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14 December 2015 A simplified approach of drought risk assessment in Poyang Lake basin using real-time precipitation and multi-source remote sensing data
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Proceedings Volume 9815, MIPPR 2015: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications; 98151X (2015) https://doi.org/10.1117/12.2205991
Event: Ninth International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2015), 2015, Enshi, China
Abstract
Drought risk assessment is critical to drought early-warning and drought relief decision making. Drought risk assessment is defined as the assessment on both probability and degree of damage caused by drought. This study presents a methodology for risk analysis and assessment of drought disaster t in the Poyang Lake Basin, China based on Geographical Information Systems (GIS).The main objectives of the present study are to: (1) Study the relationships among the precipitation, the water area and NDVI. (2) Assess the degree of drought disaster risk in the Poyang Lake Basin by using a method of quantitative risk analysis. The methodology employed in this study can be applied to the drought of the other area.The study introduced a new simplified approach of drought risk assessment using real-time precipitation and multi-source remote sensing data. The following conclusions are presented on the basis of study.(1)The regression shows a high level of correlation among the precipitation, drought and water area. (2)Short-time series of water area play an important role in determining if there is a drought or not or what is the degree of the drought. Further investigations are required in order to improve the precision. This can be reached by investing the relationship between the precipitation and the vegetation cover.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Haixia He "A simplified approach of drought risk assessment in Poyang Lake basin using real-time precipitation and multi-source remote sensing data", Proc. SPIE 9815, MIPPR 2015: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 98151X (14 December 2015); https://doi.org/10.1117/12.2205991
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