land use /cover change monitoring and prediction using markov chain (case study: the abbas plain)

Authors

کامران کریمی

دانشجوی دکتری بیابان زدایی، دانشگاه کشاورزی و منابع طبیعی گرگان، ایران غلامرضا زهتابیان

استاد دانشکده منابع طبیعی، دانشگاه تهران، ایران مرزبان فرامرزی

استادیار گروه مرتع و آبخیزداری، دانشگاه ایلام، ایران حسن خسروی

استادیار دانشکده منابع طبیعی، دانشگاه تهران، ایران

abstract

remote sensing is a key technology for assessing expansion and rate of land cover changes that awareness of these changes as the basic information has a special importance for various programs. in this study, land use changes were examined over the past 24 years, and the feasibility of predicting it in the future was evaluated by using the markov chain model of the abbas plain. landsat tm, etm+, and oli satellite images for the years 1968, 2003 and 2013, respectively; along with topographic and vegetation maps of the study region were used in this research. the images for three periods were classified into five land-use classes of rangeland, agricultural land (irrigated and rain-fed)), residential land, riverbed and barren and hilly land. according to the results, agricultural land is the most dynamic land-use class in the study area and its area has followed an upward trend during the period 1968 – 2003, so that 4337 ha (7.12%) has been added to this land-use class during this period. the trend of rangeland use change has had a descending trend during the period 1968 – 2003, so that has caused its area to be decreased by 3.19% (6573.6 ha) during this period. the results obtained from markov chain analysis in the period 1968-2003, for model calibration; the maps for the years 1968 and 2003, and its matrix for predicating land use changes of the year 2023 indicate the kappa coefficient equal to 80 percent. based on the obtained results, in the year 2023, 49.1 and 10.1 percent of the study region are comprised of agricultural land and rangeland, respectively.

Upgrade to premium to download articles

Sign up to access the full text

Already have an account?login

similar resources

Detection and prediction of land use/ land cover changes using Markov chain model and Cellular Automata (CA-Markov), (Case study: Darab plain)

unprincipled changes in land use are major challenges for many countries and different regions of the world, which in turn have devastating effects on natural resources, Therefore, the study of land-use changes has a fundamental and important role for environmental studies. The purpose of this study is to detect and predicting of land use/ land cover (LULC) changes in Darab plain through the Ma...

full text

Prediction of Land Use Change and its Hydrological Effects Using Markov Chain Model and SWAT Model

Access to current and future water resources is one of the concerned problems for managers and policymakers around the world. Because of the communication between water resources and land use, these two topics had come together in different researches. Scenarios designed in regional land planning provide the basis for analyzing the existing opportunities and making the right decisions for manag...

full text

Simulation and prediction of land use and land cover change using GIS, remote sensing and CA-Markov model

This study analyzes the characteristics of land use/land cover change in Jordan’s Irbid governorate, 1984–2018, and predicts future land use/land cover for 2030 and 2050 using a cellular automata-Markov model. The results inform planners and decision makers of past and current spatial dynamics of land use/land cover change and predicted urban expansion, for a better understanding and successful...

full text

land use/cover change detection in 2025 with ca-markov chain model (case study: esfarayen)

modeling and prediction of land use/cover changes is an essential need for planning sustainable use of land in country like iran with its high level of changes in land uses and land covers. this study aimed to analyze the capability of ca markov prediction model and landsat satellite images for land use/cover change detection within the framework of “iran at 1404 prospective” in esfarayen r...

full text

The Impact of Land Use/Land Cover Changes on Groundwater Resources Using Remote Sensing & GIS (Case Study: Khan-Mirza Plain)

Hydrological status and water table fluctuations are directly related to land use and/or land cover (LULC) changes in each area. In this research, the impact of LULC changes on groundwater quantity and quality of Khan-Mirza Plain, in the northern Karun watersheds, was investigated. For this purpose, Landsat 5, 7 and 8 satellite images and ETM and OLI sensors were employed to prepare the L...

