Global dust Detection Index (GDDI); a new remotely sensed methodology for dust storms detection

Abstract

Dust storm occurs frequently in arid and semi-arid areas of the world. This natural phenomenon, which is the result of stormy winds, raises a lot of dust from desert surfaces and decreases visibility to less than 1 km. In recent years the temporal frequency of occurrences and their spatial extents has been dramatically increased. West of Iran, especially in spring and summer, suffers from significant increases of these events which cause several social and economic problems. Detecting and recognizing the extent of dust storms is very important issue in designing warning systems, management and decreasing the risk of this phenomenon. As the process of monitoring and prediction are related to detection of this phenomenon and it's separation from other atmospheric phenomena such as cloud, so the main aim of this research is establishing an automated process for detection of dust masses. In this study 20 events of dust happened in western part of Iran during 2000–2011 have been recognized and studied. To the aim of detecting dust events we used satellite images of MODIS sensor. Finally a model based on reflectance and thermal infrared bands has been developed. The efficiency of this method has been checked using dust events. Results show that the model has a good performance in all cases. It also has the ability and robustness to be used in any dust storm forecasting and warning system.

Evaluating MODIS Dust-Detection Indices over the Arabian Peninsula

“…Most previous work has only distinguished between bright land cover and dark land cover (Barren-Vegetation); however, the performance of the observation in reflective bands are different over various land cover types [27]. In this study, we go further by evaluating how the effectiveness of the various dust detection tests varies between urban, barren and vegetated areas within each region.…”

“…However, this is compensated by the much higher spatial and spectral resolution of MODIS, which has 36 spectral channels and generates imagery at spatial resolutions 250 m, 500 m and 1 km, depending on the channel [23]. Hence, several previous studies have developed and described dust-detection tests based on MODIS data [24][25][26][27][28]. Consequently, the aim of this study is to evaluate which of the existing MODIS dust detection methods are most effective over the Arabian Peninsula.…”

“…The NDDI, used in several previous studies [26,27,38], is calculated using reflective solar bands 3 and 7 of MODIS (Equation (1)). The spatial resolution of these bands is 500 m and is characterized by a spectral reflectance at a wavelength range of 459-479 nm for band 3 and 2105-2155 nm for band 7.…”

“…BTD methods utilize differences between multiple thermal emissive bands and have been used successfully across a wide range of regions [24,27,43,44]. The most commonly used thermal emissive bands are BT20, BT31 and BT 32, which are characterized by a wavelength range of 3.66-3.84 µm, 10.78-11.28 µm and 11.77-12.27 µm, respectively, and a spatial resolution of 1000 m. The equations for the existing BTD-related indices considered in this study are given by Equations (2) and (3).…”

“…Finally, we also consider an index derived from the MODIS reflective solar bands B2 (841-876 nm) at a spatial resolution of 250 m and B18 (931-941 nm) at a spatial resolution of 1000 m (Equation (5)) as developed by Samadi [27]. This index has been used over the western part of Iran to detect dust over bright and dark surfaces [27].…”