Preparation and Verification of Poplar Plantation Mapping Using Satellite Data of Sentinel-2 and Ground Data in Zanjan Province

Document Type : Original Article


1 Assistant Prof., Research Institute of Forests and Rangelands, Agricultural Research, Education and Extension Organization (AREEO), Tehran

2 Research Instructor, Research Institute of Forests and Rangelands, Agricultural Research, Education and Extension Organization (AREEO), Tehran

3 Research Expert, Research Institute of Forests and Rangelands, Agricultural Research, Education and Extension Organization (AREEO), Tehran

4 Ph.D. of Environment, Faculty of Natural Resources, University of Tehran


Lack of up-to-date, documented and scientific information on the current situation (area and distribution) of Zanjan poplar plantation is one of the main problems of wood production managers for planning and management of wood supply in the province and the country. In this study, Sentinel-2 satellite data with spatial resolution of 10 m in spectral bands were used and the ground truth map of existing poplar fields with 600 points was plotted in all cities and villages from field surveys. From the beginning to the end of the poplar growing season (first half of March to December 2018), at least 6 time periods of 30 to 40 days were used in the SVM classifier. Post-test and calibration of SVM model based on the phenology of poplar genus and field samples were extracted, populated area distribution map of province was extracted. The results showed that the total area of ​​poplar areas is 2744 hectares which covers 0.12% of total area of ​​Zanjan province. One percent of the total polygons were randomly selected for field control and after field control, the overall mapping error was obtained and calculated. In this study, the exact location and area of ​​poplar mills were estimated with acceptable accuracy (96%). So that using extracted information (distribution map of poplars of the province) can provide studies on comprehensive planning of poplars and sustainable management of wood production from the poplars of the province.


  1. Asadi, F., 1994, Investigation of Economic and Social Causes of Population Reduction in Zanjanrood Area, M.Sc., Faculty of Natural Resources, Tehran University, 110 PP. (In Persian).

    Asadi, F., Nouri, F. & Yousefi, B., 2015, Vegetative Changes of Populus Nigra L. on the Rivers Margins of Kermanshah Province, Iranian Journal of Forest and Poplar Research, 23(2), PP. 221-209 (In Persian).

    Alizadeh Anaraki, K., Lashkar Ara, F. & Kiadaliri, H., 2012, Socioeconomic Factors Influencing Population Development in Guilan Province (Case Study: Somesara County), Iranian Forest and Poplar Research, 20(2), PP. 346-356 (In Persian).

    Bagheri, M., Ansari, A., Kazemi, A., Bayat, M., Heidari Masteali, S. & Ahmadloo, F., 2020, Estimation and Survey of Parks and Green Spaces Per Capita in Khomein Using Remote Sensing and Satellite Imagery, J. of Environmental Science and Ttechnology, under press.

    Bagheri, M., Ansari, A., Kazemi, A., Bayat, M. & Heidari Masteali, S., 2021, Investigating the Spatial Distribution of Parks and Urban Green Spaceareas in Khomein Using Landscape Approach and Sentinel-2 Satellite Images, Scientific Research Quarterly of Geographical Data (SEPEHR), 118, PP. 203-218.


    1. 1. Eslami & Zahedi
    2. Oukrop


    Bayat, M., Noi, P.T., Zare, R. & Bui, D.T., 2019, A Semi-Empirical Approach Based on Genetic Programming for the Study of Biophysical Controls on Diameter-Growth of Fagus Orientalis in Northern Iran, J. of Remote Sensing, 11(14), PP. 1-18.

    Bergen, K.M. & Dronova, I., 2007, Observing Succession on Aspen-Dominated Land-scapes Using a Remote Sensing-Ecosystem Approach, J. of Landscape Ecology, 22, PP. 1395-1410.

    Bourque, C.P.A. & Bayat, M., 2015, Landscape Variation in Tree Species Richness in Northern Iran Forests, PloS one., 10(4), PP. 1-18.

    Bourque, C.P.A., Bayat, M. & Zhang, C., 2019, An Assessment of Height–Diameter Growth Variation in an Unmanaged Fagus Orientalis-Dominated Forest, European J of Forest Research, 138(4), PP. 607-621.

    Eshaghi, M.A. and Shataee Joybari, S., 2016. Preparation map of Forest Fire Risk Using SVM, RF & MLP Algorithms (Case Study: Golestan National Park, Northeastern Iran). Journal of Wood and Forest Science and Technology, 23(4), pp.1333-154

    Darvishsefat, A. & Shetaei, Sh., 1997, Forest Landscape Data Mapping Using Digital Method, Iranian Journal of Natural Resources, 50(2), PP. 40-35 (In Persian).

