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Smriti Thakur

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Proceedings Article | 26 October 2022 Presentation + Paper

Assessment of decadal land use land cover change using random forest classifier in Google Earth engine for Himachal Pradesh, India

Smriti Thakur , S. Samant, R. Singh

Proceedings Volume 12268, 122680V (2022) https://doi.org/10.1117/12.2636247

KEYWORDS: Agriculture, Image classification, Climate change, Snow cover, Vegetation, Reflectivity, Landsat, Earth observing sensors

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Himachal Pradesh is a state located in the Indian Himalayan Region, one of the world's biodiversity hotspots, which assures its biodiversity richness and its ecological sensitivity. Due to the rapid rate of development, this Himalayan state has recently experienced many land use changes. To better understand the dynamics of land cover, the study's main objectives are to define the key LULC classes and compute and assess the size and rate of change for these classes during a 20-year period (2000 to 2020). For the purpose of this study, we processed and classified images using the Google Earth Engine Platform. The Landsat surface reflectance data products were selected for the years 2000, 2010 and 2020. Thereafter, the median of image collections was derived to get the final image to be classified for the study area. The Random Forest classifier was used to classify the images into seven landcover classes, i.e., agriculture, forest, water, glacier, built-up, grassland, and barren. The results revealed that the total area covered by agriculture has declined over time (0.26%), while forests (1.04%) and built-up areas (0.48%) in the state have expanded from the year 2000 to 2020. The main reason for the reduction in agriculture area is decrease in agricultural activities, while afforestation and continuous infrastructural development have resulted in an increase in forest cover and built-up areas, respectively. The result of this study gives a comprehensive picture of land cover changes in the state, which could further assist policymakers in strategizing for the state’s long-term socioeconomic development.

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