پهنه‌بندی رقومی شوری خاک سطحی با بکارگیری مدل جنگل تصادفی در اراضی شور دشت ایوانکی.

Abbas, A., Khan, S., Hussain, N., Hanjra, M. A., & Akbar, S. (2013). Characterizing soil salinity in irrigated agriculture using a remote sensing approach. Physics and chemistry of the Earth, Parts A/B/C, 55, 43-52.

Aksoy, S., Yildirim, A., Gorji, T., Hamzehpour, N., Tanik, A., & Sertel, E. (2022). Assessing the performance of machine learning algorithms for soil salinity mapping in Google Earth Engine platform using Sentinel-2A and Landsat-8 OLI data. Advances in Space Research, 69(2), 1072-1086.

Alarape, M. A., Ameen, A. O., & Adewole, K. S. (2021). Hybrid students’ academic performance and dropout prediction models using recursive feature elimination technique. In Advances on Smart and Soft Computing: Proceedings of ICACIn 2021 (pp. 93-106). Singapore: Springer Singapore.

Al-Khaier, F. (2003). Soil Salinity Detection Using Satellite Remote Sensing, ITC MSc. Thesis, Supervisor: Bastiaanssen, ITC, Netherlands.

Allbed, A., Kumar L., & Sinha, P. (2014). Mapping and Modeling Spatial Variation in Soil Salinity in the Al Hassa Oasis Based on Remote Sensing Indicators and Regression Techniques. Remote Sensing, 6, 1137-1157.

Dos Santos, E. P., da Silva, D. D., do Amaral, C. H., Fernandes-Filho, E. I., & Dias, R. L. S. (2022). A Machine Learning approach to reconstruct cloudy affected vegetation indices imagery via data fusion from Sentinel-1 and Landsat 8. Computers and Electronics in Agriculture, 194, 106753.

Elhag, M. (2016). Evaluation of different soil salinity mapping using remote sensing techniques in arid ecosystems, Saudi Arabia. Journal of Sensors, 2016.

Finke, P. A. (2012). On digital soil assessment with models and the Pedometrics agenda. Geoderma, 171, 3-15.

Gao, B. C. (1996). NDWI—A normalized difference water index for remote sensing of vegetation liquid water from space. Remote sensing of environment, 58(3), 257-266.

Guyon, I., Weston, J., Barnhill, S., & Vapnik, V. (2002). Gene selection for cancer classification using support vector machines. Machine learning, 46, 389-422.

Hammam, A. A., & Mohamed, E. S. (2020). Mapping soil salinity in the East Nile Delta using several methodological approaches of salinity assessment. The Egyptian Journal of Remote Sensing and Space Science, 23(2), 125-131.

Hassan, R., Ahmed, Z., Islam, M. T., Alam, R., & Xie, Z. (2021). Soil Salinity Detection Using Salinity Indices from Landsat 8 Satellite Image at Rampal, Bangladesh. Remote Sensing in Earth Systems Sciences, 4, 1-12.

Heim Jr, R. R. (2002). A review of twentieth-century drought indices used in the United States. Bulletin of the American Meteorological Society, 83(8), 1149-1166.

Huang, S., Tang, L., Hupy, J. P., Wang, Y., & Shao, G. (2021). A commentary review on the use of normalized difference vegetation index (NDVI) in the era of popular remote sensing [Erratum: December 2021, Vol. 32 (8), p. 2719].

Hunt, G. R., JW, S., & CJ, L. (1972). Visible and near-infrared spectra of minerals and rocks: V. Halides, phosphates, arsenates, vanadates and borates.

Huete, A. R., Jackson, R. D., & Post, D. F. (1985). Spectral response of a plant canopy with different soil backgrounds. Remote sensing of environment, 17(1), 37-53.

Jahanbazi, L., Mirkhani, R. & Qavami, M. S. (2018, September). Possibility of salinity changes detect by using remote sensing data. The focus of the article: Pedometry and Soil Evaluation, 16th Iran Soil Science Congress, Zanjan, Iran. (In Persian)

Jahanbazi, L., Heidari, A., Mohammadi, M. H., & Kuniushkova, M. (2023). Salt accumulation in soils under furrow and drip irrigation using modified waters in Central Iran. Eurasian Journal of Soil Science, 12(1), 63-78.

Kilic, O. M., Budak, M., Gunal, E., Acır, N., Halbac-Cotoara-Zamfir, R., Alfarraj, S., & Ansari, M. J. (2022). Soil salinity assessment of a natural pasture using remote sensing techniques in central Anatolia, Turkey. Plos one, 17(4), e0266915.

