Detection of the changes in the cultivated area of pistachio orchards from the point of view of land management from 1987 to 2020 using remote sensing, a case study of Rafsanjan, Sirjan, and Anar Counties.
Subject Areas : Agriculture, rangeland, watershed and forestry
Ahmad Mazidi
1
,
Alireza Baniasadi
2
1 - Associate of Yazd University
2 - Kerman Province Management and Planning Organization
Keywords: detection changes, Pistachio, cultivated area, Kerman province, remote sensing,
Abstract :
The purpose of the study was to investigate the changes in pistachio cultivation in the three districts of Rafsenjan, Anar, and sirjan from the spatial planning perspective between 1987 and 2020. To achieve this goal, the Google Earth Engine system was used. And the radiometric and atmospheric images of the TM 5 Landsat and OLI Landsat 8 were used. Two conditions were used to separate pistachio gardens and other agricultural lands. The land with ndvi is equal to or higher 0.2 and lower elevation from 2000 m as pistachio garden and the land with ndvi is equal to or higher 0.2 and height of over 2000 meters were identified as other garden and agricultural land. By applying the conditions mentioned in the classification of the decision tree, the area of pistachio gardens and other agricultural lands of Anar, Rafsanjan and Sirjan were obtained over a 36 -year period. A review of the changes in the cultivation of pistachio gardens in all three counties showed that the development of agricultural orchards in the area under study and during the period (1987-2020) has been an increasing trend. This increase was 57.4 percent for Rafsanjan County, 55 % for Sirjan County, and about 37.3 percent for Anar County. The amount of cultivation of pistachio gardens in Rafsanjan County, in 1987 was 38,667 hectares, which increased to 69,704 hectares in 2020. In other words, about 31,000 hectares, equivalent to 55.4 percent of pistachio gardens in the above county, have increased. The trend line of land surface vegetation changes was obtained by using Modis satellite images. Modis' satellite images were available from 2000 to 2020 for all three counties. The time series graphs of the above images confirmed the increase in pistachio orchards in all three counties
1. Aboelnour, M, Engel, B. (2018). Application of Remote Sensing Techniques and Geographic Information Systems to Analyze Land Surface Temperature in Response to Land Use/Land Cover Change in Greater Cairo Region, Egypt. Journal of Geographic Information System, 10(1). https://doi.org/DOI: 10.4236/jgis.2018.
2. Amiri, F, Tabatabai, T. (1401). The effect of land use/land cover change on land surface temperature in the coastal area of Bushehr. Remote Sensing and Geographical Information System in Natural Resources, 13(2), 27-30. (In Persian).
3. Baltazar, M, Dumonteil, E. (2018). Application of Remote Sensing Techniques and Geographic Information Systems to Analyze Land Surface Temperature in Response to Land Use/Land Cover Change in Greater Cairo Region, Egypt. Journal of Geographic Information System, 10(1). https://doi.org/DOI: 10.4236/jgis.2018.
4. Dorn, P. Tripet, F. Dumonteil, E. (2012). Genetics and evolution of triatomines: from phylogeny to vector control. Heredity, 108(3), 190-202. https://doi.org/10.1038/hdy.2011.71
5. Enoguanbhor, E, Gollnow, F, Nielsen, Lakes, T, Walker, B. (2019). Land Cover Change in the Abuja City-Region, Nigeria: Integrating GIS and Remotely Sensed Data to Support Land Use Planning. Sustainability, 11(5). https://doi.org/10.3390/su11051313
6. Estafanove, M. J. (2001). A co-evolving decision tree classification method. Expert Systems with Applications, 34(1), 18-25.
7. Ezzatabadipour, H. (1394). Evaluation of the expansion of agricultural lands in Sirjan using remote sensing technology. The paper presented in the National Conference of Agricultural and Environmental Sciences of Iran. Retrieved from the database of the Academic Jahad Scientific Center. (In Persian).
