Enhancing Forest Landscape Spatial Data Modeling through Cloud-Based Approaches: A Case of Oluwa Forest Reserve, Ondo State, Nigeria

Abstract

The term "cloud computing" refers to Internet-based computing where virtual shared servers offer users software, infrastructure, platform, devices, and other resources on a pay-per-use basis. Remote sensing for the management of environmental resources can use cloud computing. Using cloud-based spatial data, this study will assess changes to the forest landscape in the Oluwa forest reserve. In this study, the reserve's existing and future forest cover is modelled utilising cloud data and cloud computing. This study shows how cloud computing may be used to detect different types of forest landscapes in Oluwa Forest Reserve based on projected future land cover patterns and simulated land cover utilising spatial data. The traditional approach to calculating forest cover is laborious and time-consuming. Using Google Earth and the cloud computing technology, it is possible to identify changes in forest cover more quickly and with less effort. According to the findings, forest land looked to have decreased between 1992 and 2022, with a larger rate of change between 2002 and 2012. The secondary forest increased with time as well, changing at a faster rate between 2002 and 2012 (approximately 6.5% growth) than between 2012 and 2022 (about 1.8% reduction). Between 1992 and 2022, non-forest land increased overall. Between 2002 and 2012, the non-forested area grew by 1.48%, while the 10-year period saw a 3.93% rise.
Keywords: Degradation, Cloud Computing, Modeling, Classification, Fragstats