Abstract
In this article, the performance of the Visible and Shortwave infrared Drought Index (VSDI), a drought index recently developed and validated in Oklahoma, United States, is further explored and validated in China. The in-situ measured soil moisture from 585 weather stations across China are used as ground-truth data, and five commonly used drought indices are compared with VSDI for surface drought monitoring. The results reveal that VSDI is robust and reliable in the estimation of surface dryness-it has the highest correlation with soil moisture among the six indices when computed using both the original and cloud removed data. All six indices show the highest correlation with soil moisture at the 10 cm layer and the averaged 10–50 cm layer. The spatiotemporal patterns of surface moisture indicated by the MODIS-based VSDI are further compared with the precipitation-based drought maps and the Global Land Data Assimilation System (GLDAS) simulated surface soil moisture maps over five provinces located in the Middle-Lower Yangtze Plain of China. The results indicate that despite the difference between the spatial and temporal resolutions of the three products, the VSDI maps still show good agreement with the other two drought products through the rapidly alternating drought and flood events in 2011 in this region. Therefore, VSDI can be used as an effective surface wetness indicator at both the provincial and the national scales in China.
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Brown, J. F., B. D. Wardlow, T. Tadesse, M. J. Hayes, and B. C. Reed. 2008. The Vegetation Drought Response Index (VegDRI): A New Integrated Approach for Monitoring Drought Stress in Vegetation. GIScience and Remote Sensing 45(1): 16–46.
Bryant, E. A. 1991. Natural Hazards. Cambridge, UK: Cambridge University Press.
Ceccato, P., S. Flasse, S. Tarantola, S. Jacquemoud, and J. Gregoire. 2001. Detecting Vegetation Leaf Water Content Using Reflectance in the Optical Domain. Remote Sensing of Environment 77(1): 22–33.
Chen, D., J. Huang, and T. J. Jackson. 2005. Vegetation Water Content Estimation for Corn and Soybeans Using Spectral Indices Derived from MODIS Near- and Short-Wave Infrared Bands. Remote Sensing of Environment 98(2–3): 225–236.
China Meteorological Administration. 2006. Chinese Classification of Meteorological Drought. GB/T 20481-2006. http://www.tsinfo.js.cn/inquiry/gbtdetails.aspx?A100=GB/T%2020481-2006.
Chuvieco, E., D. Riãno, I. Aguado, and D. Cocero. 2002. Estimation of Fuel Moisture Content from Multitemporal Analysis of Landsat Thematic Mapper Reflectance Data: Applications in Fire Danger Assessment. International Journal of Remote Sensing 23(11): 2145–2162.
Dawson, T. P., P. J. Curran, P. R. J. North, and S. E. Plummer. 1999. The Propagation of Foliar Biochemical Absorption Features in Forest Canopy Reflectance: A Theoretical Analysis. Remote Sensing of Environment 67(2): 147–159.
Deering, D. W. 1978. Rangeland Reflectance Characteristics Measured by Aircraft and Spacecraft Sensors. Ph.D. Dissertation, Texas A & M University, College Station, TX.
Du, X., S. Wang, Y. Zhou, and H. Wei. 2007. Construction and Validation of a New Model for Unified Surface Water Capacity Based on MODIS Data. Geomatics and Information Science of Wuhan University 32(3): 205–207 (in Chinese).
Fensholt, R., and I. Sandholt. 2003. Derivation of a Shortwave Infrared Stress Index from MODIS Near- and Shortwave Infrared Data in a Semiarid Environment. Remote Sensing of Environment 87(1): 111–121.
Gao, B. C. 1996. NDWI-A Normalized Difference Water Index for Remote Sensing of Vegetation Liquid Water from Space. Remote Sensing of Environment 58(3): 257–266.
Ghulam, A., Z. L. Li, Q. M. Qin, H. Yimit, and J. H. Wang. 2008. Estimating Crop Water Stress with ETM+NIR and SWIR Data. Agricultural and Forest Meteorology 148(11): 1679–1695.
Gu, Y., J. F. Brown, J. P. Verdin, and B. Wardlow. 2007. A Five-Year Analysis of MODIS NDVI and NDWI for Grassland Drought Assessment Over the Central Great Plains of the United States. Geophysical Research Letters 34(6): L06407.
Gu, Y., E. Hunt, B. Wardlow, J. B. Basara, J. F. Brown, and J. P. Verdin. 2008. Evaluation of MODIS NDVI and NDWI for Vegetation Drought Monitoring Using Oklahoma Mesonet Soil Moisture Data. Geophysical Research Letters 35(5): L22401.
Hardinsky, M. A., V. Lemas, and R. M. Smart. 1983. The Influence of Soil Salinity, Growth Form, and Leaf Moisture on the Spectral Reflectance of Spartina Alternifolia Canopies. Photogrammetric Engineering and Remote Sensing 49(1): 77–83.
Hunt, Jr. E. R., and B. N. Rock. 1989. Detection of Changes in Leaf Water Content Using Near- and Middle-Infrared Reflectance. Remote Sensing of Environment 30(1): 43–54.
Jackson, T. J., D. Chen, M. Cosh, F. Li, M. Anderson, C. Walthall, P. Doriaswamy, and E. R. Hunt. 2004. Vegetation Water Content Mapping Using Landsat Data Derived Normalized Difference Water Index for Corn and Soybeans. Remote Sensing of Environment 92(4): 475–482.