    Darvishsefat, A., Ghaffari, F. & Bonyad, A., 2014, Evaluation of Satellite Imaging Capabilities in Population Separation (Case Study: Somaye Sara City), Iranian Journal of Forest and Poplar Research, 22(3), PP. 401-392.

    Darvishsefat, A., Arzhangi, R., Bonyad, A. & Renoud, Gh., 2016, Evaluating the Feasibility of Mapping Poplar Trees with Landsat 8 Data (Case Study: Talesh and Somaye Sara Counties), Iranian Forest Journal, 3, PP. 312-301 (In Persian).

    Delfan E, Naghavi H, Maleknia R, Nouredini A. Comparing the Capability of Sentinel 2 and Landsat 8 Satellite Imagery in Land Use and Land Cover Mapping Using Pixel-based and Object-based Classification Methods. DEEJ. 2020; 8 (25) :1-12


    Eslami, A. & Sobheh Zahedi, Sh., 2011, Providing Poplar Plantation Map by Indian Remote Sensing (IRS) Satellite Imagery in Northern Iran, African Journal of Agricultural Research, 6(20), PP. 4769-4774.

    Ghorbanian, A., Zaghian, S., Asiyabi, R.M., Amani, M., Mohammadzadeh, A. & Jamali, S., 2021, Mangrove Ecosystem Mapping Using Sentinel-1 and Sentinel-2 Satellite Images and Random Forest Algorithm in Google Earth Engine, Remote Sensing, 13(13), P. 2565.

    Grabska, E., Hostert, P., Pflugmacher, D. & Ostapowicz, K., 2019, Forest Stand Species Mapping Using the Sentinel-2 Time Series, Remote Sensing, 11(10), P. 1197.

    Guisan, A. & Theurillat, J., 2000, Equilibrium Modeling of Alpine Plant Distribution: How Far Can We Go?, Phytocoenologia, 30, PP. 353-384.Hamzeh, B., Ashoori, P., Jalili, A., Habibi, R. & Mousavi, A., 2020, Comparison of Soil Seed Bank and Vegetation in Semi-Steppe Rangelands of Zanjan Province, Case Study: Anguran Protected Area, Ghara-Boogh Station, Nature of Iran, 24, PP. 69-80 (In Persian).

    Jia, M., Wang, Z., Wang, C., Mao, D. & Zhang, Y., 2019, A New Vegetation Index to Detect Periodically Submerged Mangrove Forest Using Single-Tide Sentinel-2 Imagery, Remote Sensing, 11(17), P. 2043.

    Lashkarbloki, A. & Kohneh, A., 2015, Seedling Production from Natural Poplar Hybrid Cultivars and their Use in the Comprehensive Timber Program, Journal of Forest Research and Development, 1(4), PP. 317-307 (In Persian).

    Mohammadpour, P., Kordovani, P. & Ebadattalab, M., 2011, Investigating the Development of Wood Agriculture in Guilan East Region, Geographical Land Quarterly, 32, PP. 32-25 (In Persian).

    Pal, M. & Mather, P.M., 2005, Support Vector Machines for Classification in Remote Sensing, International Journal of Remote Sensing, 26(5), PP. 1007-1011.

    Richards, J.A., 2013, Remote Sensing Digital Image Analysis, Springer-Verlag Berlin Heidelberg, Fifth Edition.

    Sivanpilla, R., Smith, C.T., Srinivasan, R., Messina, M.G. & Ben Wu, X., 2006, Estimation of Managed Loblolly Pine Stands Age and Density with Landsat ETM+ Data, Forest Ecology and Management, 223, PP. 247-254.

    Thanh Noi, P. & Kappas, M., 2017, Comparison of Random Forest, K-Nearest Neighbor, and Support Vector Machine Classifiers for Land Cover Classification Using Sentinel-2 Imagery, Sensors, 18(1), P. 18.

    Vafaei S, Soosani J, Adeli K, Fadaei H, Naghavi H, Pham TD, Tien Bui D. Improving Accuracy Estimation of Forest Aboveground Biomass Based on Incorporation of ALOS-2 PALSAR-2 and Sentinel-2A Imagery and Machine Learning: A Case Study of the Hyrcanian Forest Area (Iran). Remote Sensing. 2018; 10(2):172. 10.3390/rs10020172

    Yousefi, B. & Modirrahmati, A., 2018, Evaluation of Growth and Production of Poplar (Populus Nigra) Cultivars under a Period of Severe Drought in a Comparative Populetum of Sanandaj, Iranian Forest and Poplar Research, 26(2), PP. 276-290 (In Persian).