List of Articles Forest cover

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  1 - Investigation of forest land use degradation due to dam construction using satellite images processing
  mandana azizi Mohammad panahandeh
  10.29252/.5.8.37
  20.1001.1.26763060.1399.5.8.9.9
  Identify land uses and land use changes to investigate and monitor sensitive areas is essential for sustainable land planning and management. The main objective of this study is to investigate the land use changes caused by the construction of Shafarood Dam in the Hyrca More

  Identify land uses and land use changes to investigate and monitor sensitive areas is essential for sustainable land planning and management. The main objective of this study is to investigate the land use changes caused by the construction of Shafarood Dam in the Hyrcanian forests in the north of Iran during a 17-year period using Landsat satellite imagery. To do this, three satellite imagery of the years 2000, 2013 and 2017 were used, and the corrections (geometric and atmospheric) were applied on the images and the map of the land use for each section in the region was prepared using the classification method of the maximum likelihood that the produced map have Kappa coefficient more than 86% and usage accuracy of 0.83. After classification, the comparison method was used to monitor the land use changes. The results revealed that in every three years, the most land cover of Shafarood watershed belongs to the forest class and in the next rank belongs to the rangeland class. As a result, the continuous decline of the forest class accured from 63.05 percent to 57.27 and 57.22 percent in the first section for the years 2013 and 2017 respectively. The continuous increase of the rock class (8.15-9.10-10.45) and bare lands (3.5- 4.47-5.08%) confirms it in the study area. Environmental challenges of constructing the Shafaroud dam is another emphasis on the importance of conducting advanced and specialized studies based on ecological methodologies and also increasing the decision makers awareness of Hyrcanian forests complexity which has formed in a very long-time period. Manuscript profile
• Open Access Article
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  2 - Investigation and prediction on Forests Covers Changes Using Fuzzy Object-Based Satellite Image Classification and CA-Markov (case study: City of Romeshkan)
  Rahman Zandi Hajar Shehabi Ebrahim Akbari
  10.29252/.4.6.103
  20.1001.1.26763060.1398.4.6.12.1
  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 y More

  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. Manuscript profile