Arsanjani J J, Helbich M, Kainz W, et al. 2013. Integration of logistic regression, Markov chain and cellular automata models to simulate urban expansion. International Journal of Applied Earth Observation and Geoinformation, 21: 265–275.
Article
Google Scholar
Bacon J. 2016. The most polluted city is? Hint: It’s not in China. USA Today. [2016-12-19]. https://doi.org/www.usatoday.com/story/news/world/2016/12/19/most-polluted-city-is-not-in-china/95606914/#.
Google Scholar
Benedek C, Szirányi T. 2009. Change detection in optical aerial images by a multilayer conditional mixed Markov model. IEEE Transactions on Geoscience and Remote Sensing, 47(10): 3416–3430.
Article
Google Scholar
Bhatta B. 2010. Analysis of Urban Growth and Sprawl from Remote Sensing Data. Berlin: Springer-Verlag Berlin Heidelberg, 172.
Book
Google Scholar
Brémaud P. 2013. Markov Chains: Gibbs Fields, Monte Carlo Simulation, and Queues. New York: Springer Science & Business Media, 445.
Google Scholar
Clarke K C, Hoppen S, Gaydos L. 1997. A self-modifying cellular automaton model of historical urbanization in the San Francisco Bay area. Environment and Planning B, 24(2): 247–261.
Article
Google Scholar
Cooley T, Anderson G P, Felde G W, et al. 2002. FLAASH, a MODTRAN4-based atmospheric correction algorithm, its application and validation. In: IEEE, IEEE International Geoscience and Remote Sensing Symposium. Toronto: IEEE.
Book
Google Scholar
DeFries R S, Hansen M C, Townshend J R G, et al. 2000. A new global 1km dataset of percentage tree cover derived from remote sensing. Global Change Biology, 6(2): 247–254.
Article
Google Scholar
Eastman J R. 2012. IDRISI Selva. Worcester: Clark University, 354.
Google Scholar
El-Hallaq M A, Habboub M O. 2015. Using Cellular Automata-Markov Analysis and Multi Criteria Evaluation for Predicting the Shape of the Dead Sea. Advances in Remote Sensing, 4(1): 83.
Article
Google Scholar
Foley J A, DeFries R, Asner G P, et al. 2005. Global consequences of land use. Science, 309(5734): 570–574.
Article
Google Scholar
Foltz R C. 2002. Iran’s water crisis: cultural, political, and ethical dimensions. Journal of Agricultural & Environmental Ethics, 15(4): 357–380.
Article
Google Scholar
Hanin M, Ebel C, Ngom M, et al. 2016. New Insights on plant salt tolerance mechanisms and their potential use for breeding. Frontiers in Plant Science, 7.
Google Scholar
Herman J R, Bergen J R, Peleg S, et al. 2000. Method and apparatus for mosaic image construction: Google Patents. [2000-06-13]. https://doi.org/www.google.com/patents/US6075905.
Google Scholar
Houghton R A, Nassikas A A. 2017. Global and regional fluxes of carbon from land use and land cover change 1850–2015. Global Biogeochemical Cycles, 31(3): 456–470.
Article
Google Scholar
Hurskainen P, Pellikka P. 2004. Change detection of informal settlements using multi-temporal aerial photographs–the case of Voi, SE-Kenya. In: Proceedings of the 5th African Association of Remote Sensing of the Environment Conference, 18–2.
Google Scholar
October 2004. Nairobi: African Association of Remote Sensing of the Environment.
Google Scholar
Hyandye C, Martz L W. 2017. A Markovian and cellular automata land-use change predictive model of the Usangu Catchment. International Journal of Remote Sensing, 38(1): 64–81.
Article
Google Scholar
Jamil A, Riaz S, Ashraf M, et al. 2011. Gene expression profiling of plants under salt stress. Critical Reviews in Plant Sciences, 30(5): 435–458.
Article
Google Scholar
Kaufman Y J, Wald A E, Remer L A, et al. 1997. The MODIS 2.1-/spl mu/m channel-correlation with visible reflectance for use in remote sensing of aerosol. IEEE Transactions on Geoscience and Remote Sensing, 35(5): 1286–1298.
Article
Google Scholar
Kim D-H, Sexton J O, Noojipady P, et al. 2014. Global, Landsat-based forest-cover change from 1990 to 2000. Remote Sensing of Environment, 155: 178–193.
Article
Google Scholar
Lambin E F, Geist H J. 2008. Land-Use and Land-Cover Change: Local Processes and Global Impacts. Berlin: Springer Science & Business Media, 221.
Google Scholar
Lillesand T, Kiefer R W, Chipman J. 2014. Remote Sensing and Image Interpretation. New York: John Wiley & Sons, 721.
Google Scholar
Lin Z, Zhou D, Liu L. 2006. Regional-Scale Assessment and Simulation of Land Salinization Using Cellular Automata-Markov Model. In: ASABE/CSBE North Central Intersectional Meeting. Michigan: American Society of Agricultural and Biological Engineers, RRV12110.
Google Scholar
Lunetta R S, Lyon J G. 2004. Remote sensing and GIS accuracy assessment. Florida: CRC Press, 394.
