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The Oceanographic Research Centre at the National Research and Innovation Agency (BRIN) has launched the MonMang application. This second-generation smartphone-based software is designed to facilitate the monitoring of mangrove forest conditions, including their health.
MonMang is the world’s first application created to monitor mangroves. Monitoring mangroves is essential to observe degradation or the potential spread of degradation in a particular area. The results of mangrove monitoring can be used to formulate policies to address mangrove-related issues.
I Wayan Eka Dharmawan, a researcher at the Oceanographic Research Centre of BRIN, addressed, “MonMang operates by using artificial intelligence (AI), specifically Automated Mangrove Species Identification (AMSI). MonMang can also detect potential restoration areas.”
To cater to a broad spectrum of users, MonMang is not restricted solely to researchers; it is also accessible to the general public with an interest in mangrove preservation and scientific endeavours. MonMang v2.0 aims to aid research, facilitate monitoring, and promote public education. Wayan Eka initiated the development of MonMang in response to the fragmented nature of mangrove forest research across different institutions, which involved segregated data storage.
“However, one issue to consider is that different institutions use different methods. As a result, the data generated cannot be compared with one another,” Wayan Eka emphasised.
Furthermore, Wayan Eka explained the need for the same standards for monitoring mangrove forests. From this issue, there is a need for a platform to integrate mangrove monitoring. The MonMang application can be used by local communities and scientists who wish to monitor mangroves.
“In this application, we have a learning centre so that people can learn about mangroves there. We also provide digital guidebooks. Next is real-time data processing; simply use the application, and MonMang will ask for the required parameters,” Wayan Eka explained.
Since 2014, MonMang has been continuously developed, and it has reached its third version. Data updates are carried out with each performance, and in the third version, a mangrove database was established.
Regarding the observation process, Wayan Eka mentioned that mangrove changes are assessed based on their quality and in terms of changes in area. It needs to analyse changes in size, extent, and over time for observations. Indonesia, especially at the Oceanographic Research Centre, has published and introduced the Mangrove Health Index (MHI). MHI is one of the measures to assess mangrove quality.
Furthermore, Wayan Eka explained that they only identified three truly significant parameters for MHI. These parameters are density, coverage, and diameter size. Wayan Eka added that remote sensing analysis can be used for area observations, but assessing quality is somewhat challenging. “In Indonesia, mangroves are not only found in urban areas but also in remote areas. So, we need to adapt to the local communities who want to contribute to mangrove monitoring,” emphasised him.
The objective behind the development of this application is to enhance the efficiency of monitoring procedures. Wayan Eka expressed the organisation’s commitment to future advancements, promising the integration of more sophisticated artificial intelligence (AI) capabilities aimed at the automatic identification of various mangrove species, “In the future, we will also provide more advanced AI to automatically identify mangrove species,” concluded Wayan Eka.
