The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Observation of flooding and rice transplanting of paddy rice fields at the site to landscape scales in China using VEGETATION sensor data
Abstract
A unique physical feature of paddy rice fields is that rice is grown on flooded soil. During the period of flooding and rice transplanting, there is a large proportion of surface water in a land surface consisting of water, vegetation and soils. The VEGETATION (VGT) sensor has four spectral bands that are equivalent to spectral bands of Landsat TM, and its mid-infrared spectral band is very sensitive to soil moisture and plant canopy water content. In this study we evaluated a VGT-derived normalized difference water index (NDWI VGT =(B3-MIR)/ (B3+MIR)) for describing temporal and spatial dynamics of surface moisture. Twenty-seven 10-day composites (VGT- S10) from 1 March to 30 November 1999 were acquired and analysed for a study area (175 km by 165 km) in eastern Jiangsu Province, China, where a winter wheat and paddy rice double cropping system dominates the landscape. We compared the temporal dynamics and spatial patterns of normalized difference vegetation index (NDVI VGT ) and NDWI VGT . The NDWI VGT temporal dynamics were sensitive enough to capture the substantial increases of surface water due to flooding and rice transplanting at paddy rice fields. A land use thematic map for the timing and location of flooding and rice transplanting was generated for the study area. Our results indicate that NDWI and NDVI temporal anomalies may provide a simple and effective tool for detection of flooding and rice transplanting across the landscape.
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Cites
Photogrammetric Engineering and Remote Sensing
Nicol, J., King, B., Quattrochi, D., Dowman, I. J., Ehlers, M., & Xiaoli, D. (2007) · UCL Discovery (University College London) · Cited by 9,325
NDWI—A normalized difference water index for remote sensing of vegetation liquid water from space
Gao, B.-C. (1996) · Remote Sensing of Environment · doi:10.1016/s0034-4257(96)00067-3 · Cited by 6,951
International Journal of Remote Sensing
(2012) · International Journal of Remote Sensing · doi:10.1080/01431161.2012.638042 · Cited by 1,000
Rice crop mapping and monitoring using ERS-1 data based on experiment and modeling results
Le Toan, T., Ribbes, F., Wang, L.-F., Floury, N., Ding, K.-H., Kong, J. A., Fujita, M., & Kurosu, T. (1997) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/36.551933 · Cited by 590
Methane Emission from Rice Fields
Neue, H.-U. (1993) · BioScience · doi:10.2307/1311906 · Cited by 333
Changes in CH4 emission from rice fields from 1960 to 1990s: 1. Impacts of modern rice technology
van der Gon, H. D. (2000) · Global Biogeochemical Cycles · doi:10.1029/1999gb900096 · Cited by 55
Cited by
Xiao, X., Boles, S., Liu, J., Zhuang, D., & Liu, M. (2002) · Remote Sensing of Environment · doi:10.1016/s0034-4257(02)00051-2 · Cited by 355
Self-citationFrolking, S., Qiu, J., Boles, S., Xiao, X., Liu, J., Zhuang, Y., Li, C., & Qin, X. (2002) · Global Biogeochemical Cycles · doi:10.1029/2001gb001425 · Cited by 348
Chandrasekar, K., Sesha Sai, M. V. R., Roy, P. S., & Dwevedi, R. S. (2010) · International Journal of Remote Sensing · doi:10.1080/01431160802575653 · Cited by 347
Open Surface Water Mapping Algorithms: A Comparison of Water-Related Spectral Indices and Sensors
Zhou, Y., Dong, J., Xiao, X., Xiao, T., Yang, Z., Zhao, G., Zou, Z., & Qin, Y. (2017) · Water · doi:10.3390/w9040256 · Cited by 265
Self-citationLe Page, Y., Oom, D., Silva, J. M. N., Jönsson, P., & Pereira, J. M. C. (2010) · Global Ecology and Biogeography · doi:10.1111/j.1466-8238.2010.00525.x · Cited by 177
Metadata
- Authors
- Xiao, X., Boles, S., Frolking, S., Salas, W., Moore, B., Li, C., He, L., & Zhao, R.
- Venue
- International Journal of Remote Sensing
- Publisher
- Informa UK Limited
- Published
- 2002-01
- Volume
- 23
- Issue
- 15
- Pages
- 3009-3022
- ISSN
- 0143-1161 (ISSN-L)
- 1366-5901
- OpenAlex
- W2115525646
- Cited by
- 386
- References
- 6
- FWCI
- 3.83
- Type
- journal article
- Language
- en
- Open access
- closed
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- Xiao, X., Boles, S., Frolking, S., Salas, W., Moore, B., Li, C., He, L., & Zhao, R. (2002). Observation of flooding and rice transplanting of paddy rice fields at the site to landscape scales in China using VEGETATION sensor data. International Journal of Remote Sensing. https://doi.org/10.1080/01431160110107734
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