Book
Google Scholar
Mahiny A S, Clarke K C. 2012. Guiding SLEUTH land-use/land-cover change modeling using multicriteria evaluation: towards dynamic sustainable land-use planning. Environment and Planning B, 39(5): 925–944.
Article
Google Scholar
McDowell N G, Coops N C, Beck P S, et al. 2015. Global satellite monitoring of climate-induced vegetation disturbances. Trends in Plant Science, 20(2): 114–123.
Article
Google Scholar
McGarigal K, Marks B J. 1995. FRAGSTATS: spatial pattern analysis program for quantifying landscape structure. General Technical Report. PNW-GTR-351. Portland, USA.
Book
Google Scholar
Metternicht G I., Zinck J A. 2003. Remote sensing of soil salinity: potentials and constraints. Remote Sensing of Environment, 85(1): 1–20.
Article
Google Scholar
Meyfroidt P, Lambin E F, Erb K-H, et al. 2013. Globalization of land use: distant drivers of land change and geographic displacement of land use. Current Opinion in Environmental Sustainability, 5(5): 438–444.
Article
Google Scholar
Module F. 2009. Atmospheric Correction Module: QUAC and FLAASH User’s Guide (ver. 4). Boulder: Harris Geospatial Co., 44.
Google Scholar
Moradi H. 2016. Identification of Environmental Resources and Spatial zoning of Makran Coastal Area, Southeastern Iran. In: Landuse & Land Cover Change Report (1st ed.). Department of Environment, Iran.
Google Scholar
Mountrakis G, Im J, Ogole C. 2011. Support vector machines in remote sensing: A review. ISPRS Journal of Photogrammetry and Remote Sensing, 66(3): 247–259.
Article
Google Scholar
Palmate S S, Pandey A, Mishra S K. 2017. Modelling spatiotemporal land dynamics for a trans-boundary river basin using integrated Cellular Automata and Markov Chain approach. Applied Geography, 82: 11–23.
Article
Google Scholar
Pontius R G, Schneider L C. 2001. Land-cover change model validation by an ROC method for the Ipswich watershed, Massachusetts, USA. Agriculture, Ecosystems & Environment, 85(1–3): 239–248.
Article
Google Scholar
Roy D P, Wulder M A, Loveland T R, et al. 2014. Landsat-8: Science and product vision for terrestrial global change research. Remote Sensing of Environment, 145: 154–172.
Article
Google Scholar
Rozema J, Flowers T. 2008. Crops for a salinized world. Science, 322(5907): 1478–1480.
Article
Google Scholar
Saaty T L. 2008. Decision making with the analytic hierarchy process. International Journal of Services Sciences, 1(1): 83–98.
Article
Google Scholar
Shahbaz M, Ashraf M. 2013. Improving salinity tolerance in cereals. Critical Reviews in Plant Sciences, 32(4): 237–249.
Article
Google Scholar
Shalaby A, Tateishi R. 2007. Remote sensing and GIS for mapping and monitoring land cover and land-use changes in the Northwestern coastal zone of Egypt. Applied Geography, 27(1): 28–41.
Article
Google Scholar
Shrivastava P, Kumar R. 2015. Soil salinity: A serious environmental issue and plant growth promoting bacteria as one of the tools for its alleviation. Saudi Journal of Biological Sciences, 22(2): 123–131.
Article
Google Scholar
Thenkabail P S, Biradar C M, Noojipady P, et al. 2009. Global irrigated area map (GIAM), derived from remote sensing, for the end of the last millennium. International Journal of Remote Sensing, 30(14): 3679–3733.
Article
Google Scholar
Tutorial E-Z. 2010. ENVI user guide. Colorado Springs, CO: ITT, 590.
Google Scholar
Wu K Y, Ye X Y, Qi Z F, et al. 2013. Impacts of land use/land cover change and socioeconomic development on regional ecosystem services: The case of fast-growing Hangzhou metropolitan area, China. Cities, 31: 276–284.
Article
Google Scholar
Wu W, Mhaimeed A S, Al-Shafie W M, et al. 2014. Mapping soil salinity changes using remote sensing in Central Iraq. Geoderma Regional, 2–3: 21–31.
Article
Google Scholar
Xu J, Grumbine R E. 2014. Building ecosystem resilience for climate change adaptation in the Asian highlands. Wiley Interdisciplinary Reviews: Climate Change, 5(6): 709–718.
Google Scholar
Zahed M A, Rouhani F, Mohajeri S, et al. 2010. An overview of Iranian mangrove ecosystems, northern part of the Persian Gulf and Oman Sea. Acta Ecologica Sinica, 30(4): 240–244.
Article
Google Scholar
Zhou D, Lin Z, Liu L. 2012. Regional land salinization assessment and simulation through cellular automaton-Markov modeling and spatial pattern analysis. Science of the Total Environment, 439: 260–274.
Article
Google Scholar
Zhu Z, Woodcock C E, Holden C, et al. 2015. Generating synthetic Landsat images based on all available Landsat data: Predicting Landsat surface reflectance at any given time. Remote Sensing of Environment, 162: 67–83.
Article
Google Scholar