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Designing of the perpendicular drought index

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Environmental Geology

Abstract

In this paper, a simple, effective drought monitoring method is developed using two dimensional spectral space obtained from reflectance of near-infrared (NIR) and Red wavelengths. First, NIR–Red reflectance space is established using atmospheric and geometric corrected ETM+ data, which is manifested by a triangle shape and in which different surface targets possess certain spatial distribution rules. Second, perpendicular drought index (PDI) is developed on the basis of spatial characteristics of moisture distribution in NIR–Red space, as well as the relationships between PDI and soil moisture is examined. Validation work includes: comparison of PDI with in-situ drought index obtained from field measured data in the study area which includes bulk soil moisture content at different soil depths, field moisture capacity and wilting coefficient, etc.; and comparison of PDI with other recognized drought monitoring methods such as LST/NDVI and vegetation temperature condition index (VTCI). It is evident from the results that graph of PDI of field measured plots demonstrates very similar trends with ground truth drought data, LST/NDVI and VTCI. PDI is highly correlated with in-situ drought values calculated from 0 to 20 cm mean soil moisture with correlation coefficients of R 2 = 0.49 (r = 0.75). This paper concludes that PDI has a potential in remote estimation of drought phenomenon as a simple, effective drought monitoring index.

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Acknowledgments

The authors would like to extend their thanks to Professor Xu Xiru from the Institute of RS & GIS, Peking University for his kind suggestions and anonymous reviewers for their helpful comments. This work was supported by the Special Funds for Major State Basic Research (973) Project (Grant No.: G2000077900), the High-Tech Research and Development Program of China (Grant No.: 2001AA135110) and the New Technology Promotion Project from China Meteorological Administration (CMA)-monitoring and evaluation of meteorological disasters based on the retrieval of surface biophysical parameters with remote sensing data (Grant: CMATG2005M44).

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  1. Institute of Remote Sensing and GIS, Peking University, Beijing, 100871, China

    Abduwasit Ghulam, Qiming Qin & Zhiming Zhan

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  1. Abduwasit Ghulam
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  2. Qiming Qin
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  3. Zhiming Zhan
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Correspondence to Abduwasit Ghulam.

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Ghulam, A., Qin, Q. & Zhan, Z. Designing of the perpendicular drought index. Environ Geol 52, 1045–1052 (2007). https://doi.org/10.1007/s00254-006-0544-2

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  • DOI: https://doi.org/10.1007/s00254-006-0544-2

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