Modified perpendicular drought index (MPDI): a real-time drought monitoring method

Soil moisture and vegetation growth are the most direct and important indicators of drought events and, therefore, an understanding of vegetation and soil spectral behavior is critical to the drought estimation. Recently, Ghulam et al. [Ghulam, A., Qin, Q., Zhan, Z., 2006. Designing of the perpendicular drought index. Environmental Geology, doi:10.1007/s00254-006-0544-2 (accessed March 8, 2007).] established the Perpendicular Drought Index (PDI) that is based on an extensive analysis of spatial distribution features of soil moisture in NIR-Red spectral space. In this paper, an improved drought monitoring method, the Modified Perpendicular Drought Index (MPDI), is developed introducing vegetation fraction, which takes into account both soil moisture and vegetation growth. To validate the drought indices proposed by this paper, Enhanced Thematic Mapper Plus (ETM+) and MODerate Resolution Imaging Spectrometer (MODIS) images from different times registered over different eco-systems with various drought conditions are used to calculate the PDI and MPDI over ground measuring points. The PDI and MPDI are then compared to an in-situ drought index obtained from field measurements made synchronously with the satellite overpass, including the bulk soil moisture content at different soil depths, field moisture capacity, wilting coefficient, etc. It is evident from the results that the PDI and the MPDI is highly accordant with in-situ drought values with the highest correlation (R2 = 0.8134) found between the MPDI and an in-situ drought index derived from 0–20 cm mean soil moisture. This study concludes that the PDI and the MPDI provide quite similar results for bare soil surfaces, especially in the early stages of vegetation growth. However, the MPDI demonstrates a much better performance in measuring vegetated surfaces since it takes into account both soil moisture and vegetation growth in the modeling process. The MPDI has the potential to provide a simple and real-time drought monitoring method in the remote estimation of drought phenomena.