| Remote Sensing | |
| Monitoring Spatio-Temporal Distribution of Rice Planting Area in the Yangtze River Delta Region Using MODIS Images | |
| Jingjing Shi2  Jingfeng Huang2  Tao Cheng1  Yoshio Inoue1  | |
| [1] id="af1-remotesensing-07-08883">Institute of Agricultural Remote Sensing & Information Application, Zhejiang University, Hangzhou 310058, Chi;Institute of Agricultural Remote Sensing & Information Application, Zhejiang University, Hangzhou 310058, China | |
| 关键词: rice; MODIS; Yangtze River Delta region; Normalized Weighted Difference Water Index; Enhanced Vegetation Index; | |
| DOI : 10.3390/rs70708883 | |
| 来源: mdpi | |
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【 摘 要 】
A large-area map of the spatial distribution of rice is important for grain yield estimations, water management and an understanding of the biogeochemical cycling of carbon and nitrogen. In this paper, we developed the Normalized Weighted Difference Water Index (NWDWI) for identifying the unique characteristics of rice during the flooding and transplanting period. With the aid of the ASTER Global Digital Elevation Model and the phenological data observed at agrometeorological stations, the spatial distributions of single cropping rice and double cropping early and late rice in the Yangtze River Delta region were generated using the NWDWI and time-series Enhanced Vegetation Index data derived from MODIS/Terra data during the 2000–2010 period. The accuracy of the MODIS-derived rice planting area was validated against agricultural census data at the county level. The spatial accuracy was also tested based on a land use map and Landsat ETM+ data. The decision coefficients for county-level early and late rice were 0.560 and 0.619, respectively. The MODIS-derived area of late rice exhibited higher consistency with the census data during the 2000–2010 period. The algorithm could detect and monitor rice fields with different cropping patterns at the same site and is useful for generating spatial datasets of rice on a regional scale.
【 授权许可】
CC BY
© 2015 by the authors; licensee MDPI, Basel, Switzerland.
【 预 览 】
| Files | Size | Format | View |
|---|---|---|---|
| RO202003190009870ZK.pdf | 17109KB |
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