Kurdish Studies

ISSN: 2051-4883 | e-ISSN: 2051-4891
Email: editor@kurdishstudies.net

Geo-Sequential Analysis Of Juniper Forest Ziarat

Rabail Urooj
Wajeeha Alam
  Sadaf Aslam Ghori
Anila Bahadur
Keywords: Classification, Health, Juniperus cupressaceae, Machine Learning, Indices.


The state of Pakistan is showing immersive increase in population over the past few decades. Due to arid and semiarid climatic conditions the country is depriving in forested land. Juniper forest of Baluchistan province is one of few forest of province which contributed in forested land of country but unfortunately is listed in IUCN Red list. Juniper forest the aesthetic beauty and home for wild organisms is pushed backwards due to population growth, urbanization, deforestation, unemployment and climate change. The changes in the forest were monitored through emerging techniques. The present study evaluated the data of two decades from 1999-2009 and 2009-2018. 5 classes were identified in study area namely Water, Barren, Vegetation, Forest and Built up. The technique of Hybrid classification is used using Maximum Likelihood Algorithm. Various health indices like NDVI, MSI and SAVI were also calculated. The health indices result also supported classification data showing a regular decrease in forested land of Ziarat district. The accuracy for classified imageries for year 1999, 2009 and 2018 were 82%, 99% and 96% respectively, giving off the higher kappa values of 0.81%, 0.98% and 0.95% The findings of study indicated constant decrease in forested land and increase in vegetation and Built up class. Barren class was observed to be largest due to low rainfall. Climate change and human interruption are the main culprit in causing an irreversible damage to Juniper forest which if not combated could impose a huge threat in survival of Juniper forest Ziarat. Proper management and conservation strategies are necessary to be incorporated by Government to protect the natural asset.   

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