Abbasi, S., Amiri Baghbadrani, F., 2010. The importance of vegetation in measuring biodiversity, National Conference on Biodiversity and its effects on agriculture and the environment, 17 August, National Plant Gene Bank of Iran. pp. 662-667. (In Persian).
Abdullah Nejad, K., 2016. Random time series models in predicting monthly rainfall. Case Study: Hashemabad Station, Gorgan. Journal of Spatial Planning 5(17), 15-25. (In Persian)
Akbari, M., 2003. Evaluation and classification of desertification with RS and GIS technique in the arid region of northern Isfahan. Master Thesis. Desertification group. Isfahan University of Technology. Faculty of Natural Resources, 167 p. (In Persian)
Akbarzadeh, M., Mirhaji, S., 2006. Vegetation changes due to rainfall in the steppe pastures of Rudshor. Iranian Range and Desert Research 13 (3), 222-235. (In Persian)
Alavi Panah, S., 2003. Application of Remote Sensing in Earth Sciences. Ecology 34(1), 29-38. (In Persian).
Aliabadi, K., Entezari, A., Eskandari, N., 2014. Estimation of Physical Parameter (Biomass) of Vegetation Using Remote Sensing Data. Quarterly Journal of Geographical Studies of Arid Areas 4(15), 23-33. (In Persian)
Asian Cheetah and Related Ecosystem Conservation Project. 2008. Environmental Protection Organization, Phase I Report. 73 p. (In Persian).
Bachelet, D., Neilson, R.P., Lenihan, J.M., Drapek, R.J., 2001. Climate change effects on vegetation distribution and carbon budget in the United States. Ecosystems 4, 164-185.
Bagherpour, M., Sidian, S.M., Fathabadi, A., Mohammadi, A., 2018. Evaluation of the efficiency of Man Kendall test in identifying the trend of self-correlated series. Iranian Journal of Watershed Management Science and Engineering 11(36), 11-21. (In Persian)
Bannari, A., Staenz, K., Haboudane, D., Khurshid, K., 2006. Sensitivity analysis of chlorophyll indices to soil optical properties using ground-reflectance data. 2006 IEEE International Symposium on Geoscience and Remote Sensing, IEEE. pp. 120-123.
Baret, F., Jacquemoud, S., 1994. Modeling canopy spectral properties to retrieve biophysical and biochemical characteristics, Imaging spectrometry—a tool for environmental observations, Springer. pp. 145-167.
Bozorg Nia, S., Khorrami, M., 2008. Time series analysis with MINITAB 14 software. Sokhan Gostar, 336 p. (In Persian).
Depew, J.J., 2005. Habitat selection and movement patterns of cattle and white-tailed deer in a temperate savanna. Master thesis. Rangeland Ecology and Management group. Texas A&M University, 85 p.
Elvidge, C.D., Chen, Z., 1995. Comparison of broad-band and narrow-band red and near-infrared vegetation indices. Remote sensing of environment 54, 38-48.
Faber-Langendoen, D., Keeler-Wolf, T., Meidinger, D., Tart, D., Hoagland, B., Josse, C., Navarro, G., Ponomarenko, S., Saucier, J.-P., Weakley, A., 2014. EcoVeg: a new approach to vegetation description and classification. Ecological Monographs 84 (4), 533-561.
Ghobadian, A., 1982. Central Plateau of Iran, Yazd Province Natural Landscape in Relation to Desert Issues (General Survey, Geomorphology, Pedology, Hydrology and Hydrogeology). Jundishapur University, 350 p. (In Persian)
Gholam Hosseini, Q., Ismaili, H., Ahani, H., Teymouri, A., Ebrahimi, M., Kimi, H., Zahrabi, H., 2010. Topographic and Climatic Factors on the Distribution of Brown Bear (Ursus arctos) (Carnivora: Ursidae) (Linnaeus, 1758) in Fars Province Using Geographic Information System (GIS). Iranian Journal of Biology 23(2), 215-233. (In Persian)
Gocic, M., Trajkovic, S., 2013. Analysis of changes in meteorological variables using Mann-Kendall and Sen's slope estimator statistical tests in Serbia. Global and Planetary Change 100, 172-182.
Goward, S.N., Cruickshanks, G.D., Hope, A.S., 1985. Observed relation between thermal emission and reflected spectral radiance of a complex vegetated landscape. Remote sensing of Environment 18, 137-146.
