Journal of Natural Environment

Monitoring changes in vegetation cover and its relationship with surface temperature and land use in Khodaafrin and Kalibar cities using Remote sensing technology

Document Type : Research Paper

Authors

1 Department of Environmental Sciences and Engineering, Faculty of Geography and Environmental Sciences, Hakim Sabzevari University, Sabzevar, Iran.

2 Department of Natural Geography, Faculty of Environmental Sciences and Planning, Isfahan University, Isfahan, Iran.

10.22059/jne.2023.365834.2602

Abstract

Investigating changes in vegetation density and land use is one of the most important aspects of natural resource management and reviewing environmental changes. In this research, using remote sensing technique, the monitoring of changes in vegetation cover and its relationship with surface temperature and land use in Khoda Afarin and Kalibar cities were investigated using remote sensing technology during a period of 22 years (2000-2022). To perform statistical and visual analysis on satellite images, Envi 5.6 and Arc GIS 10.8 software were used. NDVI index was used to investigate changes in vegetation area and quality. Also, in order to investigate qualitative changes in vegetation, the numerical values of this index were classified into three classes: dense, semi-dense, weak or no vegetation, and the temperature changes of the earth's surface during the study period using It was calculated from Landsat satellite images and then the land use maps were extracted based on the supervised classification method and through the maximum similarity algorithm. Based on the analysis, it was determined that in the studied period, 58,196 hectares, about 15.6% of dense vegetation density, and 38,415 hectares, about 10.2% of semi-dense vegetation density, have been lost. In fact, 96,611 hectares, about 25.8% of the density of dense and semi-dense vegetation, have been converted to other uses in 22 years. The study of land use in the region showed that the changes in vegetation density are mostly related to the use of agricultural and garden lands and pastures, and during the study period, the most destruction is related to dense vegetation density. Finally, investigating the relationship between vegetation cover and land surface temperature (LST) showed that the vegetation cover index (NDVI) has a negative and inverse correlation with the land surface temperature and in most areas that have denser vegetation cover; shows a lower temperature. The results of the research show that the most important factor in the changes in vegetation density in the region is human activities such as agriculture, construction and road construction, which have caused many changes in the land surface, the analysis of the area of these land uses shows He said that the level of agricultural lands and pastures has increased significantly, which is mainly the result of the conversion of dense vegetation, especially forests, to agriculture. The results of this research can be used by the organizations of agricultural jihad, natural resources and the Ministry of Interior.

