Mendeley
TY  _  JOUR
ID  -  202008168634
TI  -  Investigation and prediction on Forests Covers Changes Using Fuzzy Object-Based Satellite Image Classification and CA-Markov (case study: City of Romeshkan)
JO  -  Journal of Environmental Research and Technology
JA  -  ES
LA  -  fa
SN  -  2676-3060
AU  -   
AU  -  Shehabi Hajar
AU  -  Akbari Ebrahim
AD  -  عضو هیات علمی دانشگاه حکیم سبزواری
AD  -  دانشگاه تبریز
AD  -  دانشگاه فردوسی
Y1  -  2020
PY  -  2020
VL  -  6
IS  -  4
SP  -  103
EP  -  114
KW  -  Forest cover
KW  -   Object-Based image classification
KW  -   CA-Markov
KW  -   Landsat
KW  -   Romeshkan
DO  -  
N2  -  Forest is a valuable heritage and one of the important factors in the ecosystem of each area that in addition to using and exploiting them, they should be preserved. Zagros’ forests, especially in Lorestan province due to negligence have been destroyed throughout past years. The aim of this research is to investigation, detect and modeling Romeshkan’s forests’ cover changes. To do this, first changes that were taken place between 1987-2017 were extracted by satellite Landsat images and using Fuzzy Object-Based classification method, then, were classified in 5 classes (Agriculture, Forest, Range, water and Residential). Finally, classification results show that there is a sharp decrease of forested areas (81.17 km2) and an increase of Range and Farmlands over past 30 years in the forest area. In a period of 1987-2002 forest cover of the study area had not faced major changes, but most of the rangelands turned to farmlands. While in the second period from 2002 onwards forest cover dramatically dipped and its area decreased from 122.58 km2 to 43.42 km2 in 2017, which the rate of forest covers decrement was around 79.16 km2. Moreover, in order to predict forest cover changes in the future CA-Markov model was applied that indicates 10.70% of current forest covers will be reduced in 2030, and the main changes will be occurred between forest classes to farmlands and rangelands classess by 6.901 and 9.172 km2, respectively. 
UR  - rimag.ir/en/Article/8634
L1  - rimag.ir/en/Article/Download/8634
ER  -  