Hamed, K.H., 2008. Trend detection in hydrologic data: the Mann–Kendall trend test under the scaling hypothesis. Journal of hydrology 349, 350-363.
Hamed, K.H., Rao, A.R., 1998. A modified Mann-Kendall trend test for autocorrelated data. Journal of hydrology 204, 182-196.
Harris, A., Carr, A.S., Dash, J., 2014. Remote sensing of vegetation cover dynamics and resilience across southern Africa. International Journal of Applied Earth Observation and Geoinformation 28, 131-139.
Hoersch, B., Braun, G., Schmidt, U., 2002. Relation between landform and vegetation in alpine regions of Wallis, Switzerland. A multiscale remote sensing and GIS approach. Computers, Environment and Urban Systems 26, 113-139.
Huete, A., Justice, C., Van Leeuwen, W., 1999. MODIS vegetation index (MOD13). Algorithm theoretical basis document 3, 295-309.
Huete, A.R., Didan, K., 1999. MODIS vegetation index (MOD 13) algorithm theoretical basis document. Science Team Members Wim Van Leeuwen1, MODIS Associate Science Team Member, the University of Arizona, 129 p.
Jahantigh, M., Jahantigh, M., 2021. Investigation of Wind Erosion Status and Identification of Suitable Species for Soil Conservation (Case Study: Gharghari Region, Sistan, Iran). Degradation and Rehabilitation of Natural Land 1(2), 59-68. (In Persian)
Kardovani, p., 1988. Characteristics (Climatic, Soil and Geomorphological) of Dry Areas and Its Issues. Journal of the Faculty of Literature and Humanities, University of Tehran 26 (1, 2, 3, 4), 154-168. (In Persian)
Kashki, M. T., Shahmoradi, A.Namdoost, T., 2016. Investigation of the dynamics and trend of vegetation changes in desert ecosystems (Case study: Jajarm region, North Khorasan). Journal of Desert Ecosystem Engineering 4(7), 87-98. (In Persian)
Kazeminia, A., 2018. Application of remote sensing and GIS in the investigating vegetation coverage. Geospatial Engineering Journal 9(1), 75-85. (In Persian)
Kermani, F., Raygani, B., Nezami, B., Goshtasb, H., Khosravi, H., 2016. Evaluating the trend of vegetation changes in Turan Biosphere Reserve using remote sensing data. Master Thesis. Natural Resources-Environmental Engineering group, Land Evaluation and Management, Faculty of Environment, 71 p. (In Persian)
Kermani, F., Raygani, B., Nezami, B., Goshtasb, H., Khosravi, H., 2018. Assessing the trend of vegetation changes in arid and semi-arid regions (Case study: Turan Protected Area). Journal of Desert Ecosystem Engineering 6(17), 1-14. (In Persian)
Khaliq, M.N., Ouarda, T.B., Gachon, P., Sushama, L., St-Hilaire, A., 2009. Identification of hydrological trends in the presence of serial and cross correlations: A review of selected methods and their application to annual flow regimes of Canadian rivers. Journal of Hydrology 368, 117-130.
Khwajeddin, S. J., 1997. The role of remote sensing in the development of agriculture and sustainable natural resources and the use of this data in agricultural and industrial planning, the first seminar on the role of industry in agricultural development, Shahrak Scientific and Research Publications in collaboration with Mani Publications, Isfahan. pp. 447-460. (In Persian)
Kouchali, F., Nezami Balochi, B., Goshtasb, H., Raigani, B., 2019. Identification of key habitats for the protection of brown bear (Ursus arctos) in the northern slopes of Alborz. Journal of Animal Environment 10(3), 1-8. (In Persian)
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, 287-307.
Mattson, D.J., Merrill, T., 2002. Extirpations of grizzly bears in the contiguous United States, 1850–2000. Conservation Biology 16, 1123-1136.
Mir Ahsani, M. S., Salman Mahini, A. R., Sufyanian, A., Mohammadi, J., Modares, R., Jafari, R., Pourmanafi, S., 2020. Evaluating the trend of vegetation changes using time series images and Mann-Kendall test in Gavkhooni watershed. Journal of Environmental Science 45(1), 99-114. (In Persian)
Mohammadyari, F., Pourkhbaz, H. R., Tavakoli, M., Aqdar, H., 2014. Preparation of vegetation map and monitoring of its changes using remote sensing techniques and geographic information system (Case study: Behbahan city). Geographical Information Quarterly (Sepehr) 23(92), 23-34. (In Persian)
Mokhtari, A., Faiznia, S., Ahmadi, H., Khajauddin, S.Rahnama, F., 2001. Application of Remote Sensing in Preparation of Land Use Information Layers and Land Cover in MPSIAC Soil Erosion Model. Journal of Research and Construction 13(1), 82-87. (In Persian)
Nateghi, S., Lamenter, A., Ehsani, A., BazrAfshan, A., 2017. Investigation of vegetation changes based on vegetation indices using remote sensing. Iranian Journal of Range and Desert Research 24 (4), 778-790. (In Persian).
