Deha Agus Umarhadi Wahyu Wardhana Senawi Emma Soraya


Social forestry schemes are now being implemented in numerous state forest areas in Indonesia, aiming to reduce deforestation and improve the community’s livelihood. However, spatial monitoring in the social forestry area is still limited to see how the implementation progresses. The present study aimed to identify the change of forest taking a case in Pati Forest Farmer Communities (KTH Pati) social forestry area from 1996 to 2022 using the LandTrendr algorithm based on Normalized Burn Ratio (NBR) value of Landsat image series. The results detected forest loss and gain covering an area of 453.97 ha and 494.18 ha, respectively. Two main reasons causing the forest loss are the country’s financial and political situation from 1997 to 2003 and the harvest of forest plantations in 2017–2018. However, it was found that the study area had a positive forest gain with the current continuous growth of 292.32 ha (20.16% of the total area). Even though the social forestry policy has not significantly shown a positive impact on forest growth, spatial monitoring through remote sensing can be a great tool for observing the progress.




Forest change, NBR, Remote sensing, Satellite imagery, Spectral trajectory

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Monitoring forest gain and loss based on LandTrendr algorithm and Landsat images in KTH Pati social forestry area, Indonesia. (2023). Journal of Applied and Natural Science, 15(3), 1051-1060. https://doi.org/10.31018/jans.v15i3.4781
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Monitoring forest gain and loss based on LandTrendr algorithm and Landsat images in KTH Pati social forestry area, Indonesia. (2023). Journal of Applied and Natural Science, 15(3), 1051-1060. https://doi.org/10.31018/jans.v15i3.4781