Monitoring Forest Cover Dynamics Using Orthophotos and Satellite Imagery

Abstract

The assessment of changes in forest coverage is crucial for managing protected forest areas, particularly in the face of climate change. This study monitored forest cover dynamics in a 6535 ha mountain area located in north-west Romania as part of the Apuseni Natural Park from 2003 to 2019. Two approaches were used: vectorization from orthophotos and Google Earth images (in 2003, 2005, 2009, 2012, 2014, 2016, 2017, and 2019) and satellite imagery (Landsat 5 TM, 7 ETM, and 8 OLI) pre-processed to Surface Reflectance (SR) format from the same years. We employed four standard classifiers: Support Vector Machine (SVM), Random Forest (RF), Maximum Likelihood Classification (MLC), Spectral Angle Mapper (SAM), and three combined methods: Linear Spectral Unmixing (LSU) with Natural Breaks (NB), Otsu Method (OM) and SVM, to extract and classify forest areas. Our study had two objectives: 1) to accurately assess changes in forest cover over a 17-year period and 2) to determine the most efficient methods for extracting and classifying forest areas. We validated the results using performance metrics that quantify both thematic and spatial accuracy. Our results indicate a 9% loss of forest cover in the study area, representing 577 ha with an average decrease ratio of 33.9 ha/year−1. Of all the methods used, SVM produced the best results (with an average score of 88% for Overall Quality (OQ)), followed by RF (with a mean value of 86% for OQ).

Advancements in remote sensing tools for forestry analysis

“…The fusion of optical and radar data offers significant advantages for improved forest characterization and monitoring. By integrating the complementary information from these two data sources, a more comprehensive understanding of forest structure, biomass, and dynamics can be achieved [19] . Here are the key benefits of fusing optical and radar data for forest characterization and monitoring: a) Improved forest structure estimation: Optical data, such as multispectral or hyperspectral imagery, provide high-resolution spatial information about vegetation characteristics, including leaf area index (LAI), canopy height, and vegetation indices.…”

Market segmentation and consumer motivations in protected natural parks: A study from Spain

“…Similarly, it is important that natural landscapes are protected within national parks [ 6 ]. It is also important to take into account the reduction in forest cover, which is the area of land covered by forests [ 7 ].…”

The Biocultural Resilience Index (BRI): A New Tool for Assessing the Sustainability of Multifunctional Landscapes

“…Remote sensing is a useful tool in monitoring changes [62], having a high accuracy in their quantitative and spatial analysis [62,63]. The availability of Landsat satellite images represents an opportunity for estimating the dynamics of forest surfaces [64][65][66][67]. They are considered one of the most popular tools used for highlighting the changes of forest canopy [68,69,70], a fact also highlighted by the low costs of assessing these changes [44].…”