Using Support Vector Machine To Identify Land Cover Change During Covid-19 Pandemic In Komodo National Park, Indonesia

A significant increase of 31.86% in vegetation area was observed in Komodo National Park between 2019 and 2020, attributed to reduced tourist activity during the COVID-19 pandemic. This finding highlights the unintended environmental benefits of tourism restrictions on a UNESCO World Heritage Site. The study employed Support Vector Machine (SVM) classification on high-resolution satellite imagery (Google Earth Pro, 1920 x 1280 pixels) from six key tourist destinations, pre-processed with radiometric calibration and atmospheric correction. Otsu’s thresholding quantified vegetation changes across five land cover classes: soil, vegetation, built-up areas, deep water, and shallow water. The research demonstrates the potential for tourism policies to influence ecological recovery in protected areas.

Golok Jaya, L. M., Saputra, R. A., & Idrus, S. H. (2022). Using Support Vector Machine To Identify Land Cover Change During Covid-19 Pandemic In Komodo National Park, Indonesia. Geography, Environment, Sustainability, 15(3), 70–79. https://doi.org/10.24057/2071-9388-2022-030