1. AbdulWahab, S.A. and V. Lea. 2008. Reviewing fog water collection worldwide and in Oman. International Journal of Environmental Studies, 65(3): 487-500. [
DOI:10.1080/00207230802149983]
2. Acharya, A., T.C. Piechota, H. Stephen and G. Tootle. 2011. Modeled streamflow response under cloud seeding in the North Platte River watershed. Journal of Hydrology, 409(1-2): 305-314. [
DOI:10.1016/j.jhydrol.2011.08.027]
3. Amer, R. and H. El-Desoky. 2017. A remote sensing method for mapping sillimanite mineralization. Journal of African Earth Sciences, 134: 373-382. [
DOI:10.1016/j.jafrearsci.2017.07.008]
4. Batisha, A.F. 2015. Feasibility and sustainability of fog harvesting. Sustainability of water quality and ecology, 6: 1-10. [
DOI:10.1016/j.swaqe.2015.01.002]
5. Catani, F., D. Lagomarsino, S. Segoni and V. Tofani. 2013. Landslide susceptibility estimation by random forests technique: sensitivity and scaling issues. Natural Hazards and Earth System Sciences, 13(11): 2815-2831. [
DOI:10.5194/nhess-13-2815-2013]
6. Chen, W., H.R. Pourghasemi, A. Kornejady and N. Zhang. 2017. Landslide spatial modeling: introducing new ensembles of ANN, MaxEnt and SVM machine learning techniques. Geoderma, 305: 314-327. [
DOI:10.1016/j.geoderma.2017.06.020]
7. Chen, W., Y. Zhang, W. Gao and D. Zhou. 2016. The Investigation of Urbanization and Urban Heat Island in Beijing Based on Remote Sensing. Procedia-Social and Behavioral Sciences, 216: 141-150. [
DOI:10.1016/j.sbspro.2015.12.019]
8. Darabi, H., K. Shahedi, K. Solaimani and M. Miryaghoubzadeh. 2014. Prioritization of subwatersheds based on flooding conditions using hydrological model, multivariate analysis and remote sensing technique. Water and environment journal, 28(3): 382-392. [
DOI:10.1111/wej.12047]
9. Das, T. 2009. Land use/land cover change detection: an object oriented approach, Münster Germany. M.Sc. in Geospatial Technologies, Institute for Geoinformatics University of Münster, 70 pp.
10. Elhag, M. and J.A. Bahrawi. 2014. Conservational use of remote sensing techniques for a novel rainwater harvesting in arid environment. Environmental Earth Sciences, 72(12): 4995-5005. [
DOI:10.1007/s12665-014-3367-6]
11. Elith, J., J.R. Leathwick and T. Hastie. 2008. A working guide to boosted regression trees. Journal of Animal Ecology, 77(4): 802-813. [
DOI:10.1111/j.1365-2656.2008.01390.x]
12. Felicísimo, Á.M., A. Cuartero, J. Remondo and E. Quirós. 2013. Mapping landslide susceptibility with logistic regression, multiple adaptive regression splines, classification and regression trees, and maximum entropy methods: a comparative study. Landslides, 10(2): 175-189. [
DOI:10.1007/s10346-012-0320-1]
13. Fereydooni, H. and S. Mojeddifar. 2017. A directed matched filtering algorithm (DMF) for discriminating hydrothermal alteration zones using the ASTER remote sensing data. International Journal of Applied Earth Observation and Geoinformation, 61: 1-13. [
DOI:10.1016/j.jag.2017.04.010]
14. Ferrier, S., G. Manion, J. Elith and K. Richardson. 2007. Using generalized dissimilarity modelling to analyze and predict patterns of beta diversity in regional biodiversity assessment. Diversity and Distributions, 13(3): 252-264. [
DOI:10.1111/j.1472-4642.2007.00341.x]
15. Fessehaye, M., S.A. Abdul-Wahab M.J. Savage, T. Kohler, T. Gherezghiher and H. Hurni. 2014. Fog-water collection for community use. Renewable and Sustainable Energy Reviews, 29: 52-62. [
DOI:10.1016/j.rser.2013.08.063]
16. Ghanamijaber, M., M. Maleki and M. Gholizadeh. 2016. The Feasibility of Producing Water from Fog Case Study Fandooglo in Namin city. 5th conference on rainwater catchment systems. Gilan- Rasht, 24-25 February, 1-8 (In Persian).
17. Ghassabeh, Y.A., F. Rudzicz and H.A. Moghaddam. 2016. Fast adaptive algorithms for optimal feature extraction from Gaussian data. Pattern Recognition Letters, 70: 73-79. [
DOI:10.1016/j.patrec.2015.11.021]
18. Ghosh, R., T.K. Ray and R. Ganguly. 2015. Cooling tower fog harvesting in power plants-A pilot study. Energy, 89: 1018-1028. [
DOI:10.1016/j.energy.2015.06.050]
19. Halbe Z. and M. Aladjem. 2005. Model-based mixture discriminant analysis-an experimental study. Pattern Recognition, 38(3): 437-440. [
DOI:10.1016/j.patcog.2004.08.010]
20. https://landsat.usgs.gov.