Nirumand, H. A., Bozorgnia, S.A., 2011. Time Series. Payame Noor University, 292 p. (In Persian)
Pelham Abbasi, A., 2010. Barriers and limitations of the use of remote sensing in estimating plant parameters in arid and semi-arid regions. Geographical Information Quarterly (Sepehr) 18(72), 28-31. (In Persian)
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 & Evolution 20, 503-510.
Peymanifard, B., 1996. A study of some ecological characteristics of arid and semi-arid regions. The second national conference on desertification and various methods of desertification, September 1 and 2, Deputy Minister of Education and Research of the Ministry of Jihad Sazandegi. pp. 1-7. (In Persian)
Rahmati, M., Asghari Bajestani, M., 2016. Presenting a method to eliminate the ribbon error in the images of linear array sensors. Journal of the Iranian Association of Electrical and Electronic Engineers 13(2), 93-102. (In Persian)
Rayegani, B., Jahani, A., Sattari Rad, A., Shoghi, N., 2019. Predicting Land Use Change for 2030 Using Remote Sensing and Landsat Multi-Time Images (Case Study: Mashhad). Journal of Land Management 10(2), 249-269. (In Persian)
Rayegani, B., Barati, S., Goshtasb, H., Sarkheil, H., Ramezani, J., 2019. An effective approach to selecting the appropriate pan-sharpening method in digital change detection of natural ecosystems. Ecological Informatics 53, 100984.
Richardson, A.J., Everitt, J.H., 1992. Using spectral vegetation indices to estimate rangeland productivity. Geocarto International 7, 63-69.
Rostampour, M., Jafari, M., Tavili, A., Azarnivand, H., Islami, S.V., 2017. Study of plant composition and diversity along the soil salinity gradient of the rangelands of Daq Petregan, South Khorasan. Journal of Desert Ecosystem Engineering 6(16), 11-24. (In Persian)
Safiallah, S., Jalili, S., 2013. Study of geography and vegetation and environmental threatening factors in Semnan province. National Conference on Environmental Research of Iran, November 30, Permanent Secretariat of the Conference. pp. 1-10. (In Persian)
Sanaeinejad, S. H., Astaraei, A., Mir Hosseini, P., Keshavarzi, A., 2008. Using Satellite Images for Vegetation Studies (Comparison of Different Vegetation Indicators - Case Study of Neishabour Region). 5th National Congress of Agricultural Machinery and Mechanization Engineering, 6 and 7 September, Iranian Agricultural Machinery and Mechanization Engineering Association. pp. 1-10. (In Persian)
Shahriari, H., Shariati, N., Muslimi, A., 2012. Presenting a Method for Stable Prediction of Time Series Using in Financial Problems Using Robust Method. Quarterly Journal of Financial Knowledge, Securities Analysis 5(3), 97-114. (In Persian)
Shokohizadegan, S., Khosravi, H., Azarnivand, H., Zehtabian, Gh. R., Rayegani, B., 2016. Evaluation and monitoring of vegetation based on fuzzy logic using satellite images (Case study: Bamoo-Shiraz National Park). Geographical Information Information Quarterly (Sepehr) 25(100), 157-166. (In Persian)
Tiwari, A., Jain, K., 2014. GIS Steering smart future for smart Indian cities. International Journal of Scientific and Research Publications 4, 442-446.
Yue, S., Pilon, P., Phinney, B., Cavadias, G., 2002. The influence of autocorrelation on the ability to detect trend in hydrological series. Hydrological processes 16, 1807-1829.
Zarei, A., Abedi, S., Mahmoudi, M., Peyravi Latif, Sh., 2016. Evaluation of hibernation habitat of Ursus arctos Syriacus using generalized linear modeling (GLM) and geographical weight regression (GWR) in southern Iran. Applied Ecology 4(14), 75-85. (In Persian)
)