Assessing Pine Forest Restoration Post-Fire Using NDVI and GIS Technologies

2023

Full text Open access: Hybrid Metadata (CSL-JSON)
DOI 10.18280/ijdne.180620
Data confidence 70 medium
How this score is calculated

It is built from checkable properties of the record itself: whether the article has a DOI, how many independent sources confirmed its data, whether the required fields are filled in, and how recent the latest confirmation is. Disagreement between sources and a missing identifier lower it. A value of 80 or above means the record was published without further checking; 60 to 79 means it is published at reduced confidence, with a manual check advisable. A record verified by an editor by hand is never pushed below 90 by a recalculation. This scores our data about the article, not the article itself.

Abstract

This study addresses the pressing and pertinent issue of establishing a space-based monitoring system to track forest condition changes.Utilizing geographic information system technologies and the Normalized Difference Vegetation Index (NDVI), it examines the evolution and dynamics of pine forest regeneration in the Semey Ormany State Forest Natural Reserve (Zhanasemey branch), Kazakhstan.Landsat-5 satellite data were employed to map and identify terrestrial vegetation changes within the Zhanasemey branch.Satellite imagery for June 2007 and September 2008 were specifically utilized for this investigation.Post-acquisition, the satellite images were subjected to corrections, followed by radiometric adjustments to minimize atmospheric interference.Subsequently, NDVI classifications, an established method for plant classification, were applied to each image.The study focused on a 15-year timespan (2008 to 2022) to monitor changes in vegetation intensity, classified according to NDVI, and to track the reforestation process in areas affected by fire.Analysis of the regeneration of the pine forest post the 2008 fire, conducted at five-year intervals, revealed an increase in the restored forest area from 6,773.49ha in 2013 to 10,721.07 ha in 2018, and finally to 14,742.54ha in 2022.In 2008, the fire-impacted area with reduced vegetation spanned 7,015.41ha, while by 2022, the restored area encompassed 14,742.54ha, indicating a significant enhancement in the pine forest restoration process.The findings underscore the critical role of remote sensing in forest fire modelling and identifying areas at risk, suggesting its potential utility in large-scale monitoring and management efforts.The study demonstrates the feasibility and efficiency of using space-based technologies to monitor long-term changes in forest conditions and to track reforestation dynamics in fire-affected regions.