رابطه بین حجم نمونه آموزشی و دقت طبقه‌بندی برنج با استفاده از سنتینل 1 و 2 مطالعه موردی: مازندران، ایران

• Chang, L., Chen, Y.T., Wang, J.H., Chang, Y.L. (2021). Rice-Field Mapping with Sentinel-1A SAR Time-Series Data. Remote Sens. 13, 103, doi:10.3390/RS13010103.
• 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 Sens. 9, 257, doi:10.3390/RS9030257.
• Mohanty, S., Wassmann, R., Nelson, A., Moya, P., Jagadish, S.V.K. (2013). Rice and Climate Change: Significance for Food Security and Vulnerability. Philipp. Int. Rice Res. Inst., 49, 1–14.
• Bouvet, A., Le Toan, T. (2011). Use of ENVISAT/ASAR Wide-Swath Data for Timely Rice Fields Mapping in the Mekong River Delta. Remote Sens. Environ. 115, 1090–1101, doi:10.1016/J.RSE.2010.12.014.
• Kamkar, B., Dashtimarvili, M., Kazemi, H. (2019). Detection of Rice and Soybean Grown Fields 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). J. Water Soil Conserv. 26, 151–167, doi:10.22069/jwsc.2019.15246.3044.

• Ziaiean Firouzabadi, p., Sayyad Bidhendi, l., eskandari nodeh, m. (2010). Mapping and Acreage Estimating of Rice Agricultural Land Using RADARSAT a Satellite Images. Geogr. Res. Q., 41.
• Jin, C., Xiao, X., Dong, J., Qin, Y., Wang, Z. (2016). Mapping Paddy Rice Distribution Using Multi-Temporal Landsat Imagery in the Sanjiang Plain, Northeast China. Front. Earth Sci. 10, 49–62, doi:10.1007/S11707-015-0518-3.

8-Sakamoto, T., Sprague, D.S., Okamoto, K., Ishitsuka, N. (2018). Semi-Automatic Classification Method for Mapping the Rice-Planted Areas of Japan Using Multi-Temporal Landsat Images. Remote Sens. Appl. Soc. Environ. 10, 7–17, doi:10.1016/J.RSASE.2018.02.001.

• Zhang, G., Xiao, X., Dong, J., Kou, W., Jin, C., Qin, Y., Zhou, Y., Wang, J., Menarguez, M.A., Biradar, C. (2015). Mapping Paddy Rice Planting Areas through Time Series Analysis of MODIS

Land Surface Temperature and Vegetation Index Data. ISPRS J. Photogramm. Remote Sens. 106, 157–171, doi:10.1016/J.ISPRSJPRS.2015.05.011.

• Saadat, M., Hasanlou, M., Homayouni, S. (2019). RICE CROP MAPPING USING

SENTINEL-1 TIME SERIES IMAGES (CASE STUDY: MAZANDARAN, IRAN). Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. XLII-4/W18, 897–904, doi:10.5194/isprs-archivesXLII-4-W18-897-.9102

• Inoue, S., Ito, A., Yonezawa, C. (2020). Mapping Paddy Fields in Japan by Using a Sentinel1 SAR Time Series Supplemented by Sentinel-2 Images on Google Earth Engine. Remote Sens.

12, 1622, doi:10.3390/RS12101622.

رابطه بین حجم نمونه آموزشی و دقت طبقهبندی برنج با استفاده از سنتینل 1 و 2... رحمان باریده، فرشته نسیمی    ¹⁹

• Torbick, N., Chowdhury, D., Salas, W., Qi, J. (2017). Monitoring Rice Agriculture across Myanmar Using Time Series Sentinel-1 Assisted by Landsat-8 and PALSAR-2. Remote Sens. 9, 119, doi:10.3390/RS9020119.
• Amani, M., Kakooei, M., Moghimi, A., Ghorbanian, A., Ranjgar, B., Mahdavi, S., Davidson, A., Fisette, T., Rollin, P., Brisco, B. (2020). Application of Google Earth Engine Cloud Computing Platform, Sentinel Imagery, and Neural Networks for Crop Mapping in Canada. Remote Sens. 12, 1–18, doi:10.3390/rs12213561.
• Tiwari, V., Matin, M.A., Qamer, F.M., Ellenburg, W.L., Bajracharya, B., Vadrevu, K., Rushi,

B.R., Yusafi, W. (2020). Wheat Area Mapping in Afghanistan Based on Optical and SAR TimeSeries Images in Google Earth Engine Cloud Environment. Front. Environ. Sci. 8, doi:10.3389/fenvs.2020.00077.

• 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 Sens. Appl. Soc. Environ. 18, doi:10.1016/j.rsase.2020.100290.
• Darzi, A., Karandish, F. (2016). Rice Cultivation Management in Mazandaran Province under Climate Change. Water Res. Agric. 30, 333–346, doi:10.22092/jwra.2016.107154.
• Farsadnia, F., Rostami Kamrod, M., Moghadam Nia, A. (2012). Rainfall Trend Analysis of Mazandaran Province Using Regional Mann-Kendall Test. Iran-Water Resour. Res. 8, 60–.07
• Goli, I., Azadi, H., Miceikienė, A., Tanaskovik, V., Stamenkovska, I.J., Kurban, A., Viira, A.H. (2022). Training Needs Assessment: The Case of Female Rice Farmers in Northern Iran. Agric. 12, 390, doi:10.3390/AGRICULTURE12030390/S1.
• Congalton, R.G., Green, K. (2008). Assessing the Accuracy of Remotely Sensed Data, CRC Press, ISBN 9780429143977.
• Taheri, M., Emadzadeh, M., Gholizadeh, M., Tajrishi, M., Ahmadi, M., Moradi, M. (2019).

Investigating the Temporal and Spatial Variations of Water Consumption in Urmia Lake River Basin Considering the Climate and Anthropogenic Effects on the Agriculture in the Basin. Agric. Water Manag. 213, 782–791, doi:10.1016/J.AGWAT.2018.11.013.