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Mapping Leaf Area Index of restored mangroves using WorldView-2 imagery in Perancak Estuary, Bali, Indonesia

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Abstract There have been efforts to restore and rehabilitate mangrove forests to compensate for their loss or degradation. Approaches for monitoring these efforts are increasingly developed, including assessment of the… Click to show full abstract

Abstract There have been efforts to restore and rehabilitate mangrove forests to compensate for their loss or degradation. Approaches for monitoring these efforts are increasingly developed, including assessment of the dynamic changes in restored mangroves using the biophysical tree parameter called Leaf Area Index (LAI). This study aimed to (1) apply a semi-empirical approach to estimate LAI using WorldView-2 imagery, (2) compare the LAI distributions of three different mangrove forest types (natural, mixed, and planted) at the mangrove restoration site in Perancak Estuary, Bali, Indonesia, and (3) evaluate the applicability of LAI as an indicator for monitoring mangrove growth in restoration areas. To achieve these objectives, a high-spatial-resolution WorldView-2 image data (2 m pixel size) and Normalized Difference Vegetation Index (NDVI) were used. A semi-empirical approach was used to correlate field LAI and NDVI values at the corresponding location. The results showed that the best regression function between the two variables was the third-order polynomial (R2 = 0.98). Overall, the estimated LAI values ranged from 0 to 9.56 (mean = 1.87, σ = 0.95, max. Accuracy = 97.6%) and differed between the three mangrove forest types. The comparison revealed that high LAI was associated with planted mangrove forest type where Rhizophora sp. dominated. It indicates that LAI is a useful indicator for assessing mangrove biophysical conditions and, as such, can be used for monitoring mangrove restoration activities and outcomes.

Keywords: index; area index; leaf area; mangroves using; restored mangroves; lai

Journal Title: Remote Sensing Applications: Society and Environment
Year Published: 2021

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