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Submitted
May 20, 2025
Accepted
June 30, 2025
Published
June 30, 2025
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Abstract

Ibu Kota Nusantara will be a significant smart sustainable forest city regarding climate change. Calculation of land-based carbon emission reduction performance in the IKN based on land cover maps through visual interpretation of medium-resolution satellite imagery sensing experiences uncertainty that follows a gradual process. In estimating emissions in this IKN, it is related to the uncertainty of land-based carbon emission activity data. This study aims to obtain the value of uncertainty in activity data from the dynamics of land cover changes in the IKN. The methodology used in this study is the interpretation of medium-resolution satellite imagery, and land cover changes using 5 (five) classes of change, namely deforestation, forest degradation, forest gain, stable forest, and stable non-forest, sampling design using stratified random sampling with the proportional allocation method. The results of the sample interpretation are then calculated for accuracy (user's accuracy, producer's accuracy, and overall accuracy) and uncertainty with a confusion matrix/error matrix. This study shows that changes in deforestation land cover produce high uncertainty values ​​(> 15%), this is because most of the samples for changes in deforestation land cover are in stable non-forest land cover changes, in actual the reference data from image data with high-resolution imagery does not match. While changes in stable forest and stable non-forest land cover throughout the year produce low uncertainty values ​​(≤15%), most of the samples for stable forest and stable non-forest land cover change conditions match in the diagonal column which shows that there is a match between the data class of land cover change classification results and reference data from high-resolution image data.

Keywords

Acacia, Carbon stock, Climate change, Forest.

Article Details

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