However, actual usage and the budget spent seem inconsistent with the expected performance, leading many to question the cost-effectiveness and transparency of government budget allocation. There are also concerns about whether the integration of technology and AI as tools for natural resource management truly provides benefits.
Thairath Plus explores examples of natural resource and environmental management projects where AI plays a crucial role in database creation and resolving conflicts between humans and wildlife. The problems encountered may not stem from using AI technology itself but rather from fundamental factors related to personnel, oversight, budgeting, and government management mechanisms.
In geospatial data analysis by the Geo-Informatics and Space Technology Development Agency (Public Organization), or Gistda, which handles data describing the characteristics of locations on Earth by linking geographic information with other attributes to store, analyze, and display through computer systems. Therefore, incorporating AI into data management enhances speed and accuracy in processing and analyzing information, such as
1. Satellite image analysis, where AI employs techniques like Deep Learning and Convolutional Neural Networks (CNN) to classify land use types—forests, urban areas, water, agriculture—and detect changes in land use. This supports monitoring forest encroachment, urban expansion, and water management, enabling rapid and accurate image data processing for environmental decision-making.
2. Assessing impacts from natural disasters using AI systems trained through Machine Learning on historical data to analyze and predict events such as floods, earthquakes, or wildfires, and to forecast high-risk areas in advance. For example, the UNOSAT project in Bangladesh used AI to analyze Sentinel-1 satellite images to monitor and evaluate flood impacts in 2020, allowing timely aid to affected populations.
3. Forecasting and monitoring climate change, where AI analyzes trends in temperature, rainfall, and sea level changes to plan mitigation strategies. The Climate TRACE project uses AI to gather satellite and ground sensor data for real-time monitoring of global greenhouse gas emissions.
4. Urban and infrastructure planning, utilizing AI to support smart city development by analyzing and organizing 3D map data, including traffic and population information, to reduce congestion and optimize urban resource management.Effectively.Notably, Singapore’s Virtual Singapore project has created a 3D city platform for infrastructure planning and urban development.
5. Natural resource management, where AI plays a key role in monitoring water quality, calculating carbon storage in soil and forests, and tracking sustainable fishing to minimize ecological and environmental impacts, such as with Google Earth Engineused for monitoringglobal forest changes, helping government agencies and conservation organizations nationwide to plan and protect natural resources.
Beyond geospatial data work, technology and AI significantly drive education and conservation by helping classify species, analyze images and sounds, and link global biodiversity databases so the public can easily access information and participate in data collection or environmental monitoring.
Widely known and popular applications among scientists, conservationists, and the general public include eBird and Merlin Bird ID, which are large global bird databases covering over 10,000 species with high data analysis accuracy. Both were developed by the Cornell Lab of Ornithology and can be used together with a single connected account.
eBird is used for recording and reporting bird sightings, while Merlin Bird ID assists in identifying bird species by sound, shape, or behavior. Once a species is identified, users can immediately submit sighting data as checklists to eBird, contributing to a global database used for biodiversity research and conservation.
Also including the application iNaturalist, developed by National Geographic and the California Academy of Sciences, which is a large biodiversity database covering plants, animals, fungi, and other organisms. By simply photographing an organism, AI classifies and identifies it by sound, shape, and behavior, with experts and citizen scientists able to verify and correct identifications.
It also records location and date to track and compile biodiversity data for government and related agencies to use in analyzing species status and planning conservation at local and national levels.
In recent years, technology and AI have been applied to address issues of wild elephants straying into human areas and conflicts between people and wildlife, as well as managing endangered species by using drones equipped with thermal cameras, which detect heat signatures and accurately identify whether detected animals are wild elephants or other creatures, even in dense forests or at night. This allows officials to quickly locate and count elephants to plan their return to forest areas before they reach communities or damage crops.
This system reduces workload and risk for elephant patrol officers and volunteer villagers who face elephants at close range, and supports researchers, conservationists, and organizations monitoring wildlife populations over large areas.
Especially in high-risk areas with elephant incursions, such as the forest corridors linking five eastern provinces, Kaeng Krachan National Park, Thap Lan National Park, and Kui Buri National Park, where these drones serve as primary patrol tools alongside elephant monitoring teams.
Additionally, communication technology combined with automatic camera traps and AI-based early warning systems support officials in monitoring elephants outside protected areas. This effectively helps push elephants back into forests. In 2019, Kui Buri National Park confirmed an increase in its wild elephant population from 237 to 400 individuals using thermal camera-equipped drones.
This innovation not only prevents damage to agricultural areas but also establishes peaceful coexistence strategies between humans and wild elephants, avoiding violence while enabling continuous monitoring of elephant safety and fostering harmonious human-wildlife relations.
It is clear that applying technology and AI is not limited to IT industries but can be adapted for environmental work, ecosystem and biodiversity conservation, enabling everyone to access and collaboratively build environmental databases, protect natural resources, and assist in sustainable environmental planning and management in the future.