Remote Sensing of ‘Ghost Villages’: The Challenge of Rural Migration in the Mountainous State of Uttarakhand, India

This study reviews rural migration in mountainous areas of Uttarakhand, its relations with climate change and provides a remote sensing based simple methodology for identifying depopulated villages. Declining rural depopulation and the phenomenon of abandoned villages known as ‘Ghost Villages’ are the major challenges in the Uttarakhand state of India. According to the India’s census from 2011, more than four million people which is about 40% of the population of Uttarakhand have migrated from the hilly state, due to which an increasing number of villages in Uttarakhand have become abandoned (Rural Development and migration commission, Uttarakhand, April 2018). Districts such as Pauri, Garhwal and Almora are facing negative population growth. A 2018 study conducted by the Uttarakhand Migration Commission found that 734 of the state's villages—often referred to as “ghost villages"—have been abandoned since 2011. Through reviewing how climate change affects mountainous regions, the research seeks to understand what environmental factors influence migration decisions of rural residents in Uttarakhand, India. Using census and remote sensing dataset, this research takes a multidisciplinary approach for identifying the abandoned farmland and hence the ghost villages in Uttarakhand. The aim is also to exploit satellite remote sensing to identify ghost villages within Uttarakhand. Remote sensing technology is recently being widely used for monitoring the abandoned croplands due to its long time series datasets and large spatial-scale observation. This study explores the potential of using time series analysis of the Normalized Difference Vegetation Index (NDVI) to determine the status of a specific village as either an active or abandoned farmland (indicator for ghost village). This research attempts to identify unique patterns and trends associated with ghost villages, which are defined by the absence of agricultural or human activity, through the systematic analysis of multi-temporal NDVI data. The technique to identify Ghost Villages through remote sensing shall be useful for urbanization and migration studies, land use and planning, policy development, as well as early warning system for hazards.