when a water supplement event was detected using a threshold-based model. To estimate the possible dates of each water supplement stage, Gaussian process regression and linear regression models were applied. The new framework was applied to the Hexi Corridor in northwestern China, an intensively irrigated region with a semi-arid climate. Results show that the overall accuracy of water supplement stage using the proposed method is 87%. Validation of the number of water supplement stages and possible dates of water supply by GRP model with a "strict" (or "loose") assessment method shows an overall accuracy of 55% (94%) and 59% (89%), respectively. The good accuracy of the additional independent validations for different years and sites demonstrates the robustness of the proposed method, suggesting the general applicability to other regions. Overall, this research demonstrates that the proposed method is promising in detecting irrigation attributes such as frequency and timing which have not been explored in previous research. |
| 收录类别 | SCI |
| WOS关键词 | REMOTE-SENSING DATA ; PADDY RICE AGRICULTURE ; USE/LAND-COVER LULC ; MULTITEMPORAL MODIS ; RIVER-BASIN ; ECONOMIC RETURNS ; WATER ALLOCATION ; FOOD SECURITY ; SURFACE-WATER ; CROP AREA |
| WOS研究方向 | Environmental Sciences & Ecology ; Remote Sensing ; Imaging Science & Photographic Technology |
| WOS类目 | Environmental Sciences ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:000418464400014 |
| 出版者 | ELSEVIER SCIENCE INC |
| URI标识 | http://www.irgrid.ac.cn/handle/1471x/2557622 |
| 专题 | 寒区旱区环境与工程研究所 |
| 通讯作者 | Huang, Jingfeng |
| 作者单位 | 1.Zhejiang Univ, Sch Publ Affairs, Dept Land Management, Hangzhou, Zhejiang, Peoples R China 2.Michigan State Univ, Ctr Global Change & Earth Observat, E Lansing, MI 48824 USA 3.Zhejiang Univ, Coll Environm & Resource Sci, Inst Appl Remote Sensing & Informat Technol, Hangzhou, Zhejiang, Peoples R China 4.Zhejiang Agr & Forestry Univ, Sch Environm & Resource Sci, Hangzhou, Zhejiang, Peoples R China 5.Michigan State Univ, Dept Geog Environm & Spatial Sci, E Lansing, MI 48824 USA 6.Michigan State Univ, Dept Civil & Environm Engn, E Lansing, MI 48824 USA 7.Michigan State Univ, Dept Elect & Comp Engn, E Lansing, MI 48824 USA 8.Chinese Acad Sci, Cold & Arid Reg Environm & Engn Res Inst, Key Lab Remote Sensing Gansu Prov, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Chen, Yaoliang,Lu, Dengsheng,Luo, Lifeng,et al. Detecting irrigation extent, frequency, and timing in a heterogeneous arid agricultural region using MODIS time series, Landsat imagery, and ancillary data[J]. REMOTE SENSING OF ENVIRONMENT,2018,204:197-211. |
| APA | Chen, Yaoliang.,Lu, Dengsheng.,Luo, Lifeng.,Pokhrel, Yadu.,Deb, Kalyanmoy.,...&Ran, Youhua.(2018).Detecting irrigation extent, frequency, and timing in a heterogeneous arid agricultural region using MODIS time series, Landsat imagery, and ancillary data.REMOTE SENSING OF ENVIRONMENT,204,197-211. |
| MLA | Chen, Yaoliang,et al."Detecting irrigation extent, frequency, and timing in a heterogeneous arid agricultural region using MODIS time series, Landsat imagery, and ancillary data".REMOTE SENSING OF ENVIRONMENT 204(2018):197-211. |
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来源：寒区旱区环境与工程研究所
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