8. Fitooza, H, Nakashima, T, Murata, T. (1995, November). A fuzzy classifier system that generates fuzzy if-then rules for pattern classification problems. In Proceedings of 1995 IEEE International Conference on Evolutionary Computation (Vol. 2, pp. 759-764). IEEE.
9. Hua, L, Zhang, X, Chen, Xi, Yin, K, Tang, L. (2017). A Feature-Based Approach of Decision Tree Classification to Map Time Series Urban Land Use and Land Cover with Landsat 5 TM and Landsat 8 OLI in a Coastal City, China. ISPRS International Journal of Geo-Information, 6(11). https://doi.org/10.3390/ijgi6110331
10. Jaiswal, R, Saxena, R, Mukherjee, S. (1999). Application of remote sensing technology for land use/land cover change analysis. Journal of the Indian Society of Remote Sensing, 27(2), 123. https://doi.org/10.1007/BF02990808
11. Kerman Agricultural -Jahad Organization(1389), Statistics of 1398. (In Persian).
12. Kerman Province Management and Planning Organization(1399), Provincial Planning Document, 1400. (In Persian).
13. Khanifar, H.(1389) income on the concept of land preparation and its applications in Iran, Land Planning, Second Year, Issue 2, Spring and Summer 2010. (In Persian).
14. Mahmoudabadi, M. (1389). Zoning of pistachio agricultural climate in Kerman province (Master's thesis). Yazd University - Faculty of Humanities - Department of Geography. (In Persian).
15. Mehrabi, A. (1396). Monitoring Vegetable Coating (Pistachio Gardens) Using Multi -Satellite Satellite Processing Case Study: Anar County (Kerman Province). Journal of Geography and Development, 17 (56). (In Persian).
16. Moody, A. y Strahler, AH 1994. Characteristics of composited AVHRR data and problems in
their classification, International Journal of Remote Sensing, 15 (17), 3473-3491. Moran, MS
17. Plan and Budget Organization of the Islamic Republic of Iran (1399), Provincial Planning Document. (In Persian).
18. Poo, M. M. Bi, G. Q., & (2008). Synaptic modifications in cultured hippocampal neurons: dependence on spike timing, synaptic strength, and postsynaptic cell type. Journal of neuroscience, 18(24), 10464-10472.
19. Provincial Management and Planning Organization, Provincial Statistical Yearbook, 1400
20. Rafei, A, Danekar, A, Zand Basiri, M, Bagherzadeh Karimi, M. (1401). An analysis of land use/land cover changes in Shadgan International Wetland in the last decade. Remote sensing and geographic information system in natural resources, 13(2), 1-5.
21. Sabze Gholambai, G, Jafarzadeh, K, Dashti, S, Yousefi Khan, S, Bazamra Balat, M. (1396). Disclosure of land use changes using remote sensing methods and geographical information system (Case Study: Ghaemshahr County). Journal of Environmental Science and Technology, 19 (3), 143-157. Doi: 10.22034/Jest.2017.11075
22. Sadeghi, V; Ebadi, H, Mohammadzadeh, A, Farnood Ahmadi, F. (2015). Detection of changes in multimeter remote sensing images with threshold index of integrated change index based on particle mass algorithm. Surveying Science and Technology, 5 (3), 175-191.
23. Sharma, H., & Kumar, S. (2016). A survey on decision tree algorithms of classification in data mining. International Journal of Science and Research (IJSR), 5(4), 2094-2097.
24. Shatarian, M., and Mousavi, S., and Momen Bek, Z. (1398). Application of Sensing Data from Disclosure Urban Land Use Change Case Study: Shahrekord. Geographical Information, 28 (111), 235-250. https://www.sid.ir/en/journal/viewpaper.aspx?id=48912925
25. Tapa, N. R., & Moorayama, S. K. (1993). A review on image segmentation techniques. Pattern recognition, 26(9), 1277-1294.