Applied Research in Geographical Sciences

Applied Research in Geographical Sciences

Monitoring of vegetation and land use changes process using Landsat data (Case study: Sarvestan plain)

Authors
1 PhD student in Natural Resources Engineering, Hormozgan University, Bandar Abbas, Iran.
2 Associate Professor, Faculty of Agriculture and Natural Resources, Hormozgan University, Bandar Abbas, Iran.
3 Professor, Faculty of Natural Resources, University of Tehran, Tehran, Iran.
4 Senior Researcher, Pacific Institute, United States of America.
Abstract
Desertification is a serious environmental and socio-economic threat to the planet. The aim of this study is to use a scientific, reasonable and repeatable method to evaluate the process of vegetation and land use as two important factors in the process of desertification on different scales (local-regional and global). In this study, Sarvestan plain in Fars province was selected as the study area. For this purpose, Landsat images were used for TM (1993), ETM + (2001 and 2006) and OLI / TIRS (2016). Image monitoring was performed using image differentiation, NDVI index difference and land use maps. In 1993, 2001, and 1993, and 2016 difference maps, the decrease in the amount of water in the mouth of Lake Maharloo can be clearly seen as increasing changes in the infrared band. The results of the difference between the vegetation index and the increase in vegetation in the form of agricultural lands in 2016 compared to 2006 and 1993. According to the results of the monitoring classification, from 1993 to 2016, irrigated areas decreased from 7.11 hectares to 0.7575 hectares, on the other hand, the level of saline lands increased from 143.99 hectares to 223.83 hectares and the level of cultivated lands increased. (Agricultural and horticultural) has increased from 113.28 hectares to 14/2014 hectares, which due to the importance of saline lands and land use change indicators in the studies of the desertification assessment process, it can be concluded that the desertification process in the study area is growing.
Keywords

AbdelRahman, M.A.E., Natarajan, A., Rajendra, H., Prakash, S.S., (2019), Assessment of land degradation using comprehensive geostatistical approach and remote sensing data in GIS-model builder, The Egyptian Journal of Remote Sensing and Space Science, doi.org/10.1016/j.ejrs.2018.03.002.
Chavez, P.S., (1996), Image -based atmospheric corrections-Revisited and improved, Photogrammetric Engineering and Remote Sensing, 62, 1025– 1036.
Chokri, B., (2020), Study of desertification sensitivity in Talh region (Central Tunisia) using remote sensing, G.I.S. and the M.E.D.A.L.U.S. approach, Geoenvironmental Disasters, doi.org/10.1186/s40677-020-00148-w.
Dawelbait, M., Morari, F., (2012), Monitoring desertification in a Savannah region in Sudan using Landsat images and spectral mixture analysis, Journal of Arid Environments, 80: 45-55.
Du, Y., Teillet, P.M., Cihlar, J., (2002), Radiometric normalization of multi-temporal high-resolution satellite images with quality control for land cover change detection, Remote Sensing of Environment, 82, 123–134.
Lamchin, M., Lee,Yj., Lee, WK., Lee, EJ., Kim, M., Lim, H., Choi, H., Kim, S., (2016), Assessment of land cover change and desertification using remote sensing technology in a local region of Mongolia, Advances in Space Research. 57(1): 64-77.
Li, J., Yang, X., Jin, Y., Yang, Z., Huang, W., Zhao, L., Gao, T., Yo, H., Ma, H., Qin, Z., Xu, B., (2013), Monitoring and analysis of grassland desertification dynamics using landsat images in Ningxia China, Remote Sensing of Environment, 138: 19-26.
Liu, H., Zhou, Ch., Cheng, W., Long, Li., (2008), Monitoring sandy desertification of Otindag Sandy Land based on multi-date remote sensing images, Journal ActaEcological Sinica, 28: 627−635.
Lu, P., Mausel, E., Brondízio, E., Moran, A., (2004), Change detection techniques, International Journal of Remote Sensing. 25(12): 2365-2407.
Mihretab, G. Gh., Taibao, Y., Xuemei, Y., Congqiang, W., (2019), Assessment of desertification in Eritrea: land degradation based on Landsat images, Journal of Arid Land. 11: 319-331.
Singh, A., (1989), Digital change detection techniques using remotely sensed data, International Journal of Remote Sensing, 10, 989–1003.