Deforestation in the Special Nature Reserve Gornje Podunavlje: Insights from PlanetScope, Sentinel-2 and Landsat-8 remote sensing data

Deforestation is a pressing environmental issue, and assessing forest loss with precision is crucial for effective conservation strategies. This study evaluates forest area loss in the Special Nature Reserve "Gornje Podunavlje" over a seven-year period from July 2017 to July 2024. Utilizing remote sensing data from PlanetScope, Sentinel-2, and Landsat-8 satellites, the study employs the XGBoost machine learning classifier to classify forest cover. Results indicate a consistent decline in forest area across all datasets, with reductions from approximately 43 km² in July 2017 to around 33 km² by July 2024. Despite variations in reported forest area due to differences in spatial resolution-PlanetScope (3 meters), Sentinel-2 (10 meters), and Landsat-8 (30 meters)-the overall trend of forest loss is evident. Landsat-8 consistently reported higher forest area compared to PlanetScope and Sentinel-2, attributed to its coarser resolution which may include more edge effects. The high-resolution PlanetScope data allowed for more precise delineation of forest boundaries, enhancing the accuracy of forest cover assessments.

Authors

Publication Details

Journal
Tehnika
Published
2025-01-01
DOI
https://doi.org/10.5937/tehnika2503263n
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
0.00
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article

Deforestation in the Special Nature Reserve Gornje Podunavlje: Insights from PlanetScope, Sentinel-2 and Landsat-8 remote sensing data

Ratko Nikolić
Tehnika
Remote Sensing in Agriculture
article

Deforestation in the Special Nature Reserve Gornje Podunavlje: Insights from PlanetScope, Sentinel-2 and Landsat-8 remote sensing data

Ratko Nikolić
article en

Abstract

Deforestation is a pressing environmental issue, and assessing forest loss with precision is crucial for effective conservation strategies. This study evaluates forest area loss in the Special Nature Reserve "Gornje Podunavlje" over a seven-year period from July 2017 to July 2024. Utilizing remote sensing data from PlanetScope, Sentinel-2, and Landsat-8 satellites, the study employs the XGBoost machine learning classifier to classify forest cover. Results indicate a consistent decline in forest area across all datasets, with reductions from approximately 43 km² in July 2017 to around 33 km² by July 2024. Despite variations in reported forest area due to differences in spatial resolution-PlanetScope (3 meters), Sentinel-2 (10 meters), and Landsat-8 (30 meters)-the overall trend of forest loss is evident. Landsat-8 consistently reported higher forest area compared to PlanetScope and Sentinel-2, attributed to its coarser resolution which may include more edge effects. The high-resolution PlanetScope data allowed for more precise delineation of forest boundaries, enhancing the accuracy of forest cover assessments.

TehnikaVol. 80(3)
Openalex Percentile: Top 86%
Remote Sensing in Agriculture
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Deforestation in the Special Nature Reserve Gornje Podunavlje: Insights from PlanetScope, Sentinel-2 and Landsat-8 remote sensing data — Ratko Nikolić · Tehnika (2025) | TGRS Research Map | TGRS