Kuhn, M., & Johnson, K. (2019). Feature engineering and selection: A practical approach for predictive models. Chapman and Hall/CRC.

Lv, Z. Z., Liu, G. M., Yang, J. S., Zhang, M. M., He, L. D., Shao, H. B., & Yu, S. P. (2013). Spatial variability of soil salinity in Bohai Sea coastal wetlands, China: Partition into four management zones. Plant Biosystems-An International Journal Dealing with all Aspects of Plant Biology, 147(4), 1201-1210.

McBratney, A. B., Santos, M. M., & Minasny, B. (2003). On digital soil mapping. Geoderma, 117(1-2), 3-52.

Metternicht, G. I., & Zinck, J. A. (2003). Remote sensing of soil salinity: potentials and constraints. Remote sensing of Environment, 85(1), 1-20.

Mohammadifar, A., Gholami, H., Golzari, S., & Collins, A. L. (2021). Spatial modelling of soil salinity: deep or shallow learning models. Environmental Science and Pollution Research, 28, 39432-39450.

Nielsen, D. R. (1985). Soil spatial variability. In Soil Spatial Variability. Proc. Workshop, 1985 (pp. 1-2). ISSS and SSSA.

Peng, J., Biswas, A., Jiang, Q., Zhao, R., Hu, J., Hu, B., & Shi, Z. (2019). Estimating soil salinity from remote sensing and terrain data in southern Xinjiang Province, China. Geoderma, 337, 1309-1319.

Saha, S. K. (2012). Microwave remote sensing in soil quality assessment. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 38, 34-39.

Scudiero, E., Corwin, D. L., & Skaggs, T. H. (2015, November). Regional-Scale Soil Salinity Assessment Using Landsat ETM+. In ASA, CSSA and SSSA International Annual Meetings (2015). ASA-CSSA-SSSA.

Singh, G., Bundela, D. S., Sethi, M., Lal, K., & Kamra, S. K. (2010). Remote Sensing and Geographic Information System for Appraisal of Salt‐Affected Soils in India. Journal of environmental quality, 39(1), 5-15.

Singh, A. (2022). Soil salinity: A global threat to sustainable development. Soil Use and Management, 38(1), 39-67.

Suleymanov, A., Abakumov, E., Suleymanov, R., Gabbasova, I., & Komissarov, M. (2021). The soil nutrient digital mapping for precision agriculture cases in the trans-ural steppe zone of Russia using topographic attributes. ISPRS International Journal of Geo-Information, 10(4), 243.

Staff, U. S. L. (1954). Diagnosis and improvement of saline and alkali soils. Agriculture handbook, 60, 83-100.

Vermeulen, D., & Van Niekerk, A. (2017). Machine learning performance for predicting soil salinity using different combinations of geomorphometric covariates. Geoderma, 299, 1-12.

Wang, Z., Zhao, G., Gao, M., & Chang, C. (2017). Spatial variability of soil salinity in coastal saline soil at different scales in the Yellow River Delta, China. Environmental Monitoring and Assessment, 189, 1-12.

Wang, J., Ding, J., Yu, D., Teng, D., He, B., Chen, X., ... & Su, F. (2020). Machine learning-based detection of soil salinity in an arid desert region, Northwest China: A comparison between Landsat-8 OLI and Sentinel-2 MSI. Science of the Total Environment, 707, 136092.

Wang, J., Peng, J., Li, H., Yin, C., Liu, W., Wang, T., & Zhang, H. (2021). Soil salinity mapping using machine learning algorithms with the Sentinel-2 MSI in arid areas, China. Remote Sensing, 13(2), 305.Yang, L., Huang, C., Liu, G., Liu, J., & Zhu, A. X. (2015). Mapping soil salinity using a similarity-based prediction approach: a case study in Huanghe River Delta, China. Chinese Geographical Science, 25, 283-294.

Willmott, C. J. (1982). Some comments on the evaluation of model performance. Bulletin of the American Meteorological Society, 63(11), 1309-1313.

ZHANG, W. T., Hong-Qi, W. U., Hai-Bin, G. U., Guang-Long, F. E. N. G., Ze, W. A. N. G., & SHENG, J. D. (2014). Variability of soil salinity at multiple spatio-temporal scales and the related driving factors in the oasis areas of Xinjiang, China. Pedosphere, 24(6), 753-762.