Ji, L., and A. J. Peters. 2003. Assessing Vegetation Response to Drought in the Northern Great Plains Using Vegetation and Drought Indices. Remote Sensing of Environment 87(1): 85–98.
Jimmy, O. A., and M. C. Andrew. 2002. Relations between Soil Moisture and Satellite Vegetation Indices in the U.S. Corn Belt. Journal of Hydrometeorology 3(4): 395–405.
Maki, M., M. Ishiahra, and M. Tamura. 2004. Estimation of Leaf Water Status to Monitor the Risk of Forest Fires by Using Remotely Sensed Imagery. Remote Sensing of Environment 90(4): 441–450.
McVicar, T. R., and P. N. Bierwirth. 2001. Rapidly Assessing the 1997 Drought in Papua New Guinea Using Composite AVHRR Imagery. International Journal of Remote Sensing 22(11): 2109–2128.
Mishra, A. K., and V. P. Singh. 2010. A Review of Drought Concepts. Journal of Hydrology 391(1–2): 202–216.
Oliver, M. A. 1990. Kriging: A Method of Interpolation for Geographical Information Systems. International Journal of Geographic Information Systems 4(3): 313–332.
Riebsame, W. E., S. A. Changnon, and T. R. Karl. 1991. Drought and Natural Resource Management in the United States: Impacts and Implications of the 1987–1989 Drought. Boulder, CO: Westview Press.
Steel, R. G. D., and J. H. Torrie. 1960. Principles and Procedures of Statistics. New York: McGraw-Hill.
Tannehill, I. R. 1947. Drought: Its Causes and Effects. Princeton, NJ: Princeton University Press.
Wan, Z., P. Wang, and X. Li. 2004. Using MODIS Land Surface Temperature and Normalized Difference Vegetation Index for Monitoring Drought in the Southern Great Plains, USA. International Journal of Remote Sensing 25(1): 61–72.
Wang, L., and J. J. Qu. 2009. Satellite Remote Sensing Applications for Surface Soil Moisture Monitoring: A Review. Frontiers of Earth Science in China 3(2): 237–247.
Wang, X., H. Xie, H. Guan, and X. Zhou. 2007. Different Responses of MODIS-Derived NDVI to Root-Zone Soil Moisture in Semi-Arid and Humid Regions. Journal of Hydrology 340(1–2): 12–24.
Wilhite, D. A. 2000. Drought as a Natural Hazard: Concepts and Definitions. In Drought: A Global Assessment, Vol. I, edited by D. A. Wilhite, 3–18. New York: Routledge.
Xiao, X., S. Boles, J. Liu, D. Zhuang, S. Frolking, C. Li, W. Salas, and B. Moore III. 2005. Mapping Paddy Rice Agriculture in Southern China Using Multi-Temporal MODIS Images. Remote Sensing of Environment 95(4): 480–492.
Xiao, X., Q. Zhang, B. Braswell, S. Urbanski, S. Boles, S. Wofsy, B. Moore, III, and D. Ojima. 2004. Modeling Gross Primary Production of Temperate Deciduous Broadleaf Forest Using Satellite Images and Climate Data. Remote Sensing of Environment 91(2): 256–270.
Yao, Y., Q. Qin, S. Zhao, and W. Yuan. 2011. Retrieval of Soil Moisture Based on MODIS Shortwave Infrared Spectral Feature. Journal of Infrared and Millimeter Waves 30(1): 61–67.
Yilmaz, M. T., E. R. Hunt Jr., and T. J. Jackson. 2008. Remote Sensing of Vegetation Water Content from Equivalent Water Thickness Using Satellite Imagery. Remote Sensing of Environment 112(5): 2514–2522.
Zarco-Tejada, P. J., C. A. Rueda, and S. L. Ustin. 2003. Water Content Estimation in Vegetation with MODIS Reflectance Data and Model Inversion Methods. Remote Sensing of Environment 85(1): 109–124.
Zhang, H., H. Chen, S. Shen, G. Zhou, and W. Yu. 2008. Drought Remote Sensing Monitoring Based on the Surface Water Content Index (SWCI) Method. Remote Sensing Technology and Application 23(6): 624–628 (in Chinese).
Zhang, N., Y. Hong, Q. Qin, and L. Liu. 2013. VSDI: A Visible and Shortwave Infrared Drought Index for Monitoring Soil and Vegetation Moisture Based on Optical Remote Sensing. International Journal of Remote sensing 34(13): 4585–4609.
Zhang, J., Y. Xu, F. Yao, P. Wang, W. Guo, L. Li and L. Yang. 2010. Advances in Estimation Methods of Vegetation Water Content Based on Optical Remote Sensing Techniques. Science China-Technological Sciences 53(5): 1159–1167.
Zhao, S., Q. Qin, L. You, Y. Yao, N. Yang, and J. Li. 2009. Application of Two Shortwave Infrared Water Stress Indices to Drought Monitoring Over Northwestern China. Geoscience and Remote Sensing Symposium (IGARSS 2009), III-530–III-533.
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Zhang, N., Hong, Y., Qin, Q. et al. Evaluation of the visible and shortwave infrared drought index in China. Int J Disaster Risk Sci 4, 68–76 (2013). https://doi.org/10.1007/s13753-013-0008-8
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DOI: https://doi.org/10.1007/s13753-013-0008-8