Land Use / Land Cover Change Detection and Forecasting using GEE and Hybrid Markov-CA Model in the Nainital District of Uttarakhand State, India

ABSTRACT

Analyzing and predicting changes in land use/ land cover (LU/LC) is a very essential study for decision makers to manage and control environmental sustainability by assessing the effects of global climate change. This study, aims to evaluate LULC changes in the last two decades from 2000 to 2020, as well as, to predict land cover changes in 2030 using Google Earth Engine and IDRISI software. Random Forest classification scheme in GEE is used for classifying land covers. Based upon 2000 and 2010 classified maps, the “transition prob-ability” matrix is determined by using IDRISI SILVA 17.0 software. The Markov-CA integrated method in IDRISI is used to predict 2020 LULC pattern and it is validated by actual LU/LC classified map of 2020 with a kappa index of 0.93. Finally, the LU/LC map of 2030 is predicted to analyze land cover changes for controlling and monitoring environment sustainability. Based on the results of the current analysis, Nainital, a district of Uttarakhand State, India has undergone a significant increase in urban area and agricultural area particularly in west and south direction (plain region of study area), whereas there is a sharp decrease in forest and waterbody area. In this aspect, Remote sensing (RS) methods and geographic information systems (GIS) are crucial tools that can be utilized to identify the driving elements linked with the surrounding environment that lead to altering climate and biodiversity loss.

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