Monitoring Changes in Rice Cultivation Area using Multi-Temporal Satellite images (Case Study: Beiranshahr Region, Iran)

Anonymous. (2018). Statistical Center of Iran, available at www.amar.org.ir/english.

Anonymous. (2021). Statistical Center of Iran, available at www.amar.org.ir/english.

FAO. (2017). FAOStAT. Statistical Databases. Food and Agriculture Organization of the United Nations. http:/ www.fao.org.

Ghorbani Vaghei, H., Sabouri, H., & Taliei, F. (2021). A new method for providing water requirement of rice culture based on near-saturated soil matric potential, Water and Irrigation Management, 11(3), 421-432. [In Persian]. DOI: 10.22059/JWIM.2021.319595.864.

Gilbert, R.O. (1987). Statistical methods for environmental pollution monitoring. Van Nostrand Reinhold, New York.

IPBES. (2019). Global assessment report on biodiversity and ecosystem services of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services. E. S. Brondizio, J. Settele, S. Díaz, and H. T. Ngo (editors). IPBES secretariat, Bonn, Germany. https://doi. org/10.5281/zenodo.3831673.

Kamkar, B., Dashtimarvili, M., & Kazemi Posht Msary, H. (2019). Detection of rice and soybean grown felds and their related cultivation area using Sentinel-2 satellite images in summer cropping patterns to analyze temporal changes in their cultivation area (Case study: four watershed basins of Golestan Province). Journal of Water and Soil Conservation, 26(1), 151-167. [In Persian]. Doi: 10.22069/jwsc.2019.15246.3044.

Lennon, R. (2006). Remote sensing digital image analysis: An introduction. United States: Esa/Esrin, 4th Edition, Chapter 1, Springer, Germany, Berlin, Heidelberg.

Madani, K., AghaKouchak, A., & Mirchi, A. (2016). Iran’s Socio-economic Drought: Challenges of a Water-Bankrupt Nation. The International Society for Iranian Studies, 49(6), 997-1016.

Mansaray, L.R., Huang, W., Zhang, D., Huang, J., & Li, J. (2017). Mapping Rice Fields in Urban Shanghai, Southeast China, Using Sentinel-1A and Landsat 8 Datasets. Remote Sensing. 9(3), 257. https:// doi.org/10.3390/rs9030257.

Mousavi, S. R., Sarmadian, F., Omid, M., & Bogaert, P. (2022). Three-dimensional mapping of soil organic carbon using soil and environmental covariates in an arid and semi-arid region of Iran, Measurement, 201, 111706. https://doi. org/10.1016/j.measurement.2022.111706

Nicholson, Ch, F., Stephens, E. C., Kopainsky, B., Jones, A. D., Parsons, D., & Garrett, J. (2021). Food security outcomes in agricultural systems models: Current status and recommended improvements, Agricultural Systems, 188, 103028. https://doi. org/10.1016/j.agsy.2020.103028

Pourgholam, M. & Rahimzadegan, M. (2017). Identifcation of the area under cultivation of saffron using landsat 8 temporal satellite images (case study: Torbat Heydarieh). Journal of Remote Sensing and Geographic Information System in Natural Resources, 7(4), 97-115. [In Persian]. https:// girs.bushehr.iau.ir/ article_528884.html?lang=en.

Renza, D., Martinez, E., Molina, I., & Ballesteros, D.M. (2017). Unsupervised change detection in a particular vegetation land cover type using spectral angle mapper, Advances in Space Research. 59(8), 2019-2031. https://doi.org/10.1016/j. asr.2017.01.027

Rezayan, A., & Rezayan A.H. (2016). Future studies of water crisis in Iran based on processing scenario. Iranian Journal of Ecohydrology. 3(1), 1-11. [In Persian]. DOI: 10.22059/IJE.2016.59185.

Riahi, V., Zeaiean Firouzabadi, P., Azizpour, F., & Darouei, P. (2019). Identifcation and investigation of the area under cultivation in Lenjanat using Landsat 8 satellite images. Journal of Applied researches in Geographical Sciences, 19(52), 147-169. [In Persian]. DOI: 10.29252/jgs.19.52.147.

Sadoghi, H., Rajaee, T., & Rouhani, N. (2021). Identifcation and Investigation of Changes in Area of Hoseynabade Mishmast Village Using Satellite Images. Journal of Water and Soil Science, 24(4), 239-254. [In Persian]. DOI: 10.47176/jwss.24.4.42521.

Salmi, T., Määttä, A., Anttila, P., Ruoho-Airola, T. & Amnell, T. (2002). Detecting trends of annual values of atmospheric pollutants by the mann-kendall test and sen’s slope estimates -the excel template application makesens. Finnish Meteorological Institute. Publications on Air Quality. FIN-00101 Helsinki, Finland.

Talema, T., & Hailu, B.T. (2020). Mapping rice crop using sentinels (1 SAR and 2 MSI) images in tropical area: A case study in Fogera wereda, Ethiopia, Remote Sensing Applications, Society and Environment, 18,100290. https://doi.org/10.1016/j. rsase.2020.100290.

Weiss, M., Jacob, F., & Duveiller, G. (2020). Remote sensing for agricultural applications: A meta-review. Remote Sensing of Environment, 236, 111402. https://doi. org/10.1016/j.rse.2019.111402

Yaghoobzadeh, M., Ahmadee, M., Boroomand Nasab, S., & Haghayeghi Maghamam, S.A. (2017), Impact of Climate Change on Changing Trend of Evapotranspiration during the Growth Period of Irrigated and Rainfed Field Crops by AOGCM Models, Iranian Journal of Water Research in Agriculture (Formerly Soil and Water Sciences), 30(4), 511-523. [In Persian]. https://doi. org/10.22092/jwra.2017.109013.

Yaghoobzadeh, M., Ahmadee, M., Seyyed Kaboli, H., Zamani, Gh. R., & Amirabadizadeh, M. (2017), The evaluation of effect of climate change agricultural drought using ETDI and SPI indexes, Journal of Water and Soil Conservation, 24(4), 43-61. [In Persian]. DOI: 10.22069/JWFSt.2017.12202.2671.

Yaghoobzadeh, M. (2015). The simulation of evapotranspiration and moisture soil for agricultural drought evaluation in the base line and future by using remote sensing, Ph. D. dissertation, Shahid Chamran University of Ahvaz, Ahvaz. [In Persian].

Zarepour Moshizi, M., Yousef, A., Mozafar Amini, A., & Shojaei, P. (2022). Rural vulnerability to water scarcity in Iran: an integrative methodology for evaluating exposure, sensitivity and adaptive capacity, Geo Journal. https://doi.org/10.1007/s10708-022-10726-0

Zhang, H., Li, Q., Liu, J., Shang, J., Du, X., Zhao, L., Wang, N., & Dong, T. (2017). Crop classifcation and acreage estimation in North Korea using phenology features. GIS science and Remote Sensing. 54(3). 381-406. doi.org/10.1080/15481603.2016.1276255

Zhao, R., Li, Y., & Ma, M. (2021). Mapping Paddy Rice with Satellite Remote Sensing: A Review. Sustainability, 13, 503. https://doi.org/10.3390/su13020503