Enhanced mangrove index: A spectral index for discrimination understorey, nypa, and mangrove trees.

Unsupervised classification using vegetation indices has been extensively employed to map mangrove forests using medium-resolution satellite images. However, its capability is restricted to determining the extent of mangroves only. This study introduces a new spectral index called the enhanced mangrove index (EMI) for accurately mapping different components of mangrove vegetation, including mangrove trees, nypa, and understorey. An immediate effort is required to monitor the invasion of nypa and understorey in the mangrove forest of Segara Anakan Lagoon, located in Central Java, Indonesia. This issue may also be prevalent in other mangrove areas worldwide. The development of EMI involved: 1). the analysis of the reflectance exhibited by different types of mangrove vegetation, and 2). The performance of EMI was evaluated by comparing it with spectral indices such as automated mangrove map and index (AMMI), as well as supervised classification models like random forest (RF). The accuracy assessment indicates that the overall accuracy and Kappa coefficient achieved values of 0.87 and 0.84, respectively, surpassing other spectral indices and supervised classification models. AMMI and RF exhibited high overall accuracy, with values of 0.82 and 0.73, respectively. Additionally, they demonstrated a Kappa coefficient of 0.77 and 0.66, respectively.

Population of the Javan Gibbon (Hylobatesmoloch) in the Dieng Mountains, Indonesia: An updated estimation from a new approach.

The Javan gibbon (Hylobatesmoloch) is endemic to the island of Java and its distribution is restricted from the western tip of Java to the Dieng Mountains in Central Java. Unlike the other known habitats that hold a large population of Javan gibbons, the Dieng Mountains have not been protected and experience various threats. This study, which was conducted in 2018 and 2021, aimed to provide an update of the current density and population size of Javan gibbons in Dieng after the most recent study in 2010 and to investigate their relationships with habitat characteristics (vegetation and elevation). The triangulation method and a new acoustic spatial capture-recapture method were used to estimate group density. A new approach for extrapolation, based on the habitat suitability model, was also developed to calculate population size. The results show that the Javan gibbon population in the Dieng Mountains has most likely increased. The mean group density in each habitat type was high: 2.15 groups/km2 in the low suitable habitat and 5.55 groups/km2 in the high suitable habitat. The mean group size (3.95 groups/km2, n = 20) was higher than those reported in previous studies. The overall population size was estimated to be 1092 gibbons. This population increase might indicate the success of conservation efforts during the last decade. However, more effort should be made to ensure the long-term future of this threatened species. Although the density significantly differed between habitat suitability types, it was not influenced by the vegetation structure or elevation. A combination of multiple variables will probably have a greater effect on density variation.