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In the context of biodiversity conservation efforts in Indonesia and the prevention of animal and plant species extinction, artificial intelligence (AI) technology applications have become incredibly valuable tools. Using AI in this context provides convenience to experts and researchers in understanding, monitoring, and safeguarding the rich biodiversity in Indonesia.
Furthermore, AI applications can also be used to predict the trends of species extinction and analyse the factors that influence them. By studying historical data, species classifications, and relevant environmental factors, AI can generate predictive models that assist in determining effective protection and recovery measures.
AI can be utilised for large-scale data analysis and image processing to monitor endangered species. With advanced image processing techniques, AI can automatically identify animal and plant species, even in challenging situations and varying habitat conditions.
Recognising the advantages of AI in facilitating research, the National Research and Innovation Agency (Badan Riset dan Inovasi Nasional/BRIN) through the Plant Conservation Research Centre, Botanical Gardens, and Forestry (Pusat Riset Konservasi Tumbuhan, Kebun Raya, dan Kehutanan/PR KTKRK) and the Organisation for Biological Research and Environment (Organisasi Riset Hayati dan Lingkungan/OR HL) have continued to conduct comprehensive research on extinct plant species.
It includes research involving remote sensing technology and modelling to conserve endangered plants. These insights were shared by Muhammad Imam Surya, a senior researcher representing the Head of the Plant Conservation Research Centre, Botanical Gardens, and Forestry (PR KTKRK), during the 8th Garden Talk Webinar.
Meanwhile, Didit Okta Pribadi, a Senior Researcher at the Centre for Behavioral and Circular Economy Research, stated that AI-based machine learning is superior to traditional modelling. Traditional modelling only obtains the results, whereas AI obtains the modelling process and the results.
“In AI, there is a process of learning and prediction, which leads to the development of models and results. These models can be run with new data, resulting in more efficient and beneficial estimations,” said Didit.
Didit provided an example of modelling the mapping of smallholder oil palm plantations based on spatial information technology. It begins with the compilation of scientific data to identify objects through computer vision, thereby producing the characteristics of smallholder oil palm plantations.
This data is then further processed using machine learning, resulting in a model as a summary. The generated model must be validated with field data using drones as the final step.
Meanwhile, Sanjiwana Arjasakusuma, a Geography Lecturer at Gadjah Mada University provided an example of using AI in hyperspectral technology applications that he conducted to detect invasive species in Ujung Kulon National Park and Mount Merbabu National Park, as well as mapping the biophysical vegetation to calculate carbon.
The use of AI in modelling research plays a significant role, including its ability to predict future population growth, manage forests, maintain specific species populations, preserve ecosystem balance, carbon trading, and climate change.
Didit believes integrating artificial intelligence (AI) into research brings significant convenience. AI has great potential to optimise research processes quickly and accurately.
In Indonesia’s biodiversity conservation context, Didit sees AI’s immense potential in facilitating the monitoring and analysis of biodiversity. With AI, large and complex datasets can be processed efficiently, providing valuable information for researchers.
“By harnessing artificial intelligence, we can enhance our understanding of Indonesia’s biodiversity and take more effective measures to protect it,” Didit concluded.