21. Kashiwa, B.A. and C.B. Kashiwa. 2008. The solar cyclone: a solar chimney for harvesting atmospheric water. Energy, 33(2): 331-339. [
DOI:10.1016/j.energy.2007.06.003]
22. Koubbi, P., M. Moteki, G. Duhamel, A. Goarant, P.A. Hulley. R. O'Driscoll and G. Hosie. 2011. Ecoregionalization of myctophid fish in the Indian sector of the Southern Ocean: results from generalized dissimilarity models. Deep Sea Research Part II: Topical Studies in Oceanography, 58(1-2): 170-180. [
DOI:10.1016/j.dsr2.2010.09.007]
23. Liu, H. 2008. Generalized additive model. Department of Mathematics and Statistics University of Minnesota Duluth: Duluth, MN, USA, 43 pp.
24. Mahmoudi, P., Ch. Khajeh Amiri Khaledi and M.R. Salari Fanodi. 2016. Examining the feasibility of water harvesting from air humidity in the Southern province of Sistan and Baluchestan. Journal of Water and Soil Conservation, 23(2): 253-265.
25. Monde-geospatial.com
26. Moosavi, V. and Y. Niazi. 2016. Development of hybrid wavelet packet-statistical models (WP-SM) for landslide susceptibility mapping. Landslides, 13(1): 97-114. [
DOI:10.1007/s10346-014-0547-0]
27. Oh, H.J. and B. Pradhan. 2011. Application of a neuro-fuzzy model to landslide-susceptibility mapping for shallow landslides in a tropical hilly area. Computers and Geosciences, 37(9): 1264-1276. [
DOI:10.1016/j.cageo.2010.10.012]
28. Olivier, J. 2004. Fog harvesting: An alternative source of water supply on the West Coast of South Africa. Geo Journal, 61(2): 203. [
DOI:10.1007/s10708-004-2889-y]
29. Ozdemir, A. 2011. Using a binary logistic regression method and GIS for evaluating and mapping the groundwater spring potential in the Sultan Mountains (Aksehir, Turkey). Journal of Hydrology, 405(1-2):123-136. [
DOI:10.1016/j.jhydrol.2011.05.015]
30. Ridgeway, G. 2007. Generalized Boosted Models: A guide to the gbm package. Update, 1(1): 12 pp.
31. Schemenauer, R.S. and P. Cereceda. 2009. Meteorological conditions at a coastal fog collection site in Peru. Atmosfera, 6(3): 175-188.
32. Shahmohamadi, P., A.I. Che-Ani, N. Abdullah, M.M. Tahir, K.N.A. Maulud and M.F.I. Mohd-Nor. 2010. The Link between urbanization and climatic factors: a concept on formation of urban heat island. WSEAS Transactions on Environment and Development, 6(11): 754-768.
33. Sharma, V., M. Sharma, S. Kumar and V. Krishnan. 2016. Investigations on the fog harvesting mechanism of Bermuda grass (Cynodon dactylon). Flora, 224:59-65. [
DOI:10.1016/j.flora.2016.07.006]
34. Singh, R., T. Wagener, R. Crane, M.E. Mann and L. Ning. 2014. A vulnerability driven approach to identify adverse climate and land use change combinations for critical hydrologic indicator thresholds: Application to a watershed in Pennsylvania, USA. Water Resources Research, 50(4): 3409-3427. [
DOI:10.1002/2013WR014988]
35. Sobrino, J.A., J.C. Jiménez-Muñoz and L. Paolini. 2004. Land surface temperature retrieval from LANDSAT TM 5. Remote Sensing of Environment, 90(4): 434-440. [
DOI:10.1016/j.rse.2004.02.003]
36. Statnikov, A., C.F. Aliferis, D.P. Hardin and I. Guyon. 2011. A gentle introduction to support vector machines in biomedicine: Volume 1 Theory and Methods. Stallion Press. 200 pp. [
DOI:10.1142/7922]
37. Tehrany, M.S., B. Pradhan and M.N. Jebur. 2014. Flood susceptibility mapping using a novel ensemble weights-of-evidence and support vector machine models in GIS. Journal of Hydrology, 512: 332-343. [
DOI:10.1016/j.jhydrol.2014.03.008]
38. Weng, Q., D. Lu and J. Schubring. 2004. Estimation of land surface temperature-vegetation abundance relationship for urban heat island studies. Remote sensing of Environment, 89(4): 467-483. [
DOI:10.1016/j.rse.2003.11.005]
39. Xiong, Y., S. Huang, F. Chen, H. Ye, C. Wang and C. Zhu. 2012. The impacts of rapid urbanization on the thermal environment: A remote sensing study of Guangzhou, South China. Remote Sensing, 4(7): 2033-2056. [
DOI:10.3390/rs4072033]
40. Zha, Y., J. Gao and S. Ni. 2003. Use of normalized difference built-up index in automatically mapping urban areas from TM imagery. International Journal of Remote Sensing, 24(3): 583-594. [
DOI:10.1080/01431160304987]