Keywords

Abdolahi, J., Cheraqi, M.A., Rahimian, M. H., 2009. Comparison of Environmental Impacts of Land Use Change on Vegetation Change and Surface Temperature in Urban and Non-Urban Areas by Using Outcome Measurement. Journal of Environmental Studies 34(45), 85-96. (In Persian)
Allen, R.G., Tasumi, M., Trezza, R., Waters, R., Bastiaanssen, W., 2002. Surface Energy Balance Algorithm for Land (SEBAL)–Advanced training and Users Manual. Kimberly. Idaho Implementation, pp. 1- 98.
‏Amirin, M. K., Hasmadi, I. M., 2010. Land use changes in Perak catchment zone using remote sensing and GIS technique. pp. 15-19. (In Persian)
Ahmadi, A., akbari, E., jamalabadi, J., alemohammad, M., 2022. Impact of land use and vegetation on the formation of thermal islands Case Study. Qainat City jgs 22 (64), 79 - 93. (In Persian)
Brink, A., Eva, H., 2009. Monitoring 25 Years of Land Cover Changes Dynamics in Africa. A Sample Based Remote Sensing Approach. Applied Geography 29(4), 501-512.
Bandari, A.K, Kummar, A., Singh, G.K., 2012. Feature extraction using normalized difference vegetation index (NDVI), a case study of Jabalpur city. Procedia Technogy 6, 612 - 621.‏
Bertin, R.I., 2008. Plant phenology and distribution in relation to recent climate change. The Journal of the Torrey Botanical Society 135(1), 126-146.
Chen, A., He, B., Wang, H., Huang, L., Zhu, Y., Lv, A. 2015. Notable shifting in the responses of vegetation activity to climate change in China. Physics and Chemistry of the Earth. Parts A/B/C, 87, 60-66.‏
Darwish, T., Faour, G., 2008. Rangeland degradation in two watersheds of Lebanon. Lebanese Science Journal 9(1), 71-80.‏ (In Persian)
Depew, J.J., 2005. Habitat selection and movement patterns of cattle and white-tailed deer in a temperate Savanna. MSc Thesis, A and M University, Texas 71 p.
Ghorbannia, V., Mirsanjari, M., Liaghati, H., Armin, M., 2017. Estimating land surface temperature of land use and land cover in Dena County using single window algorithm and landsat 8 satellite data. Environmental Sciences 15(2), 55-74. (In Persian)
Herb, W. R., Janke, B., Mohseni, O., Stefan, H. G., 2008. Ground surface temperature simulation for different land covers. Journal of Hydrology 356(3-4), 327-343.‏
Jensen, J.R., 2007. Remote Sensing of the Environment: An Earth Resource Perspective, 2nd Edition. Prentice Hall, Saddle River.
Inteziri, A., Zandi, R., Khosrovian, M., 2019. Evaluation of spatial changes of vegetation and surface temperature using Landsat and MADIS images, case study: Fars province 1986-2017, Journal of Watershed Engineering and Management 11(4), 929-940. (In Persian)
Jiang, J., Tian, G., 2010. Analysis of the impact of land use or land cover change on land surface temperature with remote sensing. Procedia environmental sciences 2, 571-575.
-Khodaie, A., Pahlavani, A., Qalichipour, Z., Zandi, R., 2022. Evaluation of the ecological potential of Khodaafrin city using Dr. Makhdoom's ecological model and geographic information system. Watershed Engineering and Management 14(1), 40-54. (In Persian)
Karnieli, A., Agam, N., Pinker, R.T., Anderson, M., Imhoff, M.L., Gutman, G.G., Panov, N., Goldberg. A., 2010. Use of NDVI and land surface temperature for drought assessment merits and limitations. Journal of Climate 23(3),618-633.
Kerr, J.T., Ostrovsky, M., 2003. From space to Species: ecological application for remote sensing.Trend in Ecology and Evolution 18(6), 299-305.
Liu, Y., Li, Y., Li, S., Motesharrei, S., 2015. Spatial and temporal patterns of global NDVI trends: Correlations with climate and human factors. Remote Sensing 7(10), 13233-13250.
Magee, T.K., Ringold, P. L., Bollman, M.A., 2008. Alien species importance in native vegetation along wadeable streams, John Day River Basin, Oregon. USA. Plant Ecology 195(2), 287-307.
Mahdavian, S., Zeinali, B., Salahi, B., 2022. Monitoring land use changes and its relationship with land surface temperature and vegetation index in the southern areas of Ardabil province (Case study: Kiwi Chay catchment). Journal of RS and GIS for Natural Resources 13(4), 21-48.‏
Mazyidi, A., Elsadat Hosseini, F., 2014. The effect of land use and land cover change on the heat island in the urban area of ​​Yazd using remote sensing data. Journal of Geography and Development. 13(38), 1-12. (In Persian)
Mohammadyari, F., Pourkhbaz, H.R., Tavakoli, M., Aqdar, H., 2015. Preparation of vegetation map and monitoring its changes using remote sensing techniques and geographic information system (case study: Behbahan city). Geographical Information Scientific-Research Quarterly (Sephehr) 23(92), 23-34. (In Persian)
Molnar, G., 2016. Analysis of land surface temperature and NDVI distribution for Budapest using Landsat 7 ETM+ data. Acta Climatologica ET Chorologica 49, 49-61.
Mokaram, M., Mozain, M., Faraji, M. and Mousavi, K., 2017. Investigating vegetation changes in different growing seasons using satellite images and its relationship with temperature changes (study area: north of Darab city). Natural Ecosystems of Iran 8(3), 1-20. (In Persian)
Neteler, M., 2010. Estimating daily land surface temperatures in mountainous environments by reconstructed MODIS LST data. Remote Sensing 2(1), 333-351.
Pettorelli, N., Vik, J. O., Mysterud, A., Gaillard, J.M., Tucker, C. J., Stenseth, N. C., 2005. Using the satellite-derived NDVI to assess ecological responses to environmental change. Trends in Ecology and Evolution 20(9), 503-510.
Ramankutty, N., Foley, J.A., Olejniczak, N.J., 2002. People on the land: Changes in Global Population and Croplands During the 20th century. Ambio 31(3), 251-257.
Rawat, J.S., Biswas, V., Kumar, M., 2013. Changes in Land Use/ Cover Using Geospatial Techniques: A Case Study of Ramnagar Town Area, District Nainital, Uttarakhand, India. The Egyptian Journal of Remote Sensing and Space Science 16(1), 111-117.
Ruki, Z., Mohammadi, H., Zandi, R., 2023. The role of land use changes on the formation of ground surface temperature in cities (case study: Isfahan city). Natural geography researches 55(3), 1-17. (In Persian)
Rasooli, A., 2008. Fundamentals of Applied Remote Sensing with Emphasis on Satellite Image Processing, Tabriz University Press. First Edition, 806 p. (In Persian)
Saugier, B., 1996. Végétation et atmosphère France Dominos Flammarion. 107 p.
‏-Sharifi, L., Rasouli A. A., Hijazi, M.A., Rostamzadeh, H., 2012. Detecting changes in land use and land cover with object-oriented processing of satellite images (case study: Tabriz city), Journal of Geography and City Planning 17(44), 203-214. (In Persian)
Szuster, B. W., Chen, Q., Borger, M., 2011. A comparison of classification techniques to support land cover and land use analysis in tropical coastal zones. Applied Geography 31(2), 525-532.‏
Thenkabail, P.S., Smith, R.B., De Pauw, E., 2002. Evaluation of narrowband and broadband vegetation indices for determining optimal hyperspectral wavebands for agricultural crop characterization. Photogrammetric engineering and remote sensing 68(6), 607-622.
Tucker, C. J., 1979. Red and photographic infrared linear combinations for monitoring vegetation. Remote Sensing of Environment 8, 127-150.
Taschner, S., Ranzi, R., 2002. Comparing the opportunities of Landsat-TM and ASTER data for monitoring a debris covered glacier in the Italian Alps within GLIMS project. International Geoscience and Remote Sensing Symposium (IGARSS) 2, 1044–1046.
Zandi, R., Salmani Mohammad, M., Roki, Z., 2023. Measuring the degree of spatial autocorrelation of land surface temperature with land use, study sample: Isfahan city. Geography and Environmental Planning 34(1), 61-76. (In Persian)
Zhou, J., Zhan, W., Hu, D., Zhao, X., 2010. Improvement of mono-window algorithm for retrieving land surface temperature from HJ-1B satellite data. Chinese Geographical Science 20, 123-131.
Journal of Natural Environment
Volume 77, Issue 1
May 2024
Pages 59-73