Assessing the distribution of poplar plantations in Ardabil province | ||
| طبیعت ایران | ||
| Article 8, Volume 7, Issue 3 - Serial Number 34, July and August 2022, Pages 63-70 PDF (850.93 K) | ||
| Document Type: Scientific Letters | ||
| DOI: 10.22092/irn.2022.356224.1409 | ||
| Authors | ||
| younes rostamikia* 1; Khosrow Mirakhorlou2; Mohsen Calagari3; Reza Talaei4; Bayramali beyrami5 | ||
| 1Forests and Rangelands Research Department, Ardabil Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Ardabil, Iran | ||
| 2Research Institute of Forests and Rangelands, Agricultural Research Education and Extension Organization (AREEO), Tehran, Iran | ||
| 3Associate Prof., Research Institute of Forests and Rangeland, Agricultural Research, Education and Extension Organization (AREEO), Tehran, Iran | ||
| 4Assistant Professor, Soil Conservation and Watershed Management Research Department, Ardabil Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Ardabil, Iran | ||
| 5Researcher, Soil Conservation and Watershed Management Research Department, Ardabil Agricultural and Natural Resources Research and Education Center, Agricultural Research,Education and Extension Organization (AREEO), Ardabil, Iran | ||
| Abstract | ||
| Lack of wood resources and forest degradation in the country, on the one hand, and the inability to import wood and its products to the country, on the other hand, have doubled the importance of wood supply for the country. Lack of information on the current situation (area and distribution) of poplar planting in Ardabil province is one of the main problems of wood production managers in planning and managing wood supply. In this regard, preparing the distribution map and determining the area of poplar wood cultivation can help the planners of the province in assessing the situation of poplar planting as well as issues related to the cultivation and development of wood cultivation in the region. For this purpose, Multi-temporal Sentinel-2 satellite data were used from the beginning to the end of the poplar growth period (first half of March to December 2018), at least six time periods between 30 and 40 days. After processing, interpretation, data analysis, including atmospheric correction, geometric correction, selection of appropriate bandwidth and temporal composition of images, modeling based on time series data, and model testing in pilot areas with fieldwork information (training examples) for use in the model a map of poplar areas in Ardabil provinces was extracted. The results showed that the province's poplar plantations were equivalent to 1074 hectares in 1397. According to the distribution map, most poplar parts are located in Meshgin Shahr, Ardabil, and Khalkhal. Most of the poplar planting plots of less than 0.5 hectares are strip or linearly planted in the margins of gardens and streams to transfer water to farms, which in addition to producing wood, act as windbreaks and garden fences. Evaluation of the accuracy of maps extracted from Sentinel-2 satellite data using 140 samples was randomly selected. The overall accuracy of the prepared map was 93.2%, which indicates the acceptable accuracy in distinguishing poplar crops from other forest species and fruitful in the extracted maps. The findings of this study can be valuable basic information for use in monitoring the area of poplar planning and management decisions in wood farming in the province. | ||
| Keywords | ||
| Ardebil province; distribution map; poplar; satellite data | ||
| References | ||
|
Bergen, K.M. and Dronova, I., 2007. Observing succession on aspen-dominated landscapes using a remote sensing-ecosystem approach. Landscape Ecology, 22: 1395-1410. Eslami, A. and Zahedi, S., 2011, Providing poplar plantation map by Indian remote sensing (IRS) satellite imagery in northern Iran. African Journal of Agricultural Research, 6(20): 4769-4774. Guisan, A., and J. Theurillat, 2000. Equilibrium modeling of alpine plant distribution: how far can we go? Phytocoenologia, 30:353-384. Karasiak, N., Sheeren, D., Fauvel, M., Willm, J., Dejoux, J.-F. and C. Monteil. 2017. Mapping tree species of forests in southwest France using Sentinel-2 image time series. In: 2017. 9th International Workshop on the Analysis of Multitemporal Remote Sensing Images (MultiTemp), 4 p. Magnus, P., Heather, R., Eva, L., 2018. Tree species classification using multi-temporal Sentinel-2 data. Master thesis, University of Agricultural Sciences. 41p. Mirakhorlou, Kh. and Akhavan R., 2017. Forest density and orchard classification in Hyrcanian forests of Iran using Landsat 8 data. Journal of Forest Science, 63(8): 355–362 Pal, M. and Mather, P.M., 2005. Support vector machines for classification in remote sensing. International Journal of Remote Sensing, 26(5): 1007-1011. Szostak, M., Hawryło, P. and Piela, D., 2018. Using of Sentinel-2 images for automation of the forest succession detection. European Journal of Remote Sensing, 51(1): 142-149. | ||
|
Statistics Article View: 561 PDF Download: 570 |
||
Journal management system. designed by sinaweb