full text

My Resources

Save resource for easier access later


Journal title:
مرتع و آبخیزداری

جلد ۶۹، شماره ۳، صفحات ۷۱۱-۷۲۴

Keywords
[ ' r e m o t e s e n s i n g i s a k e y t e c h n o l o g y f o r a s s e s s i n g e x p a n s i o n a n d r a t e o f l a n d c o v e r c h a n g e s t h a t a w a r e n e s s o f t h e s e c h a n g e s a s t h e b a s i c i n f o r m a t i o n h a s a s p e c i a l i m p o r t a n c e f o r v a r i o u s p r o g r a m s . r n i n t h i s s t u d y ' , ' l a n d u s e c h a n g e s w e r e e x a m i n e d o v e r t h e p a s t 2 4 y e a r s ' , ' a n d t h e f e a s i b i l i t y o f p r e d i c t i n g i t i n t h e f u t u r e w a s e v a l u a t e d b y u s i n g t h e m a r k o v c h a i n m o d e l o f t h e a b b a s p l a i n . l a n d s a t t m ' , ' e t m + ' , ' a n d o l i s a t e l l i t e i m a g e s f o r t h e y e a r s 1 9 6 8 ' , ' 2 0 0 3 a n d 2 0 1 3 ' , ' r e s p e c t i v e l y ; a l o n g w i t h t o p o g r a p h i c a n d v e g e t a t i o n m a p s o f t h e s t u d y r e g i o n w e r e u s e d i n t h i s r e s e a r c h . t h e i m a g e s f o r t h r e e p e r i o d s w e r e c l a s s i f i e d i n t o f i v e l a n d ' , ' u s e c l a s s e s o f r a n g e l a n d ' , ' a g r i c u l t u r a l l a n d ( i r r i g a t e d a n d r a i n ' , ' f e d ) ) ' , ' r e s i d e n t i a l l a n d ' , ' r i v e r b e d a n d b a r r e n a n d h i l l y l a n d . a c c o r d i n g t o t h e r e s u l t s ' , ' a g r i c u l t u r a l l a n d i s t h e m o s t d y n a m i c l a n d ' , ' u s e c l a s s i n t h e s t u d y a r e a a n d i t s a r e a h a s f o l l o w e d a n u p w a r d t r e n d d u r i n g t h e p e r i o d 1 9 6 8 2 0 0 3 ' , ' s o t h a t 4 3 3 7 h a ( 7 . 1 2 % ) h a s b e e n a d d e d t o t h i s l a n d ' , ' u s e c l a s s d u r i n g t h i s p e r i o d . t h e t r e n d o f r a n g e l a n d u s e c h a n g e h a s h a d a d e s c e n d i n g t r e n d d u r i n g t h e p e r i o d 1 9 6 8 2 0 0 3 ' , ' s o t h a t h a s c a u s e d i t s a r e a t o b e d e c r e a s e d b y 3 . 1 9 % ( 6 5 7 3 . 6 h a ) d u r i n g t h i s p e r i o d . t h e r e s u l t s o b t a i n e d f r o m m a r k o v c h a i n a n a l y s i s i n t h e p e r i o d 1 9 6 8 ' , 2 0 0 3 , ' f o r m o d e l c a l i b r a t i o n ; t h e m a p s f o r t h e y e a r s 1 9 6 8 a n d 2 0 0 3 ' , ' a n d i t s m a t r i x f o r p r e d i c a t i n g l a n d u s e c h a n g e s o f t h e y e a r 2 0 2 3 i n d i c a t e t h e k a p p a c o e f f i c i e n t e q u a l t o 8 0 p e r c e n t . b a s e d o n t h e o b t a i n e d r e s u l t s ' , ' i n t h e y e a r 2 0 2 3 ' , ' 4 9 . 1 a n d 1 0 . 1 p e r c e n t o f t h e s t u d y r e g i o n a r e c o m p r i s e d o f a g r i c u l t u r a l l a n d a n d r a n g e l a n d ' , ' r e s p e c t i v e l y . ' ]

Hosted on Doprax cloud platform doprax.com

copyright © 2015-2023