Atkinson, P, Jiskoot, H, Massari, R, Murray, T. (1998). Generalized linear modelling in geomorphology 1195, 1185–1195.
Baddock, M. C, Bullard, J. E, & Bryant, R. G. (2009). Dust source identification using MODIS: a comparison of techniques applied to the Lake Eyre Basin, Australia. Remote Sensing of Environment, 113 (7), 1511-1528.
Bani Habib, M. A, Shabestari, M. H, Hosseinzadeh, M. (2016). Hybrid model for strategic management of agricultural water demand in arid regions. Iranian Water Resources Research. 12 (4): 60-69
Boroughani, M, Pourhashemi, S, Hashemi, H, Salehi, M, Amirahmadi, A, Asadi, M. A. Z, & Berndtsson, R. (2020). Application of remote sensing techniques and machine learning algorithms in dust source detection and dust source susceptibility mapping. Ecological Informatics, 56, 101059
Breiman L. (2001). Random forests. Machine Learning, 45 (1):5-32.
Du, J, J. Fang, W. Xu and P. Shi. (2013). Analysis of dry/wet conditions using the standardized precipitation index and its potential usefulness for drought/flood monitoring in Hunan Province, China. Stochastic Environmental Research and Risk Assessment, 27: 377-387.
Ebrahimi-Khusfi, Z, Taghizadeh-Mehrjardi, R, & Mirakbari, M. (2021). Evaluation of machine learning models for predicting the temporal variations of dust storm index in arid regions of Iran. Atmospheric Pollution Research, 12 (1), 134-147.
Gholami, H, Mohamadifar, A, Sorooshian, A, & Jansen, J. D. (2020) a. Machine-learning algorithms for predicting land susceptibility to dust emissions: The case of the Jazmurian Basin, Iran. Atmospheric Pollution Research, 11(8), 1303-1315.
Gholami, H, Mohamadifar, A, & Collins, A. L. (2020)b. Spatial mapping of the provenance of storm dust: application of data mining and ensemble modelling. Atmospheric Research, 233, 104716.
Gholami, H, Mohamadifar, A, Rahimi, S, Kaskaoutis, D. G, & Collins, A. L. (2021). Predicting land susceptibility to atmospheric dust emissions in central Iran by combining integrated data mining and a regional climate model. Atmospheric Pollution Research, 12 (4), 172-187.
Gholami, H, Mohammadifar, A, Golzari, S, Kaskaoutis, D. G, & Collins, A. L. (2021) b. Using the Boruta algorithm and deep learning models for mapping land susceptibility to atmospheric dust emissions in Iran. Aeolian Research, 50, 100682
Goudie, A. (2018). Dust storms and ephemeral lakes. Desert 23:153–164
Heydarian, P, Ajdari, A, Judaki, M, Darvishikhatoni, J, Shahbazi, R. (2017). Identification of internal sources of dust storms using remote sensing and geology (Case study: Khuzestan province). 27 (105): 33-46
Kermani, M, Taherian, A, Izanloo, M. (2016). Analysis of satellite images of dust and dust storms in Iran in order to investigate internal and external sources and their control methods. Health guide. 2 (1): 39-51
Lee, J. A, Baddock, M. C, Mbuh, M. J, Gill, T. E. (2012). Geomorphic and land cover characteristics of aeolian dust sources in West Texas and eastern New Mexico, USA. Aeolian Research. 3:459–466
Mei, D, Xiushan, L, Lin, S, & Ping, W. A. N. G. (2008). A dust-storm process dynamic monitoring with multi-temporal MODIS data. The International Archives of the Photogrammetry. Remote Sensing and Spatial Information Sciences, 37, 965-970
Mehrabi, Sh, Jafari, R, Soltani Kopai, S. (2014). Investigation of NDDI index efficiency in dust storm zoning. Desert Ecosystem Engineering. 4 (8): 1-10.
Mirchooli, F, Motevalli, A, Pourghasemi, H. R, Mohammadi, M, Bhattacharya, P, Maghsood, F. F, & Tiefenbacher, J. P. (2019). How do data-mining models consider arsenic contamination in sediments and variables importance? Environmental monitoring and assessment, 191 (12), 1-19.
Marmion, M, Hjort, J, Thuiller, W, & Luoto, M. (2009). Computers & geosciences statistical consensus methods for improving predictive geomorphology maps 35, 615–625.
Pourghasemi, H. R, & Kerle, N. (2016). Random forests and evidential belief function-based landslide susceptibility assessment in Western Mazandaran Province, Iran. Environmental earth sciences, 75 (3), 185.
Rahmati, O, Mohammadi, F, Ghiasi, S. S, Tiefenbacher, J, Moghaddam, D. D, Coulon, F, & Bui, D. T. (2020). Identifying sources of dust aerosol using a new framework based on remote sensing and modelling. Science of the Total Environment, 737, 139508.
Sissakian, V, Al-Ansari, N, & Knutsson, S. (2013). Sand and dust storm events in Iraq. Journal of Natural Science, 5(10), 1084-1094.
Hahnenberger, M, & Nicoll, K. (2014). Geomorphic and land cover identification of dust sources in the eastern Great Basin of Utah, USA. Geomorphology, 204